Conservation Agriculture: Its effects on crop and soil in rice-based cropping systems in Bangladesh

Transcription

1 Conservation Agriculture: Its effects on crop and soil in rice-based cropping systems in Bangladesh By Md. Ariful Islam MS (Agronomy) This thesis is presented for the degree of Doctor of Philosophy Of Murdoch University 2016

2 Declaration I declare that this thesis is my own account of my research and contains as its main content work which has not previously been submitted for a degree at any tertiary institution. Md. Ariful Islam II

3 Abstract Intensive rice-based cropping systems in the Eastern Indo-Gangetic Plains (Eastern India and Bangladesh) have played a pivotal role in increasing food security in that region but sustainability of these cropping systems is under threat. Conservation agriculture (CA) cropping systems based on minimum soil disturbance, crop residue retention and suitable crop rotations has been proposed to address these challenges but there has been limited research on its effects on crop productivity and soil properties in Bangladesh. This thesis examines the effects of implementing minimum soil disturbance and increased crop residue retention on soil properties and crop performance over three years in two ricebased rotations. Two field trials were conducted during in contrasting triplecropping rotations (with crop number in parentheses): 1. Legume-dominated rotation lentil (1, 4 and 7)-mungbean (2 and 5)-monsoon rice (3 and 6) in an Alluvial soil region; and 2. Cereal-dominated rotation wheat (1, 4 and 7)-mungbean (2 and 5)-monsoon rice (3 and 6) in the High Barind Tract (HBT) region of north-west Bangladesh. There were three tillage treatments in main plots strip tillage (ST), bed planting (BP) and conventional tillage (CT). Sub-plots comprised two levels of residue high residue (HR) and low residue (LR). Puddled transplanted rice was applied in CT and unpuddled transplanted rice in ST and BP. This thesis focuses on soil properties and the growth and yield of the cool-dry season crops in each year, namely lentil on the Alluvial soil and wheat on the HBT soil. During the first two growing seasons treatment effects on soil properties and crop performance were marginal but became clearly apparent in the third year. In the legumedominated system, grain yield of lentil was 15 % higher in HR than LR averaged across all tillage types in Year 2. In Year 3, the yield of lentil was higher by 23 % in ST and 18 % in BP compared with CT. In the cereal-dominated system, grain yield was not affected by tillage and residue treatments in Year 1. However, in Year 2, grain yield of wheat was depressed by 39 % in BP due to poor crop establishment. In Year 3, the yield of wheat was greater by 9 % in ST and 7 % in BP than CT; wheat yield of HR was 3 % higher compared to LR. III

4 The soil water content (SWC) increased and bulk density (BD) and penetration resistance (PR) decreased in surface soil (0-5 cm) with ST and at 5-10 cm and cm soil depth with BP, compared to CT. The retention of more intact residue left between the plant rows conserved more SWC and lowered the soil BD and PR of surface soil under ST. Implementation of ST and BP with HR treatment gradually improved soil physical properties and alleviated puddling effects that characterise current practices (CT and LR) in rice-based systems. Such improvements are probably due to increases in soil organic carbon (SOC) and total nitrogen (TN) with ST and BP. Greater root growth under BP was not associated with increased grain yield. However, the overall improvement in soil surface conditions and greater root growth at depth may have allowed extraction of water and nutrients from a larger soil volume in ST resulting in a gradual increase in crop productivity over time. After 2.5 years in both legume- and cereal-dominated rotations, the SOC concentrations, SOC-stocks and labile C fraction (water soluble carbon WSC) at cm soil depth were greater in ST than CT. By contrast, the SOC concentrations and storage, and WSC increased at cm soil depth in BP compared to CT and ST. Soil C losses through the emission of CO2 were greater in CT than ST and BP. The relative efficacy of tillage in storing SOC was in the order of ST>BP>CT. High residue retention increased SOC concentrations, SOC storage, WSC and CO2 emission from soil. In the cereal-dominated rotation, ST sequestered Mg C/ha annually while CT caused Mg C/ha loss at 0-15 cm soil depth. In contrast to the legume-dominated rotation, neither CT nor ST sequestered SOC but ST reduced the loss by 0.40 Mg C/ha annually compared to CT. Based on the C balance, it is estimated that annual carbon inputs of 3.8 Mg C/ha under ST and 6 Mg C/ha under CT condition in the legume-dominated system, and 1.0 Mg C/ha under ST and 7.7 Mg C/ha under CT condition in the cereal-dominated system, would be required to maintain SOC at the antecedent level. IV

5 In the present study, ST and HR treatment increased TN, N-stocks, total soluble nitrogen and potentially mineralizable nitrogen (PMN) in the surface soil (0-7.5 cm) as compared to CT and LR at the end of Crop 7. In ST and HR, the lower mineral N (NH₄-N and NO₃-N) and larger PMN indicated the greater immobilization or less mineralization of N, or both, and restricted the potential losses of N. Retention of HR resulted in positive N balance while LR caused a negative N balance. Regardless of treatment variation, the soil TN, N-stocks and available N were greater in the cereal-dominated cropping system than in the legumedominated system, probably due to carry-over of higher N fertilizer rates applied to the cereal crop, and greater above- and below-ground biomass. The changes of soil TN due to residue were only apparent in legume-dominated system. The greater input derived from nitrogenous residue of mungbean and lentil may account for the positive effects of HR in the legume-dominated system. Application of ST and HR has potential for increasing carbon sequestration and N accumulation while reducing N losses, hence improving soil properties and thereby crop growth and yields, within 2-3 years in rice-based systems of Bangladesh. However, further studies are required over a longer time period to evaluate the performance of unpuddled rice rotated with ST non-rice crops with a range of residue retention levels under different soil, climatic, and socio-economic conditions in the eastern Indo-Gangetic Plains. V

6 Table of Contents Declaration... II Abstract... III Table of Contents... VI List of Tables... XVIII List of Figures... XXIV Appendices... XXXVII List of Abbreviations... XXXVIII List of Botanical Names... XLIII Acknowledgements... XLIV 1 Literature Review Introduction Conventional agriculture: basic concepts Concept of tillage Crop residue management options under conventional system Concept of conservation agriculture The key components of Conservation Agriculture Minimum soil disturbance Minimum tillage No-tillage Strip tillage Permanent raised planting VI

7 1.4.2 Permanent ground cover: residue management Crop rotation Crop diversification in rice-based systems Inclusion of legumes in rice-based systems Development of conservation agriculture Conservation agriculture adoption worldwide Constraints of conservation agriculture Effect of conservation agriculture on crop performance and system productivity Influence of conservation agriculture on soil properties Soil physical properties Soil structure and aggregation Soil bulk density and porosity Soil penetration resistance Soil water content Effects of conservation agriculture on soil organic carbon and its fractions Soil organic carbon Soil organic carbon turnover Water soluble carbon Carbon dioxide (mineralization, root and microbial respiration) Effects of conservation agriculture on soil nitrogen dynamics Total soil nitrogen Mineral nitrogen Potentially mineralizable nitrogen Research gaps and objectives VII

8 2 Effects of tillage and residue management on yield and yield attributes of winter crops in rice-based systems in Bangladesh Introduction Materials and Methods Climate and weather Experimental design and treatments Residue management protocols Agronomy of legume-dominant system Nutrient management Disease, weed and pest management of lentil Agronomic measurements of lentil Agronomy of cereal-dominated systems Crop husbandry of wheat Agronomic measurements of wheat Yield measurements for lentil and wheat Statistical analysis Results Weather Tillage and residue effects on crop performance of legume-dominated system Seed and straw yield of lentil Yield components of lentil Correlation and regression of yield and yield components of lentil Yield performance of rice and mungbean in legume-dominated system Tillage and residue effects on crop performance of cereal-dominated system Grain and straw yield of wheat VIII

9 Yield components of wheat Correlation and regression of yield and yield components of wheat Yield performance of rice and mungbean in cereal-dominated system Discussion Lentil Wheat Cropping system productivity Conclusions Effects of tillage and residue management on soil strength, soil water and crop root growth in rice-based systems on silty loam soil in Bangladesh Introduction Materials and method Treatment details Measurement of soil water content and penetration resistance Root sampling of lentil Nodulation of lentil Root sampling of wheat Measurement of root parameters Statistical analysis Results Soil physical properties during root assessment of lentil at Alipur Volumetric soil water content Soil penetration resistance Root characteristics of lentil Root and shoot growth and their ratio for lentil IX

10 3.3.4 Nodulation of lentil Soil physical properties during root assessment of wheat at Digram Volumetric soil water content Soil penetration resistance Root characteristics of wheat Root and shoot growth, and their ratio of wheat Discussion Soil penetration resistance and soil water content Root distribution as affected by tillage and residue over time Rooting patterns of wheat and lentil Root distribution related to soil water content and penetration resistance Above-ground shoot growth and yield influenced by rooting patterns Conclusion Effects of tillage and residue management on soil physical properties in rice-based cropping systems in Bangladesh Introduction Materials and methods Treatments and crop management Soil bulk density Soil temperature Volumetric soil water content Soil penetration resistance Sampling time and location Statistical analysis Results Alipur X

11 Soil bulk density Tillage effects Residue effects Volumetric soil water content and penetration resistance Tillage effects Residue effects Trends of volumetric soil water content and penetration resistance following planting of lentil Tillage effects Residue effects Relationship between soil physical properties Relation between soil bulk density and penetration resistance Depth distribution of soil physical parameters at bed planting and strip tillage system in Alipur Distribution of soil bulk density Distribution of volumetric soil water content Distribution of soil penetration resistance Soil temperature at Alipur Digram Soil bulk density at different depth Tillage effects Residue effects Volumetric soil water content and penetration resistance Tillage effects XI

12 Residue effects Trends of volumetric soil water content and penetration resistance following planting of wheat Tillage effects Residue effects Relationship between soil physical properties Relation between soil bulk density and penetration resistance Depth distribution of soil physical parameter at bed planting and strip tillage system in Digram Distribution of soil bulk density Distribution of volumetric soil water content Distribution of soil penetration resistance Soil temperature at Digram Discussion Soil bulk density and penetration resistance Volumetric soil water content System differences Conclusion Short-medium term effects of conservation management practices on soil organic carbon pools in rice-based systems in Bangladesh Introduction Materials and Methods Experimental site and treatment details Quality assurance and quality control procedures XII

13 5.2.3 Estimation of annual C inputs Soil sampling and analytical methods Bulk density Soil organic carbon, SOC-stocks and stratification ratio Soil carbon sequestration and C build-up or C losses (%) Water soluble organic carbon Measurement of soil carbon dioxide emission Statistical analysis Results Alipur Soil organic carbon concentrations Distribution and stratification of SOC concentrations at strip tillage system in Alipur Distribution and stratification of SOC concentrations at bed planting system in Alipur Temporal variation of soil organic carbon concentrations Soil organic carbon stocks and sequestration Water soluble carbon Carbon dioxide-carbon (CO₂-C) emission Correlation among different organic carbon pools Carbon balances Digram Soil organic carbon concentrations Distribution and stratification of SOC concentrations at strip tillage system in Digram XIII

14 Distribution and stratification of SOC concentrations at bed planting system in Digram Temporal variation of SOC Soil organic carbon stocks and sequestration Water soluble carbon Carbon dioxide-carbon (CO₂-C) emission Correlation among different organic carbon pools Carbon balances Discussion Tillage effects Residue effects Dynamics of soil organic carbon concentrations Distribution and stratification of soil organic carbon concentrations Cropping system differences Conclusions Effects of tillage and residue on N cycling and dynamics in two paddy soils in Bangladesh Introduction Materials and methods Site description and field management Plant measurements Soil measurements Soil sampling procedures Bulk density Total soil N and N-stocks XIV

15 Soil N accumulation Nitrogen uptake Mineral N pools Anaerobic potentially mineralizable N Total soluble N Nitrogen balance calculations Statistical analysis Results Alipur Total soil N concentrations Distribution and stratification of total soil N concentrations at strip tillage system in Alipur Distribution and stratification of total soil N concentrations at bed planting system in Alipur Temporal variation of soil total nitrogen concentrations N-stocks Nitrogen accumulation Nitrogen uptake by lentil plants Mineral N pools (NH₄-N plus NO₃-N) Anaerobic potentially mineralizable N Total soluble N Plant N concentrations of lentil Relationships among TN, N-stocks, plant N and the available indices of N XV

16 Nitrogen balances Digram Total soil N concentrations Distribution and stratification of total soil N concentrations at strip tillage system in Digram Distribution and stratification of total soil N concentrations at bed planting system in Digram C: N ratio N-stocks N uptake by wheat plants Mineral N pools (NH₄-N plus NO₃-N) Anaerobic potentially mineralizable N Total soluble N Plant N concentrations in wheat Relationships among TN, N-stocks, plant N and the available indices of N Nitrogen balances at Digram Discussion Soil total N concentrations and N-stocks Nitrogen balance Nitrogen turnover and cycling Responses of plant growth and plant N to N supply Cropping system differences Optimum N management under CA system Conclusions XVI

17 7 General discussion and conclusions Tillage and residue management effects on crop performance and soil properties Non-treatment factors affecting crop growth and yield Constraints of different treatments and their potential solution Prospects and future research directions Conclusion References XVII

18 List of Tables Table 1.1. Area of arable crop land under conservation agriculture by region in Table 1.2. Summary of major constraints of conservation agriculture systems 20 Table 1.3. Constraints to cropping systems in the Indo-Gangetic Plains 22 Table 2.1. Site characteristics of two different experiments under different 41 cropping systems Table 2.2. Basic soil properties and nutrient status of study sites at Alipur and 43 Digram Table 2.3. Details of three tillage treatments at Alipur and Digram 44 Table 2.4. Details of residue management protocols of the lentil-mungbeanmonsoon 45 rice cropping sequence at Alipur in Table 2.5. Details of residue management protocols of wheat-mungbeanmonsoon 46 rice cropping sequence at Digram in Table 2.6. Details of crop, variety, seed rate or seedlings/hill, row spacing, 47 sowing and harvesting date of lentil-mungbean-monsoon rice cropping sequence during at Alipur Table 2.7. Details of disease, insects and weeds in lentil and their management 49 practices Table 2.8. Details of crop, variety, seed rate or seedlings/hill, row spacing,, 50 sowing and harvesting date of wheat-mungbean-monsoon rice cropping sequence at Digram during Table 2.9. Tillage and residue effects on plant population and branching of lentil 56 Table Tillage and residue effects on plant population (%) affected by foot 57 and collar rot diseases of lentil in Table Tillage and residue effects on plant height, pods/plant and seeds/plant 58 of lentil Table 2.12 Tillage and residue effects on 1000-seed weight and harvest index 60 Table Correlation matrix of important yield attributes and yields of lentil 61 XVIII

19 Table Tillage and residue effects on grain and straw yield of rice and 63 mungbean of lentil-mungbean-monsoon rice cropping system in Alipur. Note: no yield results are available for Crop 2 (mungbean) due to crop damage by heavy rainfall Table Tillage and residue effects on plant population and plant height (cm) 65 of wheat Table Tillage and residue effects on tillers and effective tillers per plant of 67 wheat Table Tillage and residue effects on spikes/m², spike length (cm) and 68 spikelets/spike of wheat Table Tillage and residue effects on grains/spike, 1000-seed weight and 69 harvest index (%) of wheat Table Correlation matrix of important yield attributes and yields of wheat 71 Table Tillage and residue effects on grain and straw yield of rice and 73 mungbean of wheat-mungbean-monsoon rice cropping system in Digram. Note; no yield results are available for Crop 2 (mungbean) due to crop damage by heavy rainfall Table 3.1. Total root dry weight, shoot dry weight and root to shoot ratio (g/g) of 93 five lentil plants under different tillage and residue management at Alipur Table 3.2. Tillage and residue effects on nodulation of lentil in legumedominated 95 rice-based system Table 3.3. Total root dry weight, shoot dry weight and root to shoot ratio (g/g) of 103 five wheat plants under different tillage and residue management at Digram Table 4.1. Soil bulk density (g/cc) at three different depths (0-5 cm, 5-10 cm and cm) under tillage and residue after different crop in legumedominated system in Alipur 121 XIX

20 Table 4.2. Soil penetration resistance (MPa) at three different depths (0-5 cm, cm and cm) under tillage and residue after different crop in cereal-dominated system in Digram Table 5.1. Carbon dioxide measurements at different crop growth stages during of rice-based system Table 5.2. Tillage and residue effects on soil organic carbon concentrations and 163 stratification ratio of SOC concentrations during 2.5 years of legumedominated rice-based system at Alipur Table 5.3. Tillage and residue effects on soil organic carbon stocks (Mg C/ha) and 167 sequestration (Mg C/ha/yr) of legume-dominated rice-based system at Alipur Table 5.4. Tillage and residue effects on water soluble carbon (mg/kg) of legumedominated 168 rice-based system at Alipur Table 5.5. Correlation among soil organic carbon forms of legume-dominated 170 rice-based system at Alipur in (n = 96) Table 5.6. Estimated carbon balance for the legume-dominated rice-based 172 rotation at Alipur considering residue of eight consecutive crops in STHR = strip tillage-high residue; STLR = strip tillage-low residue; CTHR = conventional tillage-high residue; CTLR = conventional tillage-low residue Table 5.7. Tillage and residue effects on soil organic carbon concentrations and 174 stratification ratio of SOC concentrations during 2.5 years of legumedominated rice-based system at Digram Table 5.8. Tillage and residue effects on soil SOC-stocks (Mg C/ha) and 178 sequestration (Mg C/ha/yr) of cereal-dominated rice-based system at Digram Table 5.9. Tillage and residue effects on water soluble carbon (mg/kg) of cerealdominated rice-based system at Digram 179 Table Tillage and residue effects on CO₂-emission (g CO2 m -2 day -1 ) at 180 XX

21 different growth stages of wheat at Digram in Table Correlation among soil organic carbon forms of cereal-dominated ricebased system at Digram in (n = 96) Table Estimated carbon balance for the cereal-dominated rice-based rotation at Digram considering residue of eight consecutive crops in STHR = strip tillage-high residue; STLR = strip tillage-low residue; CTHR = conventional tillage-high residue; CTLR = conventional tillage-low residue Table 6.1. Tillage and residue effects on total soil N concentrations and stratification ratio of TN concentrations during 2.5 years of the legume-dominated rice-based cropping system at Alipur Table 6.2. Tillage and residue effects on N-stocks (Mg N/ha) and N-accumulation rate during 2.5 years of the legume-dominated rice-based cropping system at Alipur Table 6.3. Tillage and residue effects on N uptake by lentil plants in , and Table 6.4. Tillage and residue effects on mineral N (mg N/kg) at 0-15 cm depth at Alipur in Table 6.5. Tillage and residue effects on mineral N (mg N/kg) at and cm soil depth at Alipur in Table 6.6. Tillage and residue effects on potentially mineralizable N (PMN) at and cm soil depth at Alipur in Table 6.7. Tillage and residue effects on total soluble N in legume-dominated rice-based cropping system at Alipur in Table 6.8. Tillage and residue effects on plant N concentrations of lentil in , and Table 6.9. Correlation matrix for the relationships among soil total N (TN), N- stocks, lentil plant N and the indices of N availability at 0-15 cm at Alipur in (n = 24) XXI

22 Table Estimated nitrogen balance for the legume-dominated rice-based rotation at Alipur considering residue of eight consecutive crops in STHR = strip tillage-high residue; STLR = strip tillage-low residue; CTHR = conventional tillage-high residue; CTLR = conventional tillage-low residue Table Tillage and residue effects on total soil N (TN) concentrations and stratification ratio (SR) of TN concentrations during 2.5 years of a cereal-dominated rice-based cropping system at Digram Table Tillage and residue effects on C-N ratio during 2.5 years of a cerealdominated rice-based cropping system at Digram Table Tillage and residue effects on N-stocks (Mg N/ha) and N accumulation rates of the cereal-dominated rice-based cropping system in at Digram Table Tillage and residue effects on N uptake by wheat plants in , and Table Tillage and residue effects on mineral N (mg N/kg) at 0-15 cm soil depth in at Digram Table Tillage and residue effects on mineral N (mg N/kg) at and cm soil depth in at Digram Table Tillage and residue effects on anaerobic potentially mineralizable N (PMN) at Digram in Table Tillage and residue effects on total soluble N in legume-dominated rice-based system at Digram in Table Tillage and residue effects on plant N concentrations of wheat in , and Table Correlation matrix for the relationships among TN, N-stocks, plant N and the available indices of N at Digram at 0-15 cm in (n = 24) Table Estimated nitrogen balance for the cereal-dominated rice-based rotation at Digram considering residue of eight consecutive crops in XXII

23 STHR = strip tillage-high residue; STLR = strip tillage-low residue; CTHR = conventional tillage-high residue; CTLR = conventional tillage-low residue XXIII

24 List of Figures Figure 1.1. Schematic diagram of rice-dryland ecosystem showing conventional 2 and conservation management. Adapted from Zhou et al.(2014) Figure Potential benefits of conservation agriculture at eco-system level. 6 Adapted from Srinivasarao et al. (2015) Figure 1.3. The activities of farmer s cultivation techniques, a) puddling for rice 7 cultivation, b) conventional cropping based on intensive tillage, c) broadcast seed and fertilizer, d) levelling following tillage and e) crop residue burning Figure Problems associated with conventional agriculture systems in ricebased 8 system in Indo-Gangetic Plains. Modified from Devkota (2011) Figure 1.5. A Versatile Multi-crop Planter is using for strip tillage 11 Figure 1.6. A Versatile Multi-crop Planter is using for reshaping permanent 12 raised bed Figure 1.7. Extent of global area of conservation agriculture over time. 18 (Source: above the respective bar) Figure 1.8. The soil nitrogen cycle. Adapted from Hofman and Cleemput (2004) 32 Figure 2.1. General soil map of Bangladesh showing field study sites (A); High 42 Barind Tract, Digram, Godagari, Rajshahi (red circle) in figure (B); and; Alipur, Durgapur, Rajshahi (yellow circle) in figure (C) Figure 2.2. Monthly and annual rainfall, mean maximum and minimum 54 temperatures over the 33-months period of at the experimental site Figure 2.3. Effects of tillage and residue retention on lentil seed yield (Figure a1-c1) and straw yield (Figure a2 c2) over three growing seasons. ST strip tillage, BP bed planting, CT conventional tillage; HR high residue, LR low residue. Values are means of four replicates ± standard error of mean and the floating error bar on 55 XXIV

25 Figure 2.4. Figure 2.5. Figure 2.6. Figure 3.1. Figure 3.2. Figure 3.3. each figure represents the least significant difference (LSD) for significant effects at P 0.05 Regression of a) plant population and seed yield, b) branches/plant and seed yield and c) pods/plant and seed yield for three years of results ( ) Effects of tillage and residue on wheat grain yield (Figure a1-c1) and straw yield (Fig a2 c2). ST strip tillage, BP bed planting, CT conventional tillage; HR high residue, LR low residue. Values are means of four replicates, ± standard error of mean and the floating error bar on each figure represents the least significant difference (LSD) for significant effects only at P 0.05 Regression of a) plant population and grain yield, b) spikes/m² and grain yield and c) spikelets/spike and grain yield for three years of results ( ) Tillage and residue effects on mean volumetric soil water content (%) (a1-a3) and mean penetration resistance (MPa) (b1-b3) at three soil depths (0-5 cm, 5-10 cm and cm) at Alipur during to The floating error bars indicate the average least significant difference (LSD) at P 0.05 for significant treatment and depth difference Tillage and residue effects on lentil root distribution at 0-15 cm soil depth during the growing season. Root parameters measured are a) Root volume (cm³), b) Root dry weight (g), c) Root length (m), d) Root length density-rld (cm/cm³) and e) Specific root length-srl (m/g). Error bars indicate ± 1 standard error of the mean Tillage and residue effects on lentil root distribution at 0-10 cm and cm soil depth during the growing season. Root parameters measured are a) Root volume (cm³), b) Root dry weight XXV

26 Figure 3.4. Figure 3.5. Figure 3.6. Figure 3.7. Figure 3.8. (g), c) Root length (m), d) Root length density-rld (cm/cm³) and e) Specific root length-srl (m/g). Error bars indicate ± 1 standard error of the mean Tillage and residue effects on lentil root distribution at 0-10 cm and cm soil depth during the growing season. Root parameters measured are a) Root volume (cm³), b) Root dry weight (g), c) Root length (m), d) Root length density-rld (cm/cm³) and e) Specific root length-srl (m/g). Error bars indicate ± 1 standard error of the mean Tillage and residue effects on mean volumetric soil water content (%) (a1-a3) and mean penetration resistance (MPa) (b1-b3) at three soil depths (0-5 cm, 5-10 cm and cm) at Digram during to The floating error bars indicate the average least significant difference (LSD) at P 0.05 for significant treatment and depth difference Tillage and residue effects on wheat root distribution at 0-50 cm soil depth (10 cm increments of five soil depths) during the growing season. Root parameters measured are a) Root volume (cm 3 ), b) Root dry weight (g), c) Root length (m), d) Root length density-rld (cm/cm 3 ) and e) Specific root length-srl (m/g). Error bars indicate ± 1 standard error of the mean Tillage and residue effects on wheat root distribution at 0-60 cm soil depth (10 cm increments of six soil depths) during the growing season. Root parameters measured are a) Root volume (cm 3 ), b) Root dry weight (g), c) Root length (m), d) Root length density-rld (cm/cm 3 ) and e) Specific root length-srl (m/g). Error bars indicate ± 1 standard error of the mean Tillage and residue effects on wheat root distribution at 0-70 cm soil depth (10 cm increments of seven soil depths) during the XXVI

27 13 growing season. Root parameters measured are a) Root volume (cm 3 ), b) Root dry weight (g), c) Root length (m), d) Root length density-rld (cm/cm 3 ) and e) Specific root length-srl (m/g). Error bars indicate ± 1 standard error of the mean Figure 4.1. Relationship between volumetric water content (SWC) (%) (calculated from the gravimetric soil water content) and MP406 volumetric water content (θprobe) (%) for the data collected at 5 cm increments down the soil profile collected after 7 crops at Alipur (, ) and Digram (, ) in The soil profile depth was to 15 cm. Symbols are data points and the line represents the regression equation shown above Figure 4.2. Schematic diagram of strip tillage plot showing the location of measurements of soil water content and penetration resistance in between the strips (closed black circle) and in the strip (open black circle) in a strip-tillage plot Figure 4.3. Schematic diagram of the newly formed bed. The blue circles indicates the sampling spot of centre of the bed (closed symbol) and furrow of the bed (open symbol) for soil moisture, soil penetration resistance and bulk density measurements Figure 4.4. Tillage effects on soil bulk density over cropping cycles-initially and after Crops 1, 3, 4, 6 and 7 at 0-5 cm, 5-10 cm and cm soil depths in Alipur. Values are means across residue levels. The error bars for each data point represents ± 1 standard error. The floating error bars on the figure at each depth represent the least significant difference (LSD) at P 0.05 for tillage after each crop (T) and interaction between tillage and cropping cycle (TXCC) Figure 4.5. Residue effects on soil bulk density after different cropping cycles initially and after Crops 1, 3, 4, 6 and 7 at 0-5 cm, 5-10 cm and cm soil depths in Alipur. Values are means across tillage XXVII

28 Figure 4.6. Figure 4.7. Figure 4.8. Figure 4.9. treatments. The error bars for each data point represents ± 1 standard error. The floating error bars on the figure at each depth represent the least significant difference (LSD) at P 0.05 for residue after each crop Dynamic changes of volumetric soil water content (%) and penetration resistance (MPa) due to tillage after Crops 1, 3, 4, 6 and 7 at 0-5 cm, 5-10 cm and cm soil depths in Alipur. Values are means across residue levels. Error bars were ± 1 standard error of the mean and floating bar indicates significant difference at P 0.05 level between treatments on that time of measurement Dynamic changes of volumetric soil water content (%) and penetration resistance (MPa) due to residue after Crops 1, 3, 4, 6 and 7 at 0-5 cm, 5-10 cm and cm soil depths in Digram. Values are means across tillage treatments. Error bars were ± 1 standard error of the mean and floating error bars indicate significant difference at P 0.05 level between treatments on that time of measurement The volumetric soil water content (%) (a1-a3) and soil penetration resistance (b1-b3) at 0-5 cm, 5-10 cm and cm soil depths for different tillage treatments at 5 days after sowing (DAS) to 35 DAS during lentil planting in 2013 in Alipur. Values are means across residue levels. Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of tillage on that dates of measurement and error bars indicate ± 1 standard error of the mean The volumetric soil water content (%) (a1-a3) and soil penetration resistance (b1-b3) at 0-5 cm, 5-10 cm and cm soil depths for different residue treatments at 5 days after sowing (DAS) to 35 DAS during lentil planting in 2013 in Alipur. Values are means XXVIII

29 Figure Figure Figure Figure across tillage treatments. Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of tillage on that date of measurement and error bars indicates ± 1 standard error of the mean Relationship between soil penetration resistance (MPa) and bulk density (g/cc) after different crop determined: a) after Crop 1; b) after Crop 3; c) after Crop 4; d) after Crop 6; e) after Crop 7 during in Alipur. Values are for all three depths (0-5 cm, 5-10 cm and cm). The line represents the regression equation shown above in the graph Variation of soil bulk density after Crop 7 in Alipur relative to depth from the bed top (BT) and from the level of the bed top in the furrow (BF) of the bed planting system (a); and in the strip (IS) and off-the strip (OS) of strip tillage system (b). For comparison, initial values (before starting the experiment) are also shown. Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of sampling positions Variation of volumetric soil water content (%) after Crop 7 in Alipur relative to depth from the bed top (BT) and from the level of the bed top in the furrow (BF) of the bed planting system (a); and in the strip (IS) and off-the strip (OS) of strip tillage system (b). For comparison, initial values (before starting the experiment) are also shown. Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of sampling positions Variation of soil penetration resistance (MPa) after Crop 7 in Alipur relative to depth from the bed top (BT) and from the level of the bed top in the furrow (BF) of the bed planting system (a); and in the strip (IS) and off-the strip (OS) of strip tillage system (b). For comparison, initial values (before starting the experiment) are also XXIX

30 Figure Figure Figure Figure Figure shown. Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of sampling positions The variation of mean soil day (a) and night soil temperature ( C) (b) due to different treatments during wheat growing season at Alipur in Values are means of seven day intervals Tillage effects on soil bulk density over cropping cycles - initially and after Crops 1, 3, 4 and 6 at 0-5 cm, 5-10 cm and cm soil depths in Digram. Values are means across residue levels. The error bars for each data point represents ± 1 standard error. The floating error bars on figure at each depth represent the least significant difference (LSD) at P 0.05 for tillage after each crop (T) and interaction between tillage and cropping cycles (TXCC) Residue effects on soil bulk density after different cropping cycles initially and after Crops 1, 3, 4 and 6 at 0-5 cm, 5-10 cm and cm soil depths in Digram. Values are means across tillage treatments. The error bars for each data point represents ± 1 standard error. The floating error bars on figure at each depth represent the least significant difference (LSD) at P 0.05 for residue after each crop Dynamic changes of volumetric soil water content (%) and penetration resistance (MPa) due to tillage after Crops 1, 3, 4, 6 and 7 at 0-5 cm, 5-10 cm and cm soil depths in Digram. Values are means across residue levels. Error bars were ± 1 standard error of the mean and floating error bar indicates significant difference at P 0.05 level between treatments on that time of measurement Dynamic changes of volumetric soil water content (%) and penetration resistance (MPa) due to residue after Crops 1, 3, 4, 6 and 7 at 0-5 cm, 5-10 cm and cm soil depths in Digram. Values are means across tillage treatments. Error bars were ± XXX

31 Figure Figure Figure Figure standard error of the mean and floating error bar indicates significant difference at P 0.05 level between treatments on that time of measurement The volumetric soil water content (%) (a1-a3) and soil penetration resistance (b1-b3) at 0-5 cm, 5-10 cm and cm soil depths for different tillage treatments at 5 days after sowing (DAS) to 35 DAS during wheat planting in 2013 in Digram. Values are means across residue levels. Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of tillage on that date of measurement and error bars indicates ± 1 standard error of the mean The volumetric soil water content (%) (a1-a3) and soil penetration resistance (b1-b3) at 0-5 cm, 5-10 cm and cm soil depths for different residue treatments at 5 days after sowing (DAS) up to 35 DAS during wheat planting in 2013 in Digram. Values are means across tillage treatments. Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of tillage on that dates of measurement and error bars indicate ± 1 standard error of the mean Relationship between soil penetration resistance (MPa) and bulk density (g/cc) after different crop determined: a) after Crop 1; b) after Crop 3; c) after Crop 4; d) after Crop 6 during in Digram. Values are for all three depths (0-5 cm, 5-10 cm and cm). The line represents the regression equation shown above in the graph Variation of soil bulk density after Crop 6 in Digram relative to depth from the bed top (BT) and from the level of the bed top in the furrow (BF) of the bed planting system (a); and in the strip (IS) and off-the strip (OS) of strip tillage system (b). For comparison, XXXI

32 Figure Figure Figure Figure 5.1. Figure 5.2. initial values (before starting the experiment) are also shown. Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of sampling positions Variation of volumetric soil water content (%) after Crop 7 in Digram relative to depth from the bed top (BT) and from the level of the bed top in the furrow (BF) of the bed planting system (a); and in the strip (IS) and off-the strip (OS) of strip tillage system (b). For comparison, initial values (before starting the experiment) are also shown. Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of sampling positions Variation of soil penetration resistance (MPa) after Crop 7 in Digram relative to depth from the bed top (BT) and from the level of the bed top in the furrow (BF) of the bed planting system (a); and in the strip (IS) and off-the strip (OS) of strip tillage system (b). For comparison, initial values (before starting the experiment) are also shown. Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of sampling positions The variation of mean soil day (a) and night soil temperature ( C) (b) due to different treatments during wheat growing season at Digram in Values are means of seven day intervals Schematic representation of CO₂ production processes in soil. Those processes are root respiration, rhizosphere respiration, litter decomposition, and oxidation of SOM. Adapted from Luo and Zhou (2006) Variation of soil organic carbon concentrations at different cropping seasons in Alipur relative to depth (at 0-15 cm soil depth before starting of the experiment Initial, after Crop 1 and after Crop 4, and at cm and cm soil depth after Crop 7) in the strip (IS) and off-the strip (OS) of strip tillage system (ST) XXXII

33 Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of sampling location of strip tillage system Figure 5.3. Variation of soil organic carbon concentrations at different 165 cropping seasons in Alipur relative to depth (at 0-15 cm soil depth before starting of the experiment Initial, after Crop 1 and after Crop 4, and at cm and cm soil depth after Crop 7) from the bed top (BT) and from the level of the bed top in the furrow (BF) of the bed planting system (BP). Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of sampling location of bed planting system Figure 5.4. Temporal variation of soil organic carbon concentrations at Alipur. 166 The floating error bar indicates the average least significant difference (LSD) at P 0.05 for the different cropping cycles and tillage. Values are means across residue levels Figure 5.5. Tillage effects on CO₂ flux (g CO₂ m²/day) at different growth stages 169 of lentil in Alipur in and The floating error bar on each figure represents the least significant difference (LSD) at P 0.05, for the different crop growth stages where they were significantly different. Values are means across residue levels Figure 5.6. Residue effects on CO₂ flux (g CO₂ m²/day) at different growth 170 stages of lentil in Alipur in and The floating error bar on each figure represents the least significant difference (LSD) at P 0.05, for the different crop growth stages where there were significant treatment differences. Values are means across tillage treatments Figure 5.7. Relationship between cumulative C input and SOC sequestration 173 during 2.5 years under ST and CT conditions of legume-dominated rice based system at Alipur Figure 5.8. Variation of soil organic carbon concentrations at different 175 XXXIII

34 Figure 5.9. Figure Figure Figure Figure cropping seasons in Digram relative to depth (at 0-15 cm soil depth before starting of the experiment Initial, after Crop 1 and after Crop 4, and at cm and cm soil depth after Crop 7) in the strip (IS) and off-the strip (OS) of strip tillage system (ST). Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of sampling location of strip tillage system Variation of soil organic carbon concentrations at different cropping seasons in Digram relative to depth (at 0-15 cm soil depth before starting of the experiment Initial, after Crop 1 and after Crop 4, and at cm and cm soil depth after Crop 7) from the bed top (BT) and from the level of the bed top in the furrow (BF) of the bed planting system (BP). Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of sampling location of bed planting system Temporal variation of soil organic carbon (SOC) at Digram. The floating error bar indicates the average least significant difference (LSD) at P 0.05 for the different cropping cycles where they were significantly different. Values are means across residue levels Tillage effects on CO₂ flux (g CO₂ m²/day) at different growth stages of wheat in Digram. The floating error bar on each figure represents the least significant difference (LSD) for significant effects at P Values are means across residue levels Residue effects on CO₂ flux (g CO₂ m²/day) at different growth stages of wheat in Digram. The floating error bars represent the least significant difference (LSD) for significant effects at P 0.05 for each sampling time. Values are means across treatments Relationship between cumulative C input and SOC sequestration during 2.5 years under ST and CT conditions of cereal-dominated rice based system at Digram XXXIV

35 Figure 6.1. Figure 6.2. Figure 6.3. Figure 6.4. Figure 6.5. Figure 6.6. The conceptual model of N cycling of conservation agriculture system Variation of soil total nitrogen concentrations at different cropping seasons in Alipur relative to depth (at 0-15 cm soil depth before starting of the experiment Initial, after Crop 1 and after Crop 4, and at cm and cm soil depth after Crop 7) in the strip (IS) and off-the strip (OS) of strip tillage system (ST). Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of sampling location of strip tillage system Variation of soil total nitrogen concentrations at different cropping seasons in Alipur relative to depth (at 0-15 cm soil depth before starting of the experiment Initial, after Crop 1 and after Crop 4, and at cm and cm soil depth after Crop 7) from the bed top (BT) and from the level of the bed top in the furrow (BF) of the bed planting system (BP). Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of sampling location of bed planting system Temporal variation of total soil nitrogen concentrations at Alipur. The floating error bar indicates the average least significant difference (LSD) at P 0.05 for the different cropping cycles and tillage. Values are means across residue levels Variation of soil total nitrogen concentrations at different cropping seasons in Digram relative to depth (at 0-15 cm soil depth before starting of the experiment Initial, after Crop 1 and after Crop 4, and at cm and cm soil depth after Crop 7) in the strip (IS) and off-the strip (OS) of strip tillage system Variation of soil total nitrogen concentrations at different cropping seasons in Digram relative to depth (at 0-15 cm soil depth before starting of the experiment Initial, after Crop 1 and after Crop 4, XXXV

36 Figure 6.7. and at cm and cm soil depth after Crop 7) from the bed top (BT) and from the level of the bed top in the furrow (BF) of the bed planting system (BP). Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of sampling location of bed planting system Influences of crop residue on inorganic nitrogen transformation process. Modified from Chen (2014) 243 XXXVI

37 Appendices Appendix 1 Appendix 2 The soil organic carbon concentrations at different depths in furrow of the bed Tillage and residue effects on C-N ratio in legume-dominated rice-based system at Alipur in XXXVII

38 List of Abbreviations 1000-seed weight TSW 2-wheel tractor 2-WT 4-wheel tractor 4-WT Agro-ecological zone AEZ Ammonia nitrogen NH₃-N Ammonium nitrogen NH₄-N Analysis of variance ANOVA Approximately ~ Arsenic As Australian Centre for International Agricultural Research ACIAR Bangladesh Agricultural Research Council BARC Bangladesh Agricultural Research Institute BARI Bangladesh Agricultural University BAU Bangladesh Bureau of Statistics BBS Bangladesh Economic Review BER Bangladesh Institute of Development Studies BIDS Bangladesh Rice Research Institute BRRI Bed planting system BP Biological nitrogen fixation BNF Carbon C Carbon dioxide CO₂ Carbon dioxide-carbon CO₂-C Carbon-nitrogen ratio C:N ratio Cation exchange capacity CEC Centimetre cm Centimoles of charge per kilogram cmol/kg Coefficient of variation CV Conservation agriculture CA XXXVIII

39 Conventional flat CTF Conventional till with and without residue CWR/CNR Conventional tillage CT Conventional tillage with residue burned CTB Conventional tillage with residue incorporated CTS Cropping cycles CC Days after sowing DAS DeciSiemens per metre ds/m Degree celsius C Di-ammonium phosphate DAP Dinitrogen gas N₂ Direct-seeded rice DSR Dry weight DW Dry weight DW Duncan's multiple range test DMRT Eastern Indo-Gangetic Plains EIGP Food and Agriculture Organization of the United Nations FAO Geometric mean diameter GMD Gram g Gram per cubic centimetre g/cm 3 Gram per kilogram g/kg Greater than > Greater than equal Greenhouse gasses GHGs Harvest index HI Hectare ha High Barind Tract HBT High residue retention HR In the strip IS XXXIX

40 Indo-Gangetic Plains IGP International Centre for Agricultural Research in the Dry Areas ICARDA International Maize and Wheat Improvement Center CIMMYT International Rice Research Institute IRRI Kilogram kg Kilogram per hectare kg/ha Least significant difference LSD Less than < Low residue retention LR Mean weight diameter MWD Megagram per hectare per year Mg/ha/yr Megapascal MPa Megaram per hectare Mg/ha Methane CH4 Metre m Mid-season MS Millilitre ml Miligram per kilogram mg/kg Milligram nitrogen per gram mg N/g Milligram per gram mg/g Millimetre mm Million hectares M ha Minimum tillage MT Molar M Nitrate nitrogen NO₃-N Nitrogen N Nitrogen accumulation Nacc Nitrogen storage N storage Nitrogen use efficiency NUE XL

41 Nitrogen-stocks N-stocks Nitrous oxide N₂O Not significant ns No-till flat NTF No-tillage NT Off the strip OS Per cent % Permanent raised beds PRB Phosphorus P Plant population PP Polyvinyl chloride PVC Potassium chloride KCl Potentially mineralizable nitrogen PMN Power tiller operated seeder PTOS Probability P Pulses Research Centre PRC Reduced tillage RT Regression coefficient r² Residue R Revolutions per minute rpm Root dry weight RDW Root length RL Root length density RLD Root volume RV Soil bulk density BD Soil organic carbon SOC Soil organic carbon stocks SOC-stocks Soil organic matter SOM Soil penetration resistance PR XLI

42 Soil total nitrogen TN Soil water content SWC Specific root length SRL Square metre m 2 Standard deviation SD Standard error SE Stemphylium leaf blight SLB Stratification ratio SR Strip tillage ST Sulphur S Tillage T Tonnes per hectare t/ha Total soil nitrogen TN Total soluble nitrogen TSN Transplanted aman rice T. aman rice United States Department of Agriculture USDA United States of America USA Versatile Multi-crop Planter VMP Water soluble carbon WSC Weight per volume W/V Wheat Research Centre WRC Year Yr Years Yrs Zero tillage ZT Zero-till with and without residue ZWR/ZNR XLII

43 List of Botanical Names barley black gram chickpea cotton lentil maize mungbean mustard pigeonpea rice sorghum soybean wheat potato chilli pearl millet jute (Hordeum vulgare L.) (Vigna mungo L. Hepper) (Cicer arietinum L.) (Gossypium hirsutum L.) (Lens culinaris Medikus) (Zea mays L.) (Vigna radiata L. R. Wilczek) (Brassica campestris L.) (Cajanus cajan L.) (Oryza sativa L.) (Sorghum bicolor L. Moench) (Glycine max L. Merr.) (Triticum aestivum L.) (Solanum tuberosum L.) (Capsicum annum L.) (Pennisetum glaucum L.) (Corchorus olitorius L.) XLIII

44 Acknowledgements I thank to the omniscient, omnipotent and omnipresent Almighty Allah, the supreme ruler of the Universe, who enabled me to make my dream a reality, a successful completion of the research and submission of this thesis. It is my profound privilege to express my immense gratitude, sincere appreciation and heartfelt indebtedness to my honorable supervisor who changed my views and uncovered my eyes to see the nature deeply, Professor Richard W Bell, School of Veterinary and Life Sciences, Murdoch University for his constant and intellectual guidance, affectionate feelings, cordial support, constant encouragement, effective suggestions and constructive criticisms from the beginning of my PhD. Without his support, I may not have reached at this point of my career. I am incredibly lucky to have such a great supervisor. I believe everything he taught me will serve in future. I m also very much grateful to my co-supervisor Adjunct Professor Dr Chris Johansen, University of Western Australia, and Consultant in Agricultural Research and Development for all kind of advice toward making a clear story for the discussion, tireless review, critical evaluation and criticisms, scholastic guidance, fruitful discussion and all round help and co-operation for successful completion of this thesis. I am thankful to my in-country co-supervisor Professor M. Jahiruddin, Soil Science Division, Bangladesh Agricultural University, Mymensingh for his continuous encouragement, all kind of advice and affectionate behavior for successful completion of this thesis. I would like to thank Dr Wendy Vance, Research Officer, School of Veterinary and Life Sciences, Murdoch University for her endless co-operation throughout my PhD study. XLIV

45 I am also thankful to Dr Md. Enamul Haque, Adjunct Associate Professor, Murdoch University who look after my experiments in my absence, when I was in Australia. I appreciate his help. I m also very much grateful to the farmers of Alipur and Digram villages for their cooperation and help during my field work. I must also thank to Abdul Kuddus Gazi and Neaz Mehedi Phillips for their support. I would like to thank many peoples of Land management group in Murdoch University I came across; with whom I shared some good facts, feelings and ideas. Among them few names I cannot leave without mentioning: Enamul Kabir, Sarith Hin, Sitaram Panta, Alice, Singaravel, Karthika Krishnasamy, Fariba Mokhtari, Asha Abegunawardana, Khairul Alam, Nurul Hasan Mahmud, Truc, Thin, Dr Qifu Ma, Dr Surrender Mann, Stan. I am grateful to the Australian Centre for International Agricultural Research (ACIAR), Australia for providing financial assistance in the form of International Fellowship and Bangladesh Agricultural Research Institute (BARI) for providing study leave without which it could not have been possible to pursue my PhD at this prestigious Australian University. I would like to thank all of you whom I remember for bringing me a smile on my face at some point of my stay in Australia and Bangladesh. I wish you all the best! Special thanks to Masuka Rahman and Dr Shahidul for their inspiration during my last days in Australia. I am overwhelmed with sincere feelings of indebtedness to my beloved parents for their patience, sacrifice and encouragement throughout my life and my PhD. I m thankful to my beloved brothers and sisters for their abundant love and affection which inspired me to complete this journey. I extremely grateful to my elder brother Dr Md Shafiqul Islam for his affection, guidance, care, mental support and encouragement throughout my life and PhD. XLV

46 Md Rafsan Islam, my son has made a lot of sacrifices since his birth as his father was a PhD student. In my monotonous and painful time, he inspired and powered me by his sweet smiling and talking. Every minute of my hard time I spent with him was precious. A special thanks and appreciation to the world best tea maker, my wife Umme Rubayet Rimi for her endless support and strength she provided me at every step of this journey. Above all, she shouldered all the household responsibilities and kept me free for concentrating on my studies. XLVI

47 Dedicated to the small holder farmers of Bangladesh XLVII

48

49 1 Literature Review 1.1 Introduction Food production for a growing world population, while conserving natural resources, now faces a greater challenge than ever before (Lobell et al., 2008; Foley et al., 2011; Gathala et al., 2011b; Pittelkow et al., 2015a). An example of the challenge is Bangladesh, a densely populated country in South Asia, with a per capita agricultural land allocation of 506 m 2 which continues to decline at the rate of 1 % per year (Quasem, 2011). The government of Bangladesh has been importing large amounts of food every year to meet the domestic demand (Bangladesh Economic Review, 2011). Bangladesh has no alternative but to increase its crop production per unit area to minimize the import costs yet meet the food demand for an increasing population (Bakr et al., 2011). Under such a situation cropping intensity in Bangladesh has been increasing dramatically, it is now over 198 %, to maintain food security on the available amount of agricultural land (Jahiruddin & Satter, 2010). Rice-dryland cropping patterns play the major role in producing food, hence this system is an unavoidable lifeline for about 160 million people in Bangladesh. This system has so far effectively maintained the balance between food production and population growth (Gathala et al., 2011b). However, the current cultivation practice of the rice-based system is input intensive, damages soil health, pollutes environments and is not very profitable for farmers (Gathala et al., 2013). As a consequence, the long-term sustainability of the rice-based system is being hampered by stagnating or declining yield and productivity (Hobbs & Morris, 1996; Sharma, 1997; Bajpai & Tripathi, 2000), degrading soil and water resources (Timsina & Connor, 2001), declining soil organic carbon (SOC) and soil total nitrogen (TN) and delays in sowing (Ladha et al., 2003a). Moreover, the deteriorating soil physical properties and soil fertility have been implicated in the decline in crop yield over the long-term in rice-based systems (Sharma, 1997). As for example, the productivity of rice-wheat system in the Indo-Gangetic Plains (IGP) is stagnating or even declining and thereby the system is threatened also by degradation of the environment, increasing water and labour scarcity, and changes of socio-economic status (Rijsberman, 2006; Erenstein et al., 2007; Gathala et al., 2011b). 1

50 In intensive rice-based systems, rice and non-rice (dryland crop) crops are grown in a sequence with frequent cycling of wetting and drying under anaerobic and aerobic conditions (Zhou et al., 2014). The contrasting environments alter the soil C and N cycles, soil chemical speciation and soil biological properties through the diversity of soil organisms (Zhou et al., 2014) (Figure1.1 ). Figure 1.1. Schematic diagram of rice-dryland ecosystem showing conventional and conservation management. Adapted from Zhou et al. (2014). In intensive rice-based systems, rice is mainly grown in puddled soil with intensive tillage which is followed by residue removal for the cultivation of the succeeding nonrice crop in Bangladesh. The rotation associated with contrasting growing environments and conventional cultivation leads to deterioration of soil chemical and physical properties (Dwivedi et al., 2003; Singh et al., 2005a). Puddling is broadly practiced for lowland rice cultivation for a range of reasons throughout the IGP (Sharma et al., 2005). For example, Humphreys et al. (2005) reported that puddling in the IGP is practiced for rapid rice transplanting through softening the soil, reducing percolation loss of water and nutrients, and controlling weed incidence. However it 2

51 causes aggregate breakdown, macropore destruction and formation of subsurface compaction (Sharma & De Datta, 1986; Sharma et al., 2005), which adversely affects the succeeding dryland crop (Bajpai & Tripathi, 2000; Sharma et al., 2005). Subsurface compaction restricted root growth, water and nutrient uptake, and resulted in lowering yield of the succeeding dryland crop (Bajpai & Tripathi, 2000; Pagliai et al., 2004). However, several researchers have reported that rice transplanting into soil without puddling did not result in a yield penalty (Gathala et al., 2011a; Jat et al., 2013; Haque et al., 2016). Before sowing of arable crops, previously puddled soils take more time to dry and form cracks, and as a consequence form hard and large clods that provide poor seedbed and seed-soil contact upon dry tillage. Hence, extra tillage is required to prepare a suitable seedbed for succeeding dryland crops, which diminishes farm profits (Sharma et al., 1988; Sharma et al., 2005). In addition, simultaneous use of puddling for rice and intensive tillage for dryland arable non-rice crops over a longer period caused the degradation of soil structure and accelerated soil organic matter (SOM) decomposition resulting in a decline in SOC (Dalal & Mayer, 1986b; Six et al., 2004; Shibu et al., 2010) and TN concentrations (Dalal & Mayer, 1986a). In a long-term study on the Loess Plateau in the south-central Shanxi province, China, He et al. (2009) reported that conventional tillage (CT) based on intensive tillage and residue removal or burning reduced soil water content (SWC), macro-porosity, macroaggregates and increased soil bulk density (BD), thereby reducing plant available water and nutrient availability. Moreover, Chivenge et al. (2007) reported that tillage disrupted soil nutrient storage, accelerated SOM mineralization, and losses of SOC and TN from the soil. From a study in semi-arid and tropical India, Manna et al. (2013) found that intensive farm management practices have led to gradual depletion of soil nutrients and exacerbated soil degradation. The alterations in microbial composition, nutrient depletion and structural degradation might have collectively contributed to the decline in crop productivity (Manna et al., 2013). Several previous studies indicate that intensive soil tillage resulted in the degradation of agricultural soils, with decreases in SOC and loss of soil structure, adversely affecting soil functioning and causing a long term threat to future yields (Lal, 1994; Ladha et al., 2003c; Pagliai et al., 2004; D Haene et al., 2008). 3

52 In large parts of the developed and developing world, soil tillage by plough or hoe is the main cause of land degradation which leads to stagnating or even declining production levels and increasing production costs (Garcia-Torres et al., 2003). It also causes water runoff, soil erosion, and increased soil compaction (Garcia-Torres et al., 2003). This further leads to more severe droughts and losses in soil fertility but with less responsiveness to fertilizer. Thus it is clear that increased food production must be accompanied by concerted action to reduce the degradation of agricultural soils in Bangladesh, as is generally the case globally. In rice-based systems, crop residues are the vital source of organic C input that is necessary to maintain or increase SOC concentrations, and improve the soil physical properties and hydrothermal regime (Singh et al., 2005b; Jat et al., 2009). However, crop residues are burnt or removed from the field for livestock feed, bedding, roofing and fencing material in rice-based systems in the IGP (Timsina & Connor, 2001). As a result, there is a rapid decline in SOM due to trivial return of residue inputs (Timsina & Connor, 2001). It has been shown that soils undergoing continuous cropping with removal of crop residues and repeated tillage are declining in SOC (Hossain, 2001), which may cause yield decline (Ladha et al., 2003a). On the other hand, residues left on the topsoil of zero tillage (ZT) act as a barrier to protect the soil from runoff and intercepting rain drops while over time preventing surface soil crust formation (Naresh et al., 2013). In addition, residues with ZT reduce evaporation, and buffer temperature and moisture fluctuations (Blevins & Frye, 1993). The agricultural soils of Bangladesh are now low in organic matter; 60 % of arable soils have fallen below 1.5 % organic matter whereas a productive mineral soil should have at least 2.5 % organic matter (Rijpma & Jahiruddin, 2004). In a soil survey, Karim et al. (2004) showed that the organic matter depletion ranged from 9-62 % in different agroecological zones of Bangladesh during the period 1969 to It is estimated that at least 2 million metric tonnes of nutrients are annually removed from Bangladesh soils. One estimate puts the cost of land degradation as 3 % of crop output or 1 % of crop GDP every year in Bangladesh (Bangladesh Institute of Development Studies, 2004). 4

53 Conservation agriculture (CA) based on minimum tillage, residue retention and crop rotation, compared to the conventional system, has been proposed as a potential approach to alleviate a range of agricultural problems in small holder farming systems in the tropics (Hobbs et al., 2008; Foley et al., 2011). Conservation agriculture aims to maximize crop yields while maintaining ecosystem health, unlike conventional systems that aim to maximize yields with less regard for environmental considerations (Dumanski et al., 2006; Naresh et al., 2016). The impacts of CA have been generally positive in agricultural, environmental, economic and social terms (Garcia-Torres et al., 2003). Conservation agriculture has a wide range of benefits including improvement in soil fertility, carbon sequestration while minimizing greenhouse emissions (Reicosky & Saxton, 2007). Several CA-based experiments have been evaluated as an alternative to conventional practices, and positive benefits in terms of increase yield, productivity, economic return and the efficiency of resources have been reported in rice-based systems in the IGP (Kumar & Ladha, 2011; Gathala et al., 2013; Laik et al., 2014; Alam et al., 2015; Gathala et al., 2015). Figure 1.2 shows the potential benefits of CA at ecosystem level for achieving food security and sustainability (Srinivasarao et al., 2015). 5

54 Figure 1.2. Potential benefits of conservation agriculture at eco-system level. Adapted from Srinivasarao et al. (2015). 1.2 Conventional agriculture: basic concepts Conventional agriculture in South Asia can be generally described as follows Concept of tillage Tillage can be defined as any action involving soil disturbance for the purpose of crop production (Boone, 1988). Generally farmers till their land to invert soil, release nutrients through the oxidation of organic matter, make planting easier and to control weeds, pests and diseases (Hobbs & Govaerts, 2010). It involves soil physical, chemical or biological manipulation to optimize conditions for germination, seedling establishment and crop growth (Lal, 1979; Lal, 1983). The tillage practice was intensified with the advent of mechanical power and tractors. However, later it was clearly shown that rigorous tillage resulted in various negative effects on soil and environment. Tillage pulverizes the surface layer making it more prone to erosion and 6

55 oxidization of SOM. In addition, tractors used for tillage compact the subsoil. The activities of farmer s cultivation techniques are presented in Figure 1.3a-e. Figure 1.3. The activities of farmer s cultivation techniques, a) puddling for rice cultivation, b) conventional cropping based on intensive tillage, c) broadcast seed and fertilizer, d) levelling following tillage and e) crop residue burning, f) residue remove Generally tillage practices are done with an expense of energy, cost, time, water and fuel for tilling land for crop production in Bangladesh (Islam et al., 2012; Gathala et al., 7

56 2013; Kumar et al., 2013). Briefly, the consequences of conventional agriculture are presented below (Figure 1.4). Conventional agriculture practices of rice-based system Cropping systems Tillage Residue management Rice-rice-rice Wheat-fallow-rice Rice-maize-rice Rice-potato-rice Rice-mustard-rice Problems Puddling for rice (wet cultivation) Multiple passes of intensive tillage for 2-3 non-rice crop Planking/Laddering Residue removal Residue burning Limited residue retention Declining soil fertility Crop yield stagnation/depression Depletion of soil SOC and nutrient Deteriorate soil physical properties Decrease turnaround time Pests and diseases outbreaks Increase production cost farm economics Shortage of time, energy,labour, water More times required to dry after rice harvest and form cracks Poor seed bed and seed-soil contact Increase water logging Increase soil compaction Decrease root growth Extra tillage for good seed bed preparation Destruction of soil structure and soil aggregation Decline in SOC and TN Induced drought Increased water, energy and labour requirements Promotes erosion and run-off Increase evaporation Pollutes environment Depletion of soil fertility Reduced soil water content Reduced nutrient availability Losses of SOC and other nutrients Induced drought De-nitrification, volatilization, run-off and leaching loss Low fertilizer use efficiency Low water use efficiency Decreased ground water table Impact Poor agricultural productivity and soil degradation Declining soil fertility Unsustainable ricebased system Figure Problems associated with conventional agriculture systems in rice-based system in Indo-Gangetic Plains. Modified from Devkota (2011). 8

57 1.2.2 Crop residue management options under conventional system Farmers in South Asia can manage crop residue in a number of ways including: removal from the field, burning in situ, composting, or retention for succeeding crops. However, usually little residue is recycled in the field it is normally either harvested for fuel, animal feed, or bedding or burned in the field (Singh et al., 2008). The two common practices of residue management are as follows: Residue burning Crop residues, particularly rice straw, that are not used as animal feed are burnt in the western IGP (Singh et al., 2005b). Residues are burnt due to logistic constraints and lack of proper technologies for in situ recycling of crop residues (Jat et al., 2004). Burning is a low cost method and helps to reduce pest and disease transmission in the straw biomass (Kirkby, 1999). However, residue burning not only leads to the loss of a considerable amount of nutrients and organic matter but also contributes to the global greenhouse gasses (GHGs) through N₂O and CO₂ emissions (Grace et al., 2002; Samra et al., 2003). Residue incorporation Incorporation of crop residues into the soil and allowing them to decompose returns almost all the nutrients in the straw to the soil (Singh et al., 2005b). Traditionally this practice was considered useful in returning organic matter to the soil and protecting the soil from erosion. In tropical soils, incorporated rice residue and continuous flooding has become common through intensification of rice cropping practices (Cassman & Pingali, 1995). 1.3 Concept of conservation agriculture Dumanski et al. (2006) considered that: Conservation agriculture is a holistic idea designed to optimize yields and profits while achieving a balance of agricultural, economic and environmental benefits. It can be defined as a sequence of principles and practices that are promoted in application of modern agricultural technologies to improve production while simultaneously protecting and enhancing the land resources on which production depends. Conservation agriculture, a valid tool for sustainable 9

58 land management, is based on three key principles: minimal soil disturbance, permanent soil cover and crop rotation (Hobbs, 2007b). Although it could fit in all sizes of farm and agro-ecological systems, its adoption is urgently required in degrading environments and the regions of acute labour and energy shortage during the cropping season (Food and Agriculture Organization, 2016b). The details of individual CA-based crop management technologies are described below. 1.4 The key components of Conservation Agriculture Minimum soil disturbance The term conservation tillage can cover several related terms, zero-tillage (ZT), notillage (NT), direct-drilling, strip or zone tillage, minimum-tillage and/or ridge-tillage, and point to the fact that it has a conservation goal. Commonly used terms to describe conservation tillage are elaborated as follows Minimum tillage Minimum tillage (MT) refers to the minimum soil manipulation necessary for seed and fertilizer placement in the soil. A reduction in tractor passes and thus reduction in soil compaction may maintain or improve soil structure and stability, maintain SOM content and increase soil moisture retention, biological properties and buffer soil temperature as well as prevent the establishment of some weeds (NLWRA, 2001). Some examples of minimum tillage are described as follows No-tillage According to Lal (1983), NT systems eliminate all pre-planting mechanical seedbed preparation except for the opening of a narrow (2-3 cm wide) strip or small hole in the ground for seed placement to ensure adequate seed/soil contact. Soane et al. (2012) defined no-till (also known as direct drilling and zero tillage, ZT) as a system in which crops are sown without any prior loosening of the soil by cultivation other than the very shallow disturbance (<5 cm) which may arise by the passage of the drill coulters or narrow tynes and after which usually % of the surface remains covered with plant residues. 10

59 Strip tillage The concept of strip tillage (ST) is described by Lal (1983). The seedbed is divided into a seedling zone and a soil management zone (Figure 1.5). The seedling zone (varied seeding depth and width, 4-5 cm width and 5-7 cm depth) is mechanically tilled to optimize the soil and micro-climate environment for germination and seedling establishment. The inter-row or soil management zone (e.g. 20 cm) is left undisturbed and protected by mulch. Strip tillage can also be achieved by chiselling in the row zone to assist water infiltration and root proliferation. This tillage has the potential of combining the benefits of CT and NT by disturbing the seeding row and leaving the inter-row with complete residue cover (Vyn & Raimbault, 1993). Strip-tillage is a mode of conservation tillage involving seed bed tilled in strips, leaving the no-till zone with at least 30 % crop residue retention (Trevini et al., 2013). According to Food and Agriculture Organization (2016a), provided the disturbed area is less than 15 cm wide or 25 % cropped area, ST qualifies as a form of conservation agriculture. Figure 1.5. A Versatile Multi-crop Planter is using for strip tillage Permanent raised planting Permanent raised bed planting is a form of reduced tillage but there is substantial soil disturbance during formation of new beds. Raised beds are formed by moving soil laterally from the furrows to form a raised bed (Naresh et al., 2014b). There are two parts in a in a bed planting (BP) system - centre of the bed and furrow of the bed (Figure 1.6). The furrows are used for irrigation channels, drains and traffic lanes. Generally, two to six rows are planted on the top of each bed (Naresh et al., 2011). In the permanent raised bed (PRB) technique, once developed, the bed is not destroyed or displaced but is only renovated each season (Gathala et al., 2015). According to Sayre and Moreno (1997), the beds and furrows need to be kept permanently in the 11

60 same position and reshaped as necessary from crop to crop in PRB. Dimensions and configurations of raised beds may vary with soil conditions, field slope, available machinery, crop type and irrigation technique. The PRB is generally constructed with medium soil disturbance and maximum residue retention where equipment wheels and irrigation channels are restricted to permanent furrows and by planting crops on the edges of beds (Govaerts et al., 2007). While it involves reduced tillage, PRB involves more soil disturbance that Figure 1.6. A Versatile Multi-crop Planter is permitted in FAO CA guidelines. The using for reshaping permanent raised bed. PRB has a beneficial effect on soil properties and crop performance globally. As for example, the long-term effects of PRB significantly improved soil chemical and biological properties, compared with conventionally tilled beds in Northwest Mexico (Govaerts et al., 2007). In addition, PRB was effective in improvement of plant-available soil water and aggregate stability compared with CT (Verhulst et al., 2011). Singh et al. (2010) also found that the grain yield increased in PRB as a result of improved soil properties and reduced waterlogging in the Indian Punjab Permanent ground cover: residue management Residue retention is one of the major principles of CA whose goal is maintenance of surface soil cover to protect the soil from sunlight and direct raindrop impacts (Busari et al., 2015). Residue cover also protects the soil surface from wind and water erosion, while retaining C at the soil surface. In South Asia, the amount of residue being returned to the soil is inadequate due to its uses for different purposes (Mohanty et al., 2007). Gangwar et al. (2006) reported that mulch can increase yield, water use efficiency and profitability, while decreasing weed pressure. In order to avoid serious adverse impacts on soil, crop and environment, it remains to be determined where, when, and how much of crop residue can be removed from soil (Wilhelm et al., 2007). 12

61 According to Graham et al. (2007), the threshold levels of crop residue removal must be established based on the amount of residue needed to: (i) conserve soil and water, (ii) maintain or increase crop production, (iii) increase SOM pools, (iv) reduce net GHG emissions, and (v) minimize non-point source pollution. The cutting height at harvest and also the spread pattern of the residues are the main management options at harvest (Anderson, 2009). When deciding on the cutter height of mechanical harvesters it is important to know the height of the lowest obstruction under the seeding bar of the subsequent seed drill. Standing wheat stubble is much easier to seed into than stubble that has been flattened by machinery (Anderson, 2009). With the emergence of a range of planters for 2-WT (e.g. Haque et al. 2011; Haque et al. 2016) there is a need to determine the optimal residue retention for CA in rice-based cropping systems Crop rotation Crop rotation involves growing different crops in planned succession on the same field and it is one of the key pillars of CA. However, selection of appropriate crops and cropping systems is an important factor for maintaining soil fertility, productivity and profitability. As an example, in Bangladesh mungbean is a short duration legume crop which can be grown in early summer (March to May) and could fill the gap in ricebased cropping systems between the winter and rainy season rice crops. Therefore, suitable crop selection in the system is important for a CA system to be successful. The appropriate crop selections in rice-based systems are discussed below: Crop diversification in rice-based systems Rice is the dominant crop and occupies about 81 % of the total cropped area in Bangladesh (Bangladesh Bureau of Statistics, 2010). Further, rice is grown in three distinct seasons, namely aman rice (monsoon rice), aus rice (pre-monsoon rice) and boro rice (dry season rice). As a result, most cropping systems are dominated by rice in Bangladesh. However, repeated growing of monoculture rice for longer periods could face a number of problems, such as decline of soil fertility (Singh & Singh, 1995; Manna et al., 2003; Jat et al., 2012a), deterioration soil physical properties (Sharma et al., 2003), reduction in water table, and pest and disease outbreaks etc, resulting in a 13

62 serious threat to agricultural sustainability (Jat et al., 2012a). In Bangladesh, the dry season rice (boro rice) contributes over 60 % of total rice production (Bangladesh Bureau of Statistics, 2015). As a dry season crop, boro rice is grown under irrigated conditions. Hence, continuously using ground water for boro rice cultivation under ponded condition leads to severe ground water depletion (Karim et al., 2014). Rahman and Mondal (2010) predicted that water availability for the cultivation of boro rice will be drastically reduced in the future due to global climate change and ground water depletion in the High Barind Tract (HBT) of Bangladesh. Also, arsenic (As) contamination of groundwater is widely prevalent in Bangladesh, caused by groundwater depletion (Brammer, 2009). Further, rice is typically established by transplanting seedlings into puddled soil in Bangladesh. This requires a huge amount of water and labour which are becoming increasingly scarce and expensive, making rice production less profitable and unsustainable. In addition, continuous flooded rice cultivation reduces the N availability owing to slow and incomplete decomposition of retained residue (Olk & Cassman, 1995). Under such conditions, inclusion of a dryland crop in a rice-based system could hasten the decomposition of organic matter through providing aerobic soil conditions (Jat et al., 2012a). In addition, higher production cost and lower market value of rice encourages diversification of rice-rice systems with higher valued crops which can provide more income and improved nutrition. Campbell et al. (1990) reported that yield potential can be increased under diversified crop rotations by favorably altering plant diseases, root distribution, weeds, moisture conservation, and nutrient availability. Wheat among other crops can add diversity, requires reduced water, and results in higher profit while sustaining the productivity of the rice-wheat system compared to rice-rice systems (Halvorson et al., 2002). In addition, rice-wheat rotations have been considered as a potential rotation to sequester SOC due to slow decomposition of carbon resulting from anaerobic rice cultivation, and addition of greater carbon input through higher biomass of rice and wheat than other rice-dryland cropping systems (Kukal et al., 2009; Sahrawat, 2012). 14

63 Inclusion of legumes in rice-based systems The rice-wheat rotation is a dominant and desirable cropping system in Northwest Bangladesh for ensuring food security. However, the sustainability of rice-wheat system in the IGP is under threat (Ghosh et al., 2012; Bhatt et al., 2016). Rice and wheat are heavy feeders of nutrients (Chauhan et al., 2012a) and continuous cereal cultivation is leading to the degradation of SOM, soil structure and the depletion of plant nutrients which are also major causes of yield decline in intensive cereal-based cropping systems in South Asia (Ladha et al., 2003a; Mulvaney et al., 2009). In addition, Zhou et al. (2014) reported that rice and wheat rotation using conventional practices is leading to stagnated or reduced yields through the deterioration of soil physical properties and decreased water and fertilizer use efficiencies. Therefore, some form of crop diversification is necessary to sustain the agricultural production system. There is some evidence that inclusion of leguminous crops in a cropping sequence reverses the degradation process, increases yield, and improves soil fertility by fixing of atmospheric nitrogen (N) in their root nodules, which in turn supplies residual N to the succeeding crop (Kumbhar et al., 2007; Ghosh et al., 2012). In addition, legume-based cropping sequences reduce water and nutrient requirement compared to cereal-based systems. Further, legume crops leave more unused SWC in the soil profile which would benefit deep rooting crops grown after the shallow rooting legume crops (Cutforth et al., 2013). Legume-based cropping sequences can accumulate SOC, increase soil N content, and improve soil aggregation which can be attributed to symbiotic fixation of N, return of leaf litter and N-rich roots to the soil (Bhattacharyya et al., 2009b; Ghosh et al., 2012) which leads to residual benefits for the following crop. Kumar Rao et al. (1998) reported that a grain legume can supply kg N/ha to the succeeding crop. In addition, the potential NO₃-N losses can be minimized by growing legumes crops during the dry-wet transition periods after monsoon rice. Sarker (2005) found that incorporation of mungbean residue was effective in increasing the growth and yield of succeeding monsoon rice. Further, inclusion of mungbean in the rotation could increase system productivity and economic returns (Gathala et al., 2013). In addition, increased grain legume cultivation is critical for providing essential protein, minerals and vitamins to humans and livestock (Lauren et al., 2001). Therefore, it is necessary to 15

64 further examine prospects for legume-based rotations under CA as information on legumes in rice-based cropping systems in Bangladesh is relatively limited. 1.5 Development of conservation agriculture Soil tillage in fragile ecosystems was questioned in the 1930s, when dustbowls devastated wide areas of the mid-west of the United States of America (Friedrich et al., 2009). It was observed that water and wind-driven soil erosion were greatly diminished by conservation tillage (Cline & Hendershot). Therefore, the concept of conservation tillage was introduced for protecting the soil by reduced tillage (RT) and residue retention. In the 1940s, advances in machinery design to seed directly without any tillage and CA principles were described by Edward Faulkner in his book Ploughman s Folly (Faulkner, 1945). But the practical application of conservationtillage did not occur until the 1960s. In the 1970s, farmers and scientists transformed the CA technology in Brazil, and at the same time research on NT with mulching was started in West Africa (Lal, 1976). The concept of MT was promoted by increasing concerns about soil erosion aggravated by intensive tillage (Thomas et al., 2007b). Later the development of inexpensive weed control with herbicides accelerated the spread of conservation tillage (Blevins & Frye, 1993). With the beginning of widespread use of herbicides, tillage practices were supposed to be unnecessary, at least for weed management. Experiments with MT started in North America and UK with the availability of herbicides and then it spread to commercial farming in South America and Australia (Johansen et al., 2012). For the implementation of MT, it became necessary to develop a planter that can effectively deliver seed and fertilizer into undisturbed soils. The other two pillars of CA, permanent soil cover and diverse crop rotation became viable with the development of herbicides and minimum tillage planters. During the 1970s, increased fuel prices encouraged farmers to change to CA farming and hence commercial farmers widely adopted CA for saving fuel and to protect the soil from erosion (Haggblade & Tembo, 2003). In Brazil and West Africa, NT direct seeding and mulching appeared during the early 1970s (Lal, 1976). But it took over 20 years to reach a significant adoption in South America (Haggblade & Tembo, 2003). In Zimbabwe, about 30 % of the commercial farmers using high-power traction had adopted CA by 1998 (Nyagumbo, 1998). As the high-power traction was not 16

65 available for the small holder farmers, it was necessary to develop alternative machinery to fit into small farms. In Bangladesh, the International Maize and Wheat Improvement Center (CIMMYT) introduced a power tiller operated seeder (PTOS) from China for timely sowing of wheat compared to sowing under CT by animal draught power after monsoon rice in 1995 (Roy et al., 2004). In , two-wheel tractor (2- WT) operated no-till seeders were introduced with the collaboration of Food and Agriculture Organization (FAO), CIMMYT and Bangladesh Agricultural Research Institute (BARI) (Hossain et al., 2015a). Later, an Australian Centre for International Agricultural Research (ACIAR)-funded project improved the 2-WT operated no-till seeder for planting seeds of a range of crops and to manage residue properly (Hossain et al., 2009). Currently, around 450,000 to 700,000 2-WT are used by small holders accounting for 85 % of primary tillage in Bangladesh (Krupnik et al., 2013; Hossain et al., 2015a). However, even though a range of planters for minimum soil disturbance planting have been developed in recent years, there is still limited adoption of CA by smallholders in rice-based cropping in Bangladesh or the Eastern Indo-Gangetic Plains (Johansen et al., 2012). In part, this can be attributed to the limited number of medium to long term studies on CA in farmers fields to demonstrate its performance in ricebased cropping systems, using machinery suitable for small farms or fields. 1.6 Conservation agriculture adoption worldwide Farmers commitment and mutual support of all linked stakeholders are required for the rapid adoption and spread of CA (Kassam et al., 2014). Over the last three decades, CA has been practiced continuously and has spread widely (Kassam et al., 2009). The adoption of CA for arable cropping systems by region is given in Table 1.1. The different components of CA are now being practiced from the Arctic Circle (e.g., Finland) across the tropics (e.g., Kenya, Uganda), to about 50 latitude south (e.g., Malvinas/Falkland Islands) (Derpsch et al., 2010). Conservation agriculture is practiced on all kinds of farm sizes from a half hectare (e.g. China, Zambia) to hundreds of hectares in many countries of the world, and to thousands of hectares in countries like Australia, Brazil, USA or Kazakhstan (Kassam et al., 2009). 17

66 Figure 1.7. Extent of global area of conservation agriculture over time (Source: above the respective bar). Although currently there has been continued and rapid spread of CA systems across the world, the total area of CA at present is only 9 % (about 125 M ha) of the total cropped area (Friedrich et al., 2012). The current database of an ongoing collaboration between FAO s Conservation Agriculture and AQUASTAT programmes in 2016 shows that globally the spread of CA is about 156 M ha while in 1973/74 it was only on 2.8 M ha (Figure 1.7). The area of CA in the world is currently spreading at a rate of 10 M ha per year and rapid expansion is mainly on large farmers land (Kassam et al., 2014). However, adoption has been limited in small holder farms and in intensive rice-based cropping systems (Food and Agriculture Organization, 2013a). There are several constraints that impede widespread uptake of CA in small holder farms, such as lack of extension programs, traditional mindset, lack of technical knowledge, weak institutional support, unavailable affordable CA equipment and machinery and lack of suitable herbicide (Friedrich et al., 2012). 18

67 Table 1.1. Area of arable crop land under conservation agriculture by region in Region Area (M ha) Percent of global total Percent of arable land South America North America Australia and New Zealand Asia Russia and Ukraine Europe Africa Global total Adapted from Kassam et al. (2014). 1.7 Constraints of conservation agriculture Although CA has many beneficial effects on soil, environment and crop there are also constraints to adoption of CA practices. Due to resource constraints and trade-offs with other farm activities, especially with regard to the availability of crop residues, seeds, land, labor, cash or credit it has been reported that small holder farmers rarely adopt all three CA principles together (Wall, 2007; Kassam et al., 2009). Moreover, Giller et al. (2009) identified some important constraints such as limited mechanization within the small holder system, lack of suitable implements, lack of proper fertility management options, weed control problems, limited access to credit, lack of appropriate technical information, blanket recommendations that ignore the resource status of rural households, competition for crop residues in mixed crop-livestock systems, and limited availability of household labour. Some other constraints are summarized in Table

68 Table 1.2. Summary of major constraints of conservation agriculture systems. Constraint Major finding References Risk of lower crop yields Slow adoption and extent Weeds and herbicides New machinery and operating skills required Other uses of crop residue Nutrient immobilization Without concurrent implementation of residue retention and crop rotation, NT alone tends to cause yield losses Grain yields of wheat reduced under ZT during the initial years of CA adoption During the first few years lower yields under NT compared to ploughing. Adverse effects of waterlogging in CA decreased grain yield of maize Capital- and labour-constrained small holder farmers often reluctant to adopt CA because of concerns such as risk of yield loss, increased labour demand if herbicides unavailable, unavailable crop residue due to use for household purposes, lack of knowledge and skills on CA Increased recruitment of small-seeded weeds in minimum and NT systems. Herbicides are relied on as the main means of weed control in conservation tillage systems Pittelkow et al. (2015a) Govaerts et al. (2005) Guto et al. (2012) Thierfelder and Wall (2010) Giller et al. (2009) Chauhan et al. (2006a) Anderson (2009) Greater dependence on herbicides Lafond et al. (2009) During initial years of CA adoption, weed control is often laborious and more costly with a greater requirement for herbicides High costs to import herbicide during initial 4-5 years causes reluctance to adopt CA in many developing countries Constant use of herbicide in conservation tillage systems resulted in the development of herbicide resistance; and heavy use may badly affect succeeding crops and the chemical runoff can lead to water pollution Heavy and continuous use of herbicides may adversely affect the environment Continuous use of herbicide reduces its efficacy Wall (2007) Machado and Silva (2001) D'Emden and Llewellyn (2006); and Hinkle (1983) Hinkle (1983) Chauhan et al. (2006b) May require additional machinery Hulugalle and Scott (2008) Specialized equipment is important for successful adoption of CA Hobbs et al. (2008) CA is a knowledge intensive process Umar et al. (2011) Use of crop residue for different purposes such as livestock feeding, fuel and burning are the major constraints for the adoption of CA High amounts of cereal residues with a high C:N ratio causes temporary immobilization of soil mineral N Bhan and Behera (2014) Abiven and Recous (2007) 20

69 Constraint Major finding References Carryover of insect pests and diseases Greater immobilization occurs under ZT with residue retention 30 % higher pesticides required in conservation tillage over CT to protect from enhanced insect, pests and diseases Rice cultivation under CA was more affected by Laodelphax striatellus because it was difficult to apply insecticide or herbicides under the layer of straw and stubble in CA systems Bradford and Peterson (2000) Hinkle (1983) Mousques and Friedrich (2007) 1.8 Effect of conservation agriculture on crop performance and system productivity In the IGP, there are numerous constraints to crop production in rice-based systems. Since this thesis deals with the development of CA for two intensive rice-based rotations in the Eastern IGP Bangladesh, some of the major constraints and their possibilities for alleviation are summarized in Table

70 Table 1.3. Constraints to cropping systems in the Indo-Gangetic Plains. Constraint Unsustainable production system Decreasing crop productivity Lower system productivity Soil organic carbon depletion Cropping system Rice-wheat Ricewheat; Cottonwheat Rice-wheat Rice-wheat Rice-wheat Cause Consequence Solution Reference Low yield and Plateauing and Adaptation of (Bhushan et al., 2007; farm income; reducing CA based Hobbs, 2007a; Kumar & environmental agronomic systems Ladha, 2011; Raman et constraints and productivity al., 2011; Gathala et al., weather and 2013; Jat et al., 2014; variability profitability Laik et al., 2014) Degradation of Decline in crop Application of (Mishra et al., 2015) soil physical productivity CA-based properties management system - minimum or ZT and crop residue retention Puddling use for Deterioration Direct seeded (Kukal & Aggarwal, rice cultivation of soil unpuddled 2003a; Mohanty et al., structure, rice, 2006) failure of permanent seedling raised bed emergence and yield loss of next crop after rice Intensive tillage Reduces Residue (Ghimire et al., 2011) and removal of productivity retention and crop residue and causes ZT system environmental degradation Reduces Integrated (Yadav et al., 2000; sustainability nutrient Nayak et al., 2012) management Adverse ZT and residue (Bhattacharyya et al., environmental retention 2006b; Bhattacharyya impacts and et al., 2012b; Das et al., unsustainable 2013; Das et al., 2014) productivity 22

71 Constraint Total Soil N depletion Cropping system Cottonwheat Cause Consequence Solution Reference Intensive tillage Unsustainable ZT under BP (Bhattacharyya et al., and removal of and lower crop system and 2013) crop residue productivity residue retention In the IGP, the productivity of rice-based systems has plateaued or started diminishing due to mismanagement of natural resources (Ladha et al., 2003c). Traditional crop establishment methods in rice-based systems such as puddling for transplanted rice and intensive tillage for wheat planting require large amounts of water, energy and labour, which are becoming increasingly scarce and expensive (Mishra & Singh, 2012). Moreover, conventional agronomic practices are no longer able to maintain the gains in productivity during the past few decades (Chauhan et al., 2012a). Conservation agriculture as a paradigm shift is proposed for enhancing the system's productivity and sustainability in South Asia (Jat et al., 2011). Laik et al. (2014) concluded that CA comprising ZT with full residue retention enhanced the productivity and economic returns over farmers practices involving intensive tillage for wheat cultivation, and puddling for rice cultivation with residue removal. Kumar et al. (2013) demonstrated from five wheat establishment methods (CT, reduced-tillage, rotovator tillage, raised bed and zero-tillage) that ZT improved the operational field capacity of machinery by 81 %, and decreased specific energy (energy required to produce per kg of grain) by 17 % and increased the energy usage efficiency by 13 % compared to CT in a Typic Ustochrept alluvial sandy loam soil in the IGP. Erenstein and Laxmi (2008) concluded from a comprehensive review of ZT impacts on wheat in the Indian IGP that ZT wheat is suitable for rice-wheat systems in the IGP by allowing earlier wheat planting, facilitating weed control, reducing production costs and saving water. A different study of rice-wheat systems in the IGP showed that the resource conserving CA technologies saved water consumption and negative environmental impacts and increased crop production (Gupta & Seth, 2007). A survey in the IGP showed that even resource-poor small holders have started to benefit from this technology by using contractors to direct-drill their crops (Hobbs & Gupta, 2002). Hobbs and Gupta (2003) also showed that wheat yields were greater when it was planted with ZT after unpuddled rice. In 23

72 another 2-year study, yield of dry direct-seeding rice and wheat under NT performed the same as with conventional practice, but under NT conditions the water savings and labor use were significant (Bhushan et al., 2007). Wang et al. (2012) reported that yields with RT were higher by % in spring maize and 9-37 % in winter wheat, whereas those with NT were comparable to conventional methods in China. Balwinder et al. (2011) reported that mulch residue improved crop performance when water was limiting, and occasionally increased yield. Some other researchers have demonstrated that NT and residue mulching is effective in increasing crop yields (Naudin et al., 2010). However, Zheng et al. (2014) showed from a metaanalysis in China that NT without straw retention increased the risk of yield loss, although CA effects on crop yield differ due to the variation of regional, climate and crop types. Although some studies demonstrated no advantage of PRB, there is increasing evidence that this procedure is advantageous to system productivity. Permanent raised beds are increasingly used in many developed and developing countries and have been introduced in Bangladesh with the aim of improving system productivity (Talukder et al., 2002). Singh et al. (2010) studied the effects of PRB on soil fertility, yield, and water and nutrient use efficiencies in a pigeon pea wheat system in India. They concluded that PRB produced greater yield of pigeonpea and higher system productivity but lower wheat yield as compared to conventional flat bed. Hossain et al. (2008) evaluated system productivity, fertility and N-use efficiency under N fertilization, straw retention and tillage options in a rice-wheat-mungbean cropping system. They concluded that PRB with straw retention produced the highest productivity for all three crops in the sequence. Within each N rate the total system productivity was the greatest with residue on PRB and least in conventional traditional planting with no straw retention. Wheat performed better with BP in terms of spike number, spike length, grain yield as well as N absorption and also this planting method reduced the level of plant lodging even when N application was high (Hossain et al., 2006). Therefore, the combination of PRB with N and residues retained appears to be a very promising technology for sustainable intensification of rice-wheat systems in 24

73 Bangladesh. Khaleque et al. (2008) demonstrated from an experiment of BP and N application on wheat yield and N-use efficiency that plants take up more N and thereby increased wheat yield in newly formed BP compared to the conventional planting system. Talukder et al. (2004) reported from a three-year study of the ricewheat-maize+mungbean cropping system in Bangladesh that 50 % previous crop residue increased maize yield by 31.6 % and rice yield by 19.3 %. Moreover, in a different study of the rice-wheat system in Bangladesh, Hossain et al. (2008) concluded that wheat root length density and root diameter were increased with raised beds, straw mulch and N application. In a rice-wheat system at Jabalpur, Madhya Pradesh, India Gathala et al. (2015) evaluated four tillage methods (direct seeding in dry fields, direct seeding of sprouted seeds in a puddled field by drum seeder, manual transplanting, and mechanical transplanting) for rice and four tillage methods (CT, ZT, ST and BP) for wheat. They found that direct seeding of sprouted seeds of rice following ST of wheat resulted in higher yield and water productivity by ensuring timely and low-cost sowing. However, Islam et al. (2014) did not find from their three years experiment on the rice-maize rotation in Bangladesh significant yield differences due to different tillage (CT, single pass wet tillage in rice, BP and ST) and residue retention (0, 50 and 100 %). In a 4-year study of rice-maize rotations in Bangladesh, Gathala et al. (2015) evaluated CA-based tillage (RT, ST, fresh beds and permanent beds) productivity and profitability relative to current practice CT (puddled) transplanted rice on flat followed by conventional-tilled maize on flat. They concluded that although there was no yield difference due to different CA-based tillage options, PRB and ST resulted in higher net income and benefit cost ratio compared to CT for both rice and maize. 1.9 Influence of conservation agriculture on soil properties Soil physical properties The contrasting soil environment and management condition in rice-based cropping systems exacerbates soil physical problems, particularly for the non-rice crop. Therefore, it is of particular interest to evaluate the extent to which CA can alleviate soil physical constraints in rice-based systems. 25

74 Soil structure and aggregation Soil aggregate stability is one of the key indicators for soil quality in agro-ecosystems (Paul et al., 2013). Soil structural stability is the ability of aggregates to remain intact when exposed to different stresses (Kay et al., 1988). In general, CT reduces soil aggregation and particulate organic matter by accelerating the turnover of aggregateassociated SOM (Six et al., 1999). In maize-wheat cropping systems on a Cumulic Phaeozem soil of Central Mexico, ZT with residue retention increased aggregate distribution and stability compared to CT and thereby reduced top layer slaking (Govaerts et al., 2009). More stable soil aggregate structure is present under ZT, compared to CT (Limon-Ortega et al., 2002). Govaerts et al. (2007) found higher aggregate stability and mean weight diameter (MWD) in PRB with full residue retention compared to residue removal in Mexico. Shaver et al. (2003) reported that macro-aggregation has a linear relationship with the C content of the aggregates whereby each extra g of organic C/kg in the macro-aggregates increased the macroaggregates by 4.4 %. From an 11-year long-term experiment of the Chinese Loess Plateau, He et al. (2011) found that macro-aggregates (>0.25 mm) and macroporosity (>60 µm) with NT increased by 8.1 % and 43.3 % compared to CT in the 0-30 cm soil layer. Also Chen et al. (2009a) reported that the portion of mm aggregates, MWD and geometric mean diameter (GMD) of aggregates under conservation tillage were larger than CT at both 0-15 cm and cm soil depths in the rainfed areas of northern China. Residue retention with low quality SOM can increase soil aggregate stability more than high quality organic resources but N fertilizer application negates these effects (Chivenge et al., 2011) Soil bulk density and porosity The soil bulk density (BD) varies with crop management as well as with inherent soil qualities (Singh & Kaur, 2012). From a 22-year long-term field trial in Central Ohio it was found that soil BD and penetration resistance were lower under no-till than ploughed soil. Machado and Silva (2001) reported that the soil BD of soils tended to be lower with soybean-wheat/ hairy vetch-maize under NT than with CT. Gill and Aulakh (1990) also reported that soil BD decreased and grain yield of wheat increased under NT compared to CT. By contrast, soil BD decreased significantly with CT compared to 26

75 ZT after both rice and wheat crops at 0-15 and cm soil depths in a rice-wheat cropping system in India (Bhattacharyya et al., 2006b). Similarly, Gangwar et al. (2006) also found that soil BD decreased significantly with CT compared to ZT in a sandy loam soil of the IGP. However, in a drought prone area of Northwest Bangladesh, soil BD at cm and cm depth did not significantly change due to application of either minimum tillage or CT practices (Islam et al., 2012). Retention of previous crop residue usually significantly decreases soil BD (Blanco- Canqui & Lal, 2009). Addition of each tonne crop residue per hectare over a 12-year period reduced soil BD by 0.01 g/cm³ and increased effective porosity by 0.3 % in the surface 2.5 cm soil depth in wheat-fallow, wheat-corn-fallow and continuous cropping (Shaver et al., 2003). Application of mulch of fodder radish decreased the soil BD and increased transmission pores in the 0-10 cm soil layer (Glab & Kulig, 2008). Besides, the method of residue retention also significantly influences the soil BD. Soil BD was lower when crop residue was incorporated compared to when it was retained on the soil surface as mulch (Acharya et al., 1998). Bhattacharyya et al. (2006a) reported that soil BD was significantly lower in a CT system compared to ZT due to the incorporation of crop residues in surface soil of CT in the Indian Himalayas. They also demonstrated that the BD was significantly lower with soybean-pea and soybean-lentil rotations than a soybean-wheat rotation at this location Soil penetration resistance Soil penetration resistance (PR) is a commonly used indicator of soil strength and soil compaction. High PR is correlated with poor aeration, poor drainage and restricted root growth (Celik, 2011). Tillage and residue management influences soil PR as a result of altering the soil structure and hence soil pore size distribution. In tillage studies, soil BD and PR are two interrelated variables to assess the soil pore size distribution but individual use of PR or BD may give misleading information (Campbell & Henshall, 1991). The relation between soil PR and soil BD is positive and in compact soil, soil PR strongly increases while increases in soil BD are small (Allbrook, 1986). In a study on sandy soil it was shown that wheel traffic increased soil PR about 35 % while BD increased less than 3 %; that is, soil PR was ten times more sensitive than BD as an 27

76 indicator of soil compaction (Vazquez et al., 1991). For showing tillage effects, Ferreras et al. (2000) found greater PR in the upper 10 cm soil under NT than CT. Also, Franzen et al. (1994) observed significantly lower soil PR with NT below 10 cm soil depth due to addition of mulch. It was also shown in other studies that soil PR was significantly higher with CT compared to ZT (Carman, 1997). Schwartz et al. (2003) found that the PR increased with NT practices as compared to CT and RT. Limon-Ortega et al. (2002) found that PR decreased as the amount of crop residues applied for each tillage-straw treatment increased in Northwest Mexico. Increasing crop residues can increase SOM content and thereby improve SWC which in turn lowers soil PR (Shaver et al., 2003). Complete stover removal increased soil PR in a sloping silt loam from 0.9 to 1.2 MPa and in a nearly level silt loam from 0.8 to 1.1 MPa (Blanco-Canqui & Lal, 2007) Soil water content Soil moisture conservation is a critical issue for crop production in most rainfed cropping areas around the world. It is widely recognized that puddling of soil during rice cultivation degrades the soil physical conditions and results in lower yields of dryland crops in rice-based systems (McDonald et al., 2006). After rice, the surface soil should be sufficiently dry to allow entry of machinery for establishing the dryland crop. Puddled soil, however, may require several days following rice harvest to reach an appropriate moisture content for tillage (Flinn & Khokhar, 1989). Several studies in the IGP have demonstrated yield reductions (1-1.5 %) of wheat for every day delay in planting after the optimum sowing date (Hobbs & Morris, 1996). Further, when soil moisture level permits initiation of tillage, primary tillage produces massive structure and clods in previously puddled soil, and hence extra tillage is needed to prepare a fine seed bed (Timsina & Connor, 2001). Intensive tillage can disrupt soil pores and thereby decrease water infiltration (Shukla et al., 2003). In contrast, the positive influence of ZT on soil structure, pore geometry may increase SWC and its transmission (Azooz et al., 1996). Conservation agriculture practices such as ZT and residue retention are important tools for conserving soil and water resources (Reeves, 1994). In northeast China, Liu et al. (2013) reported that SWC under NT was higher than in CT at 0-30 cm soil depth. In another study of North Cameroon, NT or RT improved SWC and corn yield compared to CT (Naudin et al., 2010). Pagliai et al. (2004) found that lower SWC 28

77 under CT soil reduced root growth of a wheat crop following rice. The SWC is also sensitive to crop residue removal and after removal the exposed soils quickly lose moisture (Blanco-Canqui & Lal, 2009). Mulch cover explained 84 % of variations in SWC under NT in a silty clay loam soil (Wilhelm et al., 1986). Crop residue retention improves SWC in three different ways: 1) increasing infiltration rate and decreasing runoff losses, 2) reducing evaporation and abrupt fluctuations in soil surface temperature, and 3) increasing SOM concentrations, which increases water retention capacity of the soil (Blanco-Canqui & Lal, 2009) Effects of conservation agriculture on soil organic carbon and its fractions Soil organic carbon Soil organic matter and carbonate minerals are the sources of SOC. The SOM is formed by various organic compounds which are processed by living and non-living organisms (Franzluebbers, 2010). The SOC is the main component and makes up a significant portion (50-58 %) of SOM (Franzluebbers, 2010). The SOC is a quantifiable component and different to SOM as it refers only to the C content of organic compounds. Generally, laboratories measure SOC and convert to SOM by a conversion factor of 1.72, i.e. SOM (%) = SOC (%) X Soil organic carbon is a key indicator of soil quality and sustainability as it is inextricably linked to physical, chemical, and biological soil quality indicators (Reeves, 1997). Therefore, maintenance of SOC is essential for sustainable agro-ecosystems. However, SOC is greatly influenced by different tillage and residue management practices. In rice-based systems, crop residues are the main source of organic C which improves soil physical properties and the hydrothermal regime (Yadvinder-Singh et al., 2005). In rice-based systems of the IGP, the conventional production practices involving intensive tillage along with removal of almost all crop residue resulted in loss of SOC and other nutrients (Beri et al., 2003). Dolan et al. (2006) studied the effects of tillage, residue and N management on SOC and N in a Minnesota soil and concluded that 30 % more SOC was obtained with NT than mouldboard plough and chisel plough tillage in the surface soil (0-20 cm). This trend was reversed at cm soil depths, where significantly greater SOC and total N were found in ploughed treatments than in NT, possibly due to residues buried by 29

78 inversion. Similarly, other researchers reported that tillage practice can influence the distribution of SOC in the soil profile with higher SOC content in surface soil with ZT than with CT, but a higher content of SOC in the deeper soil layers of tilled plots where residue is incorporated through tillage (Gal et al., 2007; Thomas et al., 2007a). In an Oxic Paleustalf at Wagga Wagga, New South Wales, SOC levels were significantly higher at 0-20 cm soil depth with direct drilling compared to CT (Chan et al., 2002). Also, Castellanos-Navarrete et al. (2012) reported that crop residue retention along with ZT and crop rotation increased SOC concentrations only at 0-5 cm soil depth compared to CT. Soils under RT increased SOC by 7.3 % compared to plough-till at 0-20 cm soil depth (Chen et al., 2009b) Soil organic carbon turnover Labile SOC fractions in the soil surface layers are sensitive to effects of CA (Li et al., 2012). Dou et al. (2008) found SOC and the labile SOC pools significantly increased under NT and intensified cropping at 0-5 cm depth while they decreased with CT with the effects gradually decreasing with depth. In the rainfed areas of northern China, Chen et al. (2009a) found that SOC fractions such as particulate organic C, permanganate oxidizable C, hot-water extractable C, microbial biomass C and dissolved organic C were all significantly higher in NT and ST than in CT in the upper 15 cm Water soluble carbon The water soluble carbon (WSC) is a small portion (<5 %) of the total SOC content (Tao & Lin, 2000; Ohno et al., 2007; Scaglia & Adani, 2009). However, it plays an important role in many biogeochemical processes of soil and is considered as the most mobile and reactive soil carbon source (Lu et al., 2011), altering a number of physical, chemical and biological processes in both aquatic and terrestrial environments (Schnabel et al., 2002; Marschner & Kalbitz, 2003). Water soluble carbon is one of the sensitive early indicators of effects of soil management practices on soil quality (Blair et al., 1995). In a study of northern China, Liu et al. (2014b) obtained 232 % higher WSC at 0-5 cm and 123 % greater at 5-10 cm soil depth under NT as compared to CT after 17 years. However, treatments were not significantly different below 10 cm soil 30

79 depth. Li et al. (2012) found that WSC under double NT (rice with NT-rape with NT) plus crop residue treatment were times higher than with residue removal and CT in a 3-year experiment of rice-rape rotation in central China Carbon dioxide (mineralization, root and microbial respiration) It is well known that tillage exposes the protected SOM and stimulates CO₂ efflux from soil (Reicosky et al., 1997; Rochette & Angers, 1999). Conventional tillage improves soil aeration along with incorporating soil residue and hastens SOC oxidation which leads to increased CO₂ emissions (Himes, 1998; West & Post, 2002). By contrast, minimum tillage and crop residue retention can reduce CO₂ emissions from the soil surface, resulting in increased C sequestration in the soil compared to intensive tillage and residue removal (Reicosky, 2001). From research on a calcareous Hypogleyic Luvisol, Buragiene et al. (2011) showed that the emission of CO₂ was greater after intensive ploughing and lowest in NT soils. Almaraz et al. (2009) examined tillage (CT and NT) and N₂-fixing soybean (Glycine max) residue effects on greenhouse gas (CO₂ and N₂O) emissions and concluded that CT with incorporation of soybean residue induced greater CO₂ emission than the NT system. The conventional rice-wheat rotation is a considerable source of GHG emissions as puddled rice contributes to methane (CH₄) emissions and dryland crop (wheat) production contributes to N₂O and CO₂ emissions (Pathak et al., 2011). On the other hand, paddy soils have potential for increased SOC storage as compared to dryland soils with proper soil management (Xu et al., 2013). Emission of CO₂ from soil can be mitigated by sequestration of SOC (Lal, 2004b; Das et al., 2013). Thus, SOC sequestration is an effective strategy for restoring the degraded soils, enhancing soil fertility and reducing the atmospheric CO₂ emission and thereby mitigating climate change (Wang et al., 2010). Adopting CA has been recognized as an important strategy to reduce greenhouse gasses through sequestering SOC, as well as through minimizing use of fuel and fertilizer (Pathak et al., 2012; Dendooven et al., 2012a; Alam et al., 2016). 31

80 1.9.3 Effects of conservation agriculture on soil nitrogen dynamics Nitrogen is the most important yield limiting nutrient in intensive irrigated ricesystems (De Datta et al., 1998; Ali et al., 2007a; Devkota et al., 2013). In most ecosystems, N regulates net plant primary production (Lambers et al., 1998). Nitrogen undergoes various transformation processes (Figure 1.8). There are three major pathways of N loss, firstly leaching (mainly NO₃-N and intermittently NH₄-N and soluble organic N), secondly by de-nitrification (emission of N₂O, NO and N₂ gases) and thirdly ammonia (NH₃-N) volatilization (Ladha et al., 2005). The resultant leachate and gases go to water bodies and the atmosphere and can pollute the environment (Ladha et al., 2005). Consequently, N management plays a vital role in improving crop yield and quality, environmental quality, and economics of crop production (Campbell et al., 1995). A mechanistic knowledge of the soil N cycle is critical in understanding the behaviour of ecosystems and their responses to natural and anthropogenic mediated change (Jones et al., 2004). Figure 1.8. The soil nitrogen cycle. Adapted from Hofman and Cleemput (2004). Nitrogen dynamics in intensive rice-dryland crop rotations (anaerobic-anaerobic) can be greatly altered by changing the crop establishment method from a conventional to a CA system (Devkota et al., 2013). Nitrogen dynamics under conventional cultivation techniques in lowland paddy soil have been extensively studied (Buresh & De Datta, 1991; Tripathi et al., 1997; Ali et al., 2007a). However, there are limited studies 32

81 available that report changes for CA cultivation of different crops especially for dryland in intensive rice-based system in Bangladesh Total soil nitrogen Conservation agriculture effects on soil TN content generally mirror those on total SOC as the N cycle is inextricably linked to the C cycle (Bradford & Peterson, 2000). Nitrogen dynamics can also be affected by a change from conventional ploughing to conservation tillage (Van den Putte et al., 2012). A significantly higher TN was observed both under ZT and PRB compared to CT in the highlands of Central Mexico (Govaerts et al., 2007). Sainju et al. (2007) reported that improving soil and crop management practices such as RT and increased cropping intensity increase soil TN and its fractions to a depth of 20 cm compared to conventional practice in dryland conditions. Residue retention improved SOC, TN and other essential nutrients, and increased thereby crop yields compared to residue removal (Das et al., 2013; Bhattacharyya, 2013; Das et al., 2014). On the other hand, Sainju et al. (2008) found from a 10-year experiment in USA that there were no effects of tillage and cropping system on SOC and soil TN. Tillage may affect surface residue and N fractions, e.g. the surface residue, NH₄-N and NO₃-N at 5-10 and cm, TN and PMN at 0-5 cm were greater in ST compared to CT (Sainju et al., 2013). There are several labile active fractions of N described below which may be more responsive early indicators for change in soil N turnover under minimum tillage than total N Mineral nitrogen The organic forms of N are generally not important for growth of crops. The organically bound N is generally only available for crop or microbial growth through N mineralization during the decomposition of crop residues (Lupwayi et al., 2006; Van Den Bossche et al., 2009). In a rice-based system, NH₄-N is the major available form of N for rice in anaerobic soils (Tripathi et al., 1997; Devkota et al., 2013). The accumulated NH₄-N during the rice season undergoes nitrification to NO₃-N which is facilitated by dry conditions and intensive cultivation for growing arable crops after rice (Tripathi et al., 1997). However, this NO₃-N is prone to losses through leaching or 33

82 de-nitrification to N₂ and N₂O upon soil flooding and heavy rains (George et al., 1993; Tripathi et al., 1997). Changes in cultivation techniques, i.e. from conventional to conservation systems, may alter N transformation in intensive rice-based system (Arora et al., 2010; Devkota et al., 2013). Conservation systems largely influence the soil physical environment such as soil temperature, water filled pore space and soil strength which in turn affects the N transformation processes (Linn & Doran, 1984; Devkota et al., 2013). Conservation systems such as ZT and residue retention reduce N mineralization through decreasing the decomposition of SOM and increase the immobilization of N (Drinkwater et al., 2000; Yadvinder-Singh et al., 2005). In contrast, CT based on intensive tillage hastens N mineralization of soil organic N and increases NO₃-N in the soil profile (Sainju & Singh, 2001; Al-Kaisi & Licht, 2004). The impact of minimum tillage and residue retention on N mineralization is still inconclusive (Verhulst et al., 2010). The N availability for plant uptake is dependent on the rate of C mineralization. Intensive tillage increases the mineralization of soil TN (Schomberg & Jones, 1999). By contrast, Schoenau and Campbell (1996) reported that CA enhanced greater initial immobilization which led to greater initial N fertilizer requirements but requirements decreased over time because of the build-up a larger pool of readily mineralizable organic N. Deep placement of N under NT increased N use efficiency in rice and wheat (Ladha et al., 2003b). Rao and Dao (1996) reported that the yield and NUE in wheat increased under ZT condition due to increased availability of applied N and reduced loss. During the transition period from CT to CA, immobilization of N takes place as a result of slow turnover of SOM (Pekrun et al., 2003). Sainju et al. (2013) found that surface soil residue and N storage increased in ST while there was increased microbial activity and N mineralization in CT because of residue incorporation to a greater depth. In Mexico, Govaerts et al. (2007) found that tillage and residue management effects did not significantly affect the concentrations of NH₄-N and NO₃-N in surface soil (0-5 cm) while the highest concentrations of NO₃-N was found in CT at 5-20 cm soil layer compared to PRB. Practicing NT in wheat-maize cropping system for 11 years significantly increased available N at the top 10 cm by 31 34

83 % as compared to CT treatment in North China Plain (He et al., 2011). In most previous studies, the soil NO₃-N and NH₄-N has been determined at the end of different field experiments. There are limited studies on changes in NO₃-N and NH₄-N, both during (when plant demand of NO₃-N and NH₄-N is high, at time of greater decomposition of residue) and after harvest of the dryland crop grown following rice. The measurement of soil NO₃-N and NH₄-N a number of times during crop growth may be necessary to understand the dynamics of N availability and their implication for crop N uptake Potentially mineralizable nitrogen The potentially mineralizable nitrogen (PMN) is the amount of N that will mineralize in infinite time at optimum temperature and moisture (Curtin & Campbell, 2007). An accurate estimate of potentially mineralizable N (PMN) in soil is useful to predict optimum crop yield and quality and also to minimize N loss to the environment that may result from overuse of fertilizers (Bordoloi et al., 2013). Tillage and residue management can greatly affect PMN (Mikha et al., 2006). Doran (1987) reported that the PMN was greater in the cm soil layer under ZT, which might be due to either greater immobilization, less mineralization or both as compared to CT. From a series of four long-term tillage trials in Canada, Sharifi et al. (2008) found greater PMN under NT than under CT at three of the four sites. Franzluebbers et al. (1995) also reported that PNM was greater in NT than in CT at 0-5 cm soil depth after 9 years in south-central Texas Research gaps and objectives Rice-based cropping systems in the Eastern IGP are among the most intensive cropping systems in the world. However, the annual alternation between anaerobic, puddled and aerobic soil conditions inevitably results in soil degradation. This is compounded, at least in traditional systems in Asia, by residue removal and intensive tillage for both rice and aerobic crops. Plough pan development and degraded soil physical conditions restrict root growth and deplete SOM and nutrients. Conservation agriculture methods, including minimum tillage and residue retention, show promise in alleviating this soil degradation. However, most such studies have been conducted in the western and central IGP, but little is known of the effects of minimum tillage and residue 35

84 retention in the rice-based cropping systems of the Eastern IGP that includes Bangladesh. Here, the specific research needs include: Assessment of the impacts of minimum tillage and residue retention on productivity of upland crops and rice and on soil conditions of rice-based cropping systems. Investigation of the extent to which minimum tillage and residue retention can increase yield through conserving soil moisture and improving soil properties. This needs to be studied in the Bangladesh context where most farmers remove much of the crop residues for use as livestock feed, building materials and fuel. Although there have been short-term studies of growing crops on raised beds or permanent raised beds and their effects on wheat performance in Bangladesh, the effects of ST as implemented with 2-WT have not yet been comprehensively evaluated. Thus there is a need to understand effects of ST on crop production, soil properties and nutrient pools in contrasting soil types in intensive rice-based systems. There is also a need to compare performance of crops on raised beds and strip tillage. While many single-season crop comparisons have been done, there is a shortage of studies that have implemented these tillage options and residue retention in all crops in the rotation and continued these for more than two crop cycles. In this thesis, different tillage practices, namely ST, BP and CT; and residue management, namely retention of HR and LR on soil properties and crop performance of two intensive rice-based systems under contrasting environments were investigated. One system was a legume-dominated (lentil-mungbean-monsoon rice) system where two legume crops were grown in the annual rotation in an alluvium area. Another system was a cereal-dominated rotation (wheat-mungbean-monsoon rice) where two cereal crops were grown in the system in a drought prone area, the High Barind Tract (HBT). 36

85 The objectives of this thesis are therefore, in contrasting rice-based cropping rotations of Bangladesh, to evaluate the effects of soil disturbance and residue management levels on: crop biomass production and yield over a three-year period; soil physical conditions and rooting habit of the cool dry season crop; soil organic carbon and its turnover; and the C budget; soil N pools, turnover, and N balance and nitrogen use efficiency. 37

86 2 Effects of tillage and residue management on yield and yield attributes of winter crops in rice-based systems in Bangladesh 2.1 Introduction The cropping sector in Bangladesh is heavily dominated by rice which is grown on more than three-fourths of the total cultivable land throughout the year in three distinct cropping seasons (Hoque, 2001). However, rice-based cropping systems are necessarily complex as rice and post-rice (upland) crops are grown under different soil conditions. Rice cultivation in South Asia is characterized by puddling of soil before rice establishment and removal or burning of crop residues. Although puddling has some benefit for weed control, seedling transplanting and reduced deep percolation of the standing water (Ringrose-Voase et al., 2000), it destroys soil aggregates, and degrades other soil physical properties to the detriment of the following upland crop (Sharma & De Datta, 1986). Field preparation for a following upland crop is impeded owing to drying of the soil and the formation of hard cracked soil blocks (Aggarwal et al., 1995). Consequently, extra tillage and irrigation are necessary to prepare a good seedbed after rice, which causes delayed planting and ultimately results in lower yield potential (Hobbs, 2001). It is argued that crop diversification is essential for sustaining farming systems through the improvement of soil fertility, reduction of production risk (Hoque, 2001), and weakening of the plough pan which forms under intensive rice cultivation (Salam et al., 2014). Wheat is the second most important cereal crop in Bangladesh on the basis of harvested area (Food and Agriculture Organization, 2013b). However, continuous cereal cropping in the rice wheat system and intensive cultivation may further exacerbate declining soil physical properties and there are reports of declining crop yields in intensive rice-based cropping of Bangladesh (Ladha et al., 2003a; Mollah et al., 2007). Rice-wheat cropping systems remove on average 278, 53 and 287 kg/ha of N, P and K annually from crop land in the Indo-Gangetic Plains (IGP) (Singh & Singh, 2001). Inclusion of legumes in the cropping system is a possible form of crop diversification 38

87 that also improves fertility status of soil (Kumar Rao et al., 1998; Porpavai et al., 2011) and increases system productivity and economic returns (Bhushan et al., 2007). To produce more food from less land, crop intensification is necessary however it needs to be a sustainable intensification. Increasing intensity of land cultivation by raising three crops in a year instead of two may reduce yield of individual crops by degrading soil physical, chemical and biological properties (Bhattacharyya et al., 2008; Johansen et al., 2012; Singh & Kaur, 2012). Possible intensification approaches to addressing this problem include conservation agriculture (no-till farming), covercropping and integrated nutrient management (Lal, 2013). Legume-based cropping sequences and conservation agriculture (CA) have the potential to enhance soil organic carbon (SOC) and soil total nitrogen (TN) and improve soil aggregation (Bhattacharyya et al., 2009b), which should lead to their positive residual effects on succeeding crops. Conservation agriculture has potential application in diverse agro-ecological zones, and has been advocated for enhancing food security for millions of smallholders in the developing world (Derpsch & Friedrich, 2009). It is proposed as a panacea to agricultural problems in smallholder farming systems, although its applicability for particular agro-environments needs to be properly demonstrated (Chivenge et al., 2007). Pittelkow et al. (2015a) showed from a meta-analysis of 610 studies worldwide involving 5,463 paired comparisons that zero-tillage (ZT) alone decreased yields and even with rotations and residue retention there was a small overall decrease in crop yields. By contrast, in dry climates, the overall effect of ZT with and without residue retention and rotation of crop was to increase yields. Conservation agriculture is based on the three key principles, namely minimal soil disturbance, and permanent soil cover combined with diverse crop rotations (Hobbs, 2007a). Many positive benefits are claimed for CA such as increased crop yield (Bhushan et al., 2007; Farooq et al., 2011; Saha & Ghosh, 2013; Choudhury et al., 2014), improved production and reduced cost (Erenstein & Laxmi, 2008). Compared to conventional tillage, CA practices generally result in improved crop yield and productivity. For example, Ghuman and Sur (2001) showed in a 5-year field experiment of the subtropical climate of Northwest Punjab, India that minimum tillage and crop residue retention improved soil properties and 39

88 sustained crop production. By contrast, Powlson et al. (2014) concluded from a metaanalysis of 43 studies that the net benefits of CA were small and often overstated. However, the rice-based intensive cropping systems of the Eastern Indo-Gangetic Plains (EIGP) are poorly represented in the studies of Powlson et al. (2014) and Pittlekow et al. (2015). Hence questions remain about the effects of CA implementation on SOC and crop yields in this system. In the western and central IGP of India and Pakistan, CA based on 4-WT has been well researched during the last two decades. However, CA based on 2-WT is under development and there is limited information on crop performance particularly in intensive rice-based systems in the EIGP. Due to small and scattered fields in Bangladesh, 4-wheel tractors (4-WT) are not suitable for mechanization (Roy & Singh, 2008; Sarkar et al., 2012). Under these circumstances, the Versatile Multi-crop Planter (VMP) mounted on a 2-wheel tractor (2-WT) has been developed for CA practices on small farms, to handle diverse cropping systems and multiple planting modes (singlepass shallow-tillage; strip tillage; zero tillage; bed planting, and conventional tillage) with a wide range of crops (Haque et al., 2011). This machine is also capable of placing seed and fertilizer in rows when driven by hp 2-WT. This study evaluates the CA options of minimum tillage and residue retention in two representative cropping systems in Bangladesh, i.e. rice-wheat-mungbean in silty clay upland soil in the High Barind Tract (HBT) and rice-lentil-mungbean on an alluvial loam soil. In this Chapter, the aim was to evaluate the effect of three types of tillage (strip tillage-st, bed planting-bp and conventional tillage-ct) and two residue levels (high residue-hr and low residue-lr) on lentil and wheat growth and their yield performance under different rice-based cropping systems in two regions of Bangladesh in a 3-year ( , and ) field experiment. 2.2 Materials and Methods Two experiments were conducted over three years ( ) in rice-based systems (legume-dominant and cereal-dominant rotations) at two locations in Bangladesh. Site 40

89 and climatic conditions are described in Table 2.1 and Figure 2.1, and baseline soil properties are described in Table 2.2. Table 2.1. Site characteristics of two different experiments under different cropping systems. Characteristics Legume-dominant system Cereal-dominant system Location (Figure 2.1) Alipur, Durgapur, Rajshahi, Bangladesh Digram, Godagari, Rajshahi, Bangladesh Latitude, longitude N, E N, E Elevation above sea level 20 m 40 m Agro-ecological zone (AEZ) AEZ-11 (High Ganges river flood plain) AEZ-26 (High Barind Tract) Crop rotation tested lentil-mungbean-rice (Legume-dominated system) wheat-mungbean-rice (Cereal-dominated system) General site physiography Alluvial plain Drought-prone uplifted and undulating ancient alluvial area Taxonomic soil classification (Huq & Shoaib, 2013) Soil tracts Gangetic alluvium High Barind Tract Subgroup (USDA) Typic Haplaquepts Aeric Albaquepts Soil series Arial/Sara Atahar Physiographic unit Ganges river flood plain Barind Tract Parent material types Ganges river alluvium Madhupur Clay USDA - United States Department of Agriculture; m - metre Climate and weather Climatic conditions of both experimental sites are characterized by hot and humid summers, and cool winters with an average annual rainfall of 1134 mm at the weather station representative of both experimental sites, most of which is received from June to August. During , monthly mean temperature was lowest (10 C) in January and highest (36 C) in April-May (Figure 2.2). 41

90 (A) (B) (C) Figure 2.1. General soil map of Bangladesh showing field study sites (A); High Barind Tract, Digram, Godagari, Rajshahi (red circle) in figure (B); and; Alipur, Durgapur, Rajshahi (yellow circle) in figure (C). Daily temperature and rainfall data were collected by the weather station at Shyampur, Rajshahi, Bangladesh. The weather station is approximately 10 km from Alipur and 25 km from Digram. 42

91 Table 2.2. Basic soil properties and nutrient status of study sites at Alipur and Digram. Soil properties Soil Sites Protocol Reference depth Alipur Digram (cm) ph (1:5 H 2O) Glass electrode Thomas (1996) Electrical Conductivity (ds/m) (1:2.5 H 2O) Electrical conductivity meter Organic Carbon (mg/g) Walkley and Black Rayment and Higginson (1992) Total N (mg N/g) Kjeldahl method O'Neill and Webb (1970) C:N ratio Cation Exchange Capacity (cmol/kg) Ammonium acetate extraction Scholenberger and Simon (1945) Textural class Silty loam Silty Hydrometer method Bouyoucos (1962) loam Sand (g/kg) Silt (g/kg) Clay (g/kg) Bulk density (g/cm 3 ) Core sampler method Black and Hartge (1986) Experimental design and treatments The experiment included four replicates of each treatment in a split-plot design. The main plots were assigned to three types of tillage, namely strip tillage (ST), bed planting (BP) (as defined in Chapter 1) and a conventional tillage system (CT). In CT, intensive tillage is used for non-rice crop and puddling (wet tillage) used for the cultivation of rice crops (Table 2.3). A VMP was used for planting non-rice crops under ST and BP while unpuddled rice was transplanted following strip tillage (Haque et al., 2016). Two previous crop residue treatments were assigned in the sub-plots retention of high residue (100 % legume residue + 50 % cereal residue) and retention of low residue (0 % legume residue + 20 % cereal residue) (Table 2.4). These treatments were repeated in the same plots for each crop over the three years. At Alipur, main plot size was 7.5 m long x 14 m wide and sub-plot was 7.5 m long x 7 m 43

92 wide and; the main plot was 8.5 m long x 14 m wide and sub-plot was 8.5 m long x 7 m wide at Digram. Table 2.3. Details of three tillage treatments at Alipur and Digram. Tillage Strip-tillage ST (Figure 4.2) Bed planting system (Permanent beds were reshaped during the sowing of each non-rice crop) BP (Figure 4.3) Conventional tillage CT (Control) Details Versatile Multi-crop Planter (VMP) used to form strip row to row distance 20 cm for both wheat and lentil tillage and seed placement 5-7 cm deep strip width 4-5 cm VMP used to form and reshape bed for every non-rice crop mid-furrow to mid-furrow distance 55 cm usually 2 rows of rice or non-rice crop per bed with a row spacing on the beds of 20 cm (cereal crop)/20-25 cm (legume crop) head to head width (Bed) 30 cm base to base width (Bed) 45 cm base to base width (furrow) 10 cm height of the bed 11 cm (from base of the furrow to the level of the bed top) reshaped beds before sowing of each crop is a mode of reduced tillage while newly formed beds (i.e. for Crop 1) involve a high levels of soil disturbance Three times full rotary tillage by 2-WT, tillage to depths of about 6 to 9 cm depth, incorporating residue, followed by one time land leveling broadcast seed sowing before final rotary tillage operation Residue management protocols The high and low residue covers were retained based on the average height of residue across all experimental plots. Afterwards the retained residue for the specific height was cut in quadrats, dried and weight; and converted to tonne per hectare for each height. There were two types of residue retained in the present trials: 1) anchored residue-standing residue retained, and 2) loose residue-residue chopped and placed on the soil surface. The details of residue management protocols of the cropping sequence at Alipur in are presented in Table

93 Table 2.4. Details of residue management protocols of the lentil-mungbean-monsoon rice cropping sequence at Alipur in Crop #. Crop residue Year (and residue type) Previous rice 2010 residue (Loose) Residue weight (t/ha) and Residue weight (t/ha) and height (cm, in parentheses) height (cm, in parentheses) for high residue plot for low residue plot 1 ST - 5, 1 BP - 5, 1 CT - 5 ST - 2, BP - 2, CT Lentil residue (Loose) 100 % residue returned to the same plot after mungbean No above ground residue returned to plot sowing ST - 2.1, BP - 1.6, CT Mungbean residue 2011 (Anchored) 100 % residue retained except pods (estimated residue weight No above ground residue retained from the succeeding years) ST (74.6 cm), BP (72.2 cm), CT (76.9 cm) 3 Rice residue 2011 (Anchored) ST (60 cm), BP (60 cm), CT (60 cm) ST (24 cm), BP (24 cm), CT (24 cm) 4 Lentil (Loose) 100 % residue returned to the same plot after sowing No above ground residue returned to plot ST , BP , CT Mungbean residue 2012 (Anchored) 100 % residue retained except husk No above ground residue returned to plot ST (60.7 cm), BP (60.1 cm), CT (60.1 cm) 6 Rice residue 2012 (Anchored) ST (61 cm), BP (61 cm), CT (61 cm) ST (24 cm), BP (24 cm), CT (24 cm) 7 Lentil (Loose) 100 % residue returned to the same plot after sowing of mungbean ST , BP , CT No above ground residue Total amount of residue (t/ha) deposited during 7 successive crops ST , BP , CT ST , BP , CT ST - strip tillage; BP - bed planting; CT - conventional tillage; Crop # - Crop number in the sequence The residue management protocols of the wheat-mungbean-monsoon rice cropping system at Digram in are presented in Table

94 Table 2.5. Details of residue management protocols of wheat-mungbean-monsoon rice cropping sequence at Digram in Crop #. Crop residue Year (and residue type) Previous rice 2010 residue (Anchored) Residue weight (t/ha) and Residue weight (t/ha) and height height (cm, in parentheses) (cm, in parentheses) for high residue plot for low residue plot 1 ST , 1 BP , 1 CT ST , BP , CT Wheat residue (Anchored) ST (47 cm), BP (47 cm), CT (47 cm) ST (19 cm), BP (19 cm), CT (19 cm) 2 Mungbean % residue retained except No above ground residue retained residue (Anchored) pods (estimated from the following years) ST (51.6 cm), BP (50.2 cm), CT (54.1 cm) 3 Rice residue 2011 (Anchored) ST (62.5 cm), BP (62.5 cm), CT (62.5 cm) ST (25 cm), BP (25 cm), CT (25 cm) 4 Wheat residue (Anchored) ST (50 cm), BP (50 cm), CT (50 cm) ST (20 cm), BP (20 cm), CT (20 cm) 5 Mungbean % residue retained except No above ground residue retained residue (Anchored) husk ST (54.1 cm), BP (50.2 cm), CT (51.6 cm) 6 Rice residue 2012 (Anchored) ST (55 cm), BP (55 cm), CT (55 cm) ST (22 cm), BP (22 cm), CT (22 cm) 7 Wheat residue (Anchored) ST (52 cm), BP (52 cm), CT (52 cm) ST (21 cm), BP (21 cm), CT (21 cm) Total amount of residue retained (t/ha) during 7 successive crops ST , BP , CT ST , BP , CT ST - strip tillage; BP - bed planting; CT - conventional tillage; Crop # - Crop number in the sequence Agronomy of legume-dominant system The field trials at Alipur were initiated with winter lentil (Lens culinaris Medik.) in (Nov-Mar); followed by mungbean (Vigna radiata (L.) R. Wilczek) in the early wet season of 2011 (Mar-May) and then transplanted rice (Oryza sativa L.) in the main wet season of 2011 (Jul-Oct). This sequence was continued until Crop 7. Lentil crops were studied in detail but only grain and biomass data of rice and mungbean in the system 46

95 are presented. Table 2.6 outlines the details of the production technology of the lentilmungbean-monsoon rice system. Table 2.6. Details of crop, variety, seed rate or seedlings/hill, row spacing, sowing and harvesting date of lentil-mungbean-monsoon rice cropping sequence during at Alipur. Year Crop Variety Seed rate (kg/ha) or Date of sowing Date of harvesting Row spacing (cm) seedlings of rice/hill Lentil BARI Masur Nov, 8 Mar, cm Mungbean BARI Mung Mar, May-10 Jun, 2011 ST - 30 cm, BP - 30 cm 2011 Monsoon rice Hybrid rice Tej (Bayer crop Two seedlings/hill 8 Jul, Oct, 2011 ST and BP - 20 cm Science) Lentil BARI Masur Nov, Mar, 2012 ST - 25 cm, BP - 25 cm 2012 Mungbean BARI Mung Mar, May, 2012 ST - 25 cm, BP - 20 cm 2012 Monsoon rice Hybrid rice (ACI-1) Two seedlings/hill Seeding-6 Jun, Oct, 2012 ST and BP - 20 cm Planting-5 Jul, Lentil BARI Masur Nov, Mar, 2013 ST and BP - 20 cm Note: Transplanting of monsoon rice in unpuddled soil for ST and BP; puddled soil for CT Nutrient management Both lentil and mungbean were fertilized during final land preparation at the rate of 20, 20, 20 and 1 kg/ha of nitrogen (N), phosphorus (P) in the form of DAP and potassium (K) and boron (B) in the form of muriate of potash (MP) and boric acid, respectively, as recommended by the Pulses Research Centre, Bangladesh. The BINA (Bangladesh Institute of Nuclear Agriculture)-LT-18 Rhizobium inoculum for lentil and BINA-MB-1 Bradyrhizobium inoculum for mungbean were applied at the rate of 50 47

96 g/kg seed. Only DAP fertilizer, a source of N and P, was drilled with seed by VMP while other fertilizers were broadcast in ST and BP plots and all fertilizers were broadcast in CT plots. Both puddled and unpuddled monsoon rice in the rotation was fertilized by broadcast application of 90, 10, 35, 12 and 1 kg/ha of N, P, K, S and Zn, respectively Disease, weed and pest management of lentil Prior to seeding of lentil, weeds were suppressed using pre-plant application of glyphosate (Table 2.7) and during the season by one hand weeding at days after sowing (DAS) in every year. The plants were monitored regularly to detect any diseases and insects on lentil plants. In , foot and collar rot disease of lentil, caused by Sclerotium rolfsii, were scored visually for each plot as a percentage of total plant population. Selective fungicides were applied before or at first appearance of fungal diseases (collar rot, a soil-borne disease and stemphylium blight, a foliar disease of lentil). Insecticides were applied to control insects especially for aphids (Aphis craccivora) at their first appearance. The details of weed, pest, diseases and their management practices of lentil are presented in Table Agronomic measurements of lentil Plant density at 30 DAS and at harvest was determined from three randomly located pre-selected (after seeding) quadrats of 0.5 m² each. The average heights of 10 randomly selected plants in each plot were measured from ground level up to the tip of the uppermost leaf. Total number of pods was counted from 10 randomly selected plants per plot. Seeds per pod were calculated from 20 randomly selected pods from the same 10 plants. Five hundred seeds were counted to derive 1000-seed wt. Dry weights of plant parts are reported after oven drying at 65 C to constant weight. 48

97 Table 2.7. Details of disease, insects and weeds in lentil and their management practices. Year Name Frequency and date of application Fungicide Sprayed on canopy twice - 1 and 11 Dec, 2010 Three times - 6 and 25 Jan and 9 Feb, 2011 Name of fungicide, insecticide and herbicide and their functions Bavistin (common name: 2 g/l water to protect against foot and collar rot and foot and root rot diseases (caused by Sclerotium rolfsii, Fusarium avenaceum, Fusarium solani, Rhizoctonia solani, Pythium sp.) Rovral (common name: 2 g/l sprayed against stemphylium blight diseases (Causal pathogen: Stemphylium sp.) Insecticide Twice - 20 and 28 Jan, 2011 Malathion (common name: O,O-dimethyl phosphorodithioate of diethyl 1 ml/l of water to control aphids Herbicide Once - 8 Nov, 2010 Roundup (common name: Isopropylamine salt of Fungicide Three times -30 Nov, 8 and 20 Dec, 2011 Three times-6 and 15 Jan, 15 Feb, 2012 N-(phosphonomethyl) 250 ml/15l H 2O applied 48 hours before lentil sowing Bavistin (common name: 2 g/l water (as above) Rovral (common name: 2 g/l (as above) Insecticide Twice-6 Jan, 16 Feb, 2012 Malathion (common name: O,O-dimethyl phosphorodithioate of diethyl 1 ml/l of water (as above) Herbicide Once -10 Nov, 2011 Roundup (common name: Isopropylamine salt of Fungicide Three times - 2,18 and 29 Dec, Weeding 2012 Once - 12 Dec, 2012 Three times - 16 Jan, 5 Feb, 20 Feb, 2013 N-(phosphonomethyl) glycine) 250 ml/15 L H 2O (as above) Bavistin (common name: 2 g/l water (as above) Provex (common name: 2 g/l water Rovral (common name: 2 g/l (as above) Insecticide Twice Jan, 2013 Malathion (common name: O,O-dimethyl phosphorodithioate of diethyl 1 ml/l of water (as above) Herbicide Twice Nov, 2013 Roundup (common name: Isopropylamine salt of Hand weeding at DAS in every year N-(phosphonomethyl) glycine) 250 ml/15 L H 2O (as above) 49

98 2.2.5 Agronomy of cereal-dominated systems The Digram field trial was initiated with winter wheat (Triticum aestivum L.) in (Nov-Mar); followed by mungbean in the early wet season of 2011 (Mar-May) and then transplanted rice in the main wet season of 2011 (Jul-Oct). Wheat crops were studied in detail but only grain and biomass data of rice and mungbean in the system are presented. This system was continued for 7 crops following the same sequence of crops. Table 2.8 outlines the details of crop, variety, seed rate or seedlings/hill, line to line distance, sowing and harvesting date of wheat-mungbean-monsoon rice cropping sequence during Table 2.8. Details of crop, variety, seed rate or seedlings/hill, row spacing, sowing and harvesting date of wheat-mungbean-monsoon rice cropping sequence at Digram during Year Crop Variety Seed rate Row Date of sowing Date of harvesting (kg/ha) /rice seedlings /hill spacing (cm) (and or transplanting of monsoon rice) Wheat BARI Gom Dec, Apr, 2011 (Prodip) 2011 Mungbean BARI Mung Apr, Jun, Monsoon Local variety Two seedlings 20-25/15 12 Jul, Nov, 2011 rice Swarna /hill Wheat BARI Gom Dec, 29 Mar, 2012 (Prodip) Mungbean BARI Mung Apr, Jun, Monsoon BRRI Dhan 51 Two Jul, Nov, 2012 rice seedlings/hill Wheat BARI Gom 24 (Prodip) Dec, Mar, 2013 Note: Transplanting of monsoon rice in unpuddled soil for ST and BP; puddled soil for CT Crop husbandry of wheat Although the irrigation amount was not precisely measured in this experiment, the same amount (each application ~ 3 cm) was applied to all the treatments following the 50

99 same procedure for all irrigations. Generally two to three irrigations, depending on rainfall during wheat season are necessary for growing wheat (Mojid et al., 2013). Two flood irrigations at 27 and 72 DAS were applied in In , three irrigations were applied at 32, 64 and 92 DAS. In , two irrigations at 32 and 60 DAS were applied and a third irrigation was not applied as a downpour occurred before hand. The seeds of wheat were treated with the fungicide Provex at the rate of 3 g/kg seed just before seed sowing in the field for controlling the major seed and soil borne diseases. Nutrient management Fertilizers were applied for wheat at the rate of kg/ha of N, P, K and S in the form of urea, DAP, MP and gypsum, respectively, as recommended by the Wheat Research Centre, Bangladesh (Wheat Research Centre, 2004). Two-thirds of urea and all of DAP, MP and gypsum were applied before final land preparation. The remaining one-third of urea was applied as a top dressing after the first irrigation. The DAP was drilled with seed by VMP while other fertilizers were broadcast in ST and BP plots. However, for conventional tilled plots, all fertilizers were broadcast. Mungbean was fertilized and supplied with Rhizobium inoculants as described above. Monsoon rice in the rotation was fertilized by broadcasting at the rate of 90, 10, 50, 8 and 1 kg/ha of N, P and K, S and Zn. Weed, insect and bird management Intensive care was taken to control bird damage to seed and to seedlings up to 25 days after sowing (DAS). One hand weeding was done at DAS when the soil drained to field capacity in the first and second growing season and in the third growing season Affinity herbicide 2.5 g/litre water was applied after the first irrigation. In and , soap solution was applied to control aphids which appeared sporadically in the experimental field. Aphid infestation was severe in and Malathion 57 3 ml/l of H2O was applied to control these aphids. 51

100 Agronomic measurements of wheat Initial plant population and plant density at harvest were assessed from three preselected quadrats of 0.5 m² each. At harvest, the average heights of 10 plants selected randomly in each plot were measured from ground level up to the tip of the longest leaf blade or spike awn. The number of spikelets/spike and number of grains per spike were calculated from 10 randomly selected spikes per plot. All the grains of the 10 sampled plants were separated from the spikes and oven dried thoroughly to constant moisture content. Thereafter, 1000 grains were counted and their weight was determined Yield measurements for lentil and wheat The crops were harvested from the central 3 m x 2 m area of each plot when the pods (lentil) or spikes (wheat) turned straw colour and the yields were converted to t/ha. The harvested bunches were threshed, cleaned, and sun dried. Grain and straw yield was determined after sun drying from which a 100 g sub-sample from each treatment was taken for oven drying and finally plot dry weights were converted to t/ha. Biological yield (kg/ha) and harvest index (%) were determined as follows- Biological yield (t/ha) = grain + straw yield Harvest index (%) (HI) = grain yield/biological yield x Statistical analysis Data were analysed separately for lentil and wheat each year using GenStat 15 th Edition (VSN International Ltd, United Kingdom). Mean values were calculated for each set of measurements, and analysis of variance (ANOVA) for split-plot design was performed to assess treatment effects on the measured variables. When the F-test was significant, treatment means were separated by least significant difference (LSD) at P A correlation matrix of different yield and yield attributes were based on Pearson correlation coefficients (P 0.01 and P 0.05). 52

101 2.3 Results Weather The weather conditions at the experimental locations were quite variable during the three years of experimentation. The monthly rainfall and minimum/maximum temperatures for the years 2010 to 2013 are shown in Figure 2.2. The rainfall was highest in (1108 mm) followed by (1092 mm) and (909 mm) up to the lentil harvest (Mar 13). Most rain was received during the summer season, during May-September. During lentil and wheat growing seasons (Nov-Mar), the amount of rainfall was highest in (136 mm), less in (59 mm) and negligible in (14 mm). In , it rained on 8-9 Dec at the start of the growing season. There was no rainfall except drizzle during the second lentil growing season (Nov-Mar). In the third lentil growing season, mm rainfall occurred in November (4-7 Nov, 2012) before crop sowing. In the middle of the growing season on 20 Jan, 2013 there was drizzle and 22 mm rainfall occurred in February (17-18 Feb, 2013). 53

102 Monthly rainfall (mm) Jul-10 Rice Aug-10 Sep Rainfall Max. Temp. Min. Temp. Total rainfall: 1092 mm Lentil/wheat Mung Oct-10 Nov-10 Dec-10 Jan-11 Feb-11 Mar-11 Apr-11 May-11 Jun-11 Mean mothly temperature ( C) Monthly rainfall (mm) Jul-11 Aug Rainfall Max. Temp. Min. Temp. 45 Total rainfall: 1108 mm Sep-11 Oct-11 Nov-11 Dec-11 Jan-12 Feb-12 Mar-12 Apr-12 May-12 Jun-12 Mean mothly temperature ( C) Months Monthly rainfall (mm) Months Rainfall Max. Temp. Min. Temp. 45 Total rainfall: 909 mm Jul-12 Aug-12 Sep-12 Oct-12 Nov-12 Dec-12 Jan-13 Feb-13 Mean mothly temperature ( C) Mar-13 Apr-13 May-13 Jun-13 Month Figure 2.2. Monthly and annual rainfall, mean maximum and minimum temperatures over the 33-months period of at the experimental site. The mean monthly minimum and maximum temperatures were similar across the years. The daily minimum temperature in these years reached 3-4 C and foggy weather persisted continuously from 8 to 24 Dec in the second growing season. April and May were the hottest months with mean monthly maximum temperatures of 38 C in May, December and January were the coldest months with mean monthly minimum temperature of 9-12 C in Tillage and residue effects on crop performance of legume-dominated system Seed and straw yield of lentil In the legume-dominated system, the seed yield of lentil ( t/ha) under CTHR, CTLR, STHR and STLR was higher while lower under BPHR (1.58 t/ha) and BPLR (1.37 t/ha) in Year 1 (Figure 2.3a1). Although depressed yield was measured with BP there was no yield variation between ST and CT in Year 1 (Figure 2.3a1). In Year 2, the seed 54

103 Seed yield (t/ha) Straw yield (t/ha) yield of lentil was 15 % higher in HR than LR (Figure 2.3a2). In Year 3, compared to CT, the seed yield of lentil was higher by 23 % in ST and 18 % in BP (Figure 2.3a3) ST-HR a1) ST-LR BP-HR BP-LR CT-HR CT-LR Tillage TillageXResidue ST-HR a2) ST-LR BP-HR BP-LR CT-HR CT-LR ST BP CT b1) Residue ST BP CT Tillage treatment b2) Residue ST BP CT c1) Tillage treatment Tillage ST BP CT C2) Tillage treatment Tillage Figure 2.3. Effects of tillage and residue retention on lentil seed yield (Figure a1-c1) and straw yield (Figure a2 c2) over three growing seasons. ST strip tillage, BP bed planting, CT conventional tillage; HR high residue, LR low residue. Values are means of four replicates ± standard error of mean and the floating error bar on each figure represents the least significant difference (LSD) for significant effects at P ST BP CT Tillage and residue treatment 0.0 ST BP CT Tillage and residue treatment In Year 1, the straw yield of lentil was not significantly affected either by tillage or residue or their interaction (Figure 2.3a2). In Year 2, the straw yield of lentil with HR was 22 % higher than LR (Figure 2.3b2). However, in Year 3, the straw yield of lentil with ST and BP were 28 % and 25 % higher over CT (Figure 2.3c2). 55

104 Yield components of lentil Plant population and branching of lentil The overall plant establishment in all treatments was satisfactory for all the study years. There were no treatment effects on plant population either at 30 DAS or at harvest in the first two years (Table 2.9). In , there was a significant tillage and residue interaction on plant population at both 30 DAS and at harvest. In , the plant populations (214 and 214 plants/m²) of STHR were higher than that of CTHR (144 and 143 plants/m²) at 30 DAS and harvest. In ST and BP, HR increased plant population while it decreased in CT (Table 2.9). Table 2.9. Tillage and residue effects on plant population and branching of lentil. Tillage treatment 1 HR 1 LR Mean HR LR Mean HR LR Mean Plant population/m² at 30 DAS ST BP CT Mean LSD Tillage (T) ns ns 32.8* Residue (R) ns ns ns TxR ns ns 35.3* Plant population/m² at harvest ST BP CT Mean LSD 0.05 Tillage (T) ns ns 42.4* Residue (R) ns ns ns TxR ns ns 44.0* Branches/plant ST BP CT Mean

105 LSD 0.05 Tillage (T) 16.4* ns 2.04* Residue (R) ns 2.8** 1.04* TxR ns ns ns 1 HR - high residue; LR - low residue, ST - strip tillage; BP - bed planting; CT - conventional tillage; 2 the least significant difference (LSD) at the P 0.05, ns - not significant, * - significant at P 0.05 and ** - significant at P Several plants were affected by foot and collar rot diseases in the first few days after sowing in every year but the infestation was higher in third growing season with BP (Table 2.10). At flowering to podding stage, generally stemphylium leaf blight (SLB) disease was more visible in the CT plot in all the growing seasons but no quantitative data on these differences were gathered. Some plants were affected by aphids during the vegetative and flowering stages. Apart from these pests and diseases, over the whole growing period the crop grew well with good canopy development and maintained similar plant density until harvest. Table Tillage and residue effects on plant population (%) affected by foot and collar rot diseases of lentil in Tillage 14 December, December, December, 12 treatment 1 Residue treatment 1 Residue treatment Residue treatment HR 1 LR Mean HR LR Mean HR LR Mean ST BP CT Mean LSD Tillage (T) 2.8* 4.9* 6.5* Residue (R) ns ns ns TxR ns ns ns 1 HR - high residue; LR - low residue, ST - strip tillage; BP - bed planting; CT - conventional tillage; 2 the least significant difference (LSD) at the P 0.05, ns - not significant, * - significant at P 0.05 and ** - significant at P

106 In the season, the highest number of branches (55.8) was in plants grown in CT (Table 2.9). In , HR increased branch number. In , the highest number of branches (35.4) was obtained in BP compared to other tillage treatments. In , when branch numbers were less than half those of the previous two years, HR increased number of branches per plant from 15.8 to 17 per plant. Plant height, pods/plant, seeds/plant, 1000-seed weight and harvest index The HR treatments significantly increased plant height by 1-4 cm in all the study years but tillage had no effects on plant height (Table 2.11). Table Tillage and residue effects on plant height, pods/plant and seeds/plant of lentil. Tillage treatment 1 HR 1 LR Mean HR LR Mean HR LR Mean Plant height (cm) ST BP CT Mean LSD Tillage (T) ns ns ns Residue (R) 0.71** 1.30** 0.91** TxR ns ns ns Pods/plant ST BP CT Mean LSD 0.05 Tillage (T) 31.2** 10.8** ns Residue (R) ns 10.0** ns TxR ns ns ns Seeds/pod ST BP CT Mean

107 LSD 0.05 Tillage (T) 0.055* ns ns Residue (R) 0.058* ns ns TxR ns 0.05* ns 1 HR - high residue; LR - low residue, ST - strip tillage; BP - bed planting; CT - conventional tillage; 2 the least significant difference (LSD) at the P 0.05, ns - not significant, * - significant at P 0.05 and ** - significant at P In , there were significantly higher number of pods/plant in CT treatment (168) than that of ST (115) and BP (118) treatments (Table 2.11). In , the pods/plant of BP (116) was higher than that of CT (100) and ST (98). In , HR increased pods/plant (112) relative to LR (98). In , the pods/plant was not affected either by tillage or residue treatments. In , the seeds/pod of BP (1.86) was higher than that of CT (1.85) and ST (1.80) (Table 2.11). In , the significantly highest number of seeds/pod (1.78) was counted in BPHR and the lowest in CTHR (1.71) (Table 2.11). Treatments had no effect on 1000-seed weight except in , when the 1000-seed weight of STLR (19.3) was higher than that of STHR (17.4) (Table 2.12). The harvest index was significantly higher with HR (48.9) than LR treatment (47.6) in ; but in , the harvest index was higher in LR (53.4) than HR (51.2) (Table 2.12). The harvest index was not affected by tillage and residue retention in (Table 2.12). 59

108 Table Tillage and residue effects on 1000-seed weight and harvest index. Tillage treatment 1 HR 1 LR Mean HR LR Mean HR LR Mean 1000-seed weight ST BP CT Mean LSD Tillage (T) ns ns ns Residue (R) ns 0.46** ns TxR ns 0.80** ns Harvest index (%) ST BP CT Mean LSD 0.05 Tillage (T) ns ns ns Residue (R) 1.06* 1.42** ns TxR ns ns ns 1 HR - high residue; LR - low residue, ST - strip tillage; BP - bed planting; CT - conventional tillage; 2 the least significant difference (LSD) at the P 0.05, ns - not significant, * - significant at P 0.05 and ** - significant at P Correlation and regression of yield and yield components of lentil In , number of branches/plant and pods/plant were positively correlated with seed yield (Table 2.13) and both parameters were correlated to each other. There was a significant positive correlation between lentil seed yield and both plant population and plant height in Straw yield also showed a significant correlation with plant population, plant height and seed yield. 60

109 Table Correlation matrix of important yield attributes and yields of lentil Plant population Plant height Branches /plant Pods Seeds Seed yield Straw yield Plant population 1 Plant height Branches/plant Pods * 1 Seeds ** Seed yield ** 0.49* Straw yield Plant population Plant height Branches /plant Pods Seeds Seed yield Straw yield Plant population 1 Plant height Branches/plant * 1 Pods * 0.79** 1 Seeds Seed yield 0.44* 0.80** Straw yield 0.43* 0.83** * Plant population Plant height Branches /plant Pods Seeds Seed yield Straw yield Plant population 1 Plant height Branches/plant Pods * 0.54** 1 Seeds Seed yield 0.71** Straw yield 0.68** ** 1 * - significant at 5% level and ** - significant at 1% level Pod number increased with increasing plant height and branch number as their relationships were significantly positive. In , plant population was positively correlated with seed and straw yield of lentil. The number of pods significantly increased with increasing plant height and branches. 61

110 Seed yield (t/ha) Seed yield (t/ha) The relationship between plant population/m² and yield across all three years ( ) was positive (R² = 0.31) and linear (Figure 2.4a-c) but yield was not correlated with branches/plant, or pods/plant (R² = 0.023, R² = 0.012, respectively) a) y = 0.006x R² = b) y = x R² = Plant population per m2 Seed yield (t/ha) c) y = x R² = Branches/plant Pods/ plant Figure 2.4. Regression of a) plant population and seed yield, b) branches/plant and seed yield and c) pods/plant and seed yield for three years of results ( ) Yield performance of rice and mungbean in legume-dominated system There were no treatment effects on yield of rice as Crop 3 in the system, however by Crop 6, grain yield of rice with ST (8.3 t/ha) was higher than with BP (7.0 t/ha) and similar with CT (8.1 t/ha) treatments (Table 2.14). All pods of mungbean as Crop 2 were damaged due to heavy rainfall, hence there was no seed harvested. The yield of mungbean as Crop 5 in the rotation was greater with CT (1.5 t/ha) or BP (1.4 t/ha) than ST (0.9 t/ha); and compared to LR (1.1 t/ha), HR (1.4 t/ha) increased mungbean yield (Table 2.14). Straw yield responses mirrored those of seed yield. 62

111 Table Tillage and residue effects on grain and straw yield of rice and mungbean of lentil-mungbean-monsoon rice cropping system in Alipur. Note: no yield results are available for Crop 2 (mungbean) due to crop damage by heavy rainfall. Tillage Rice Mungbean Rice treatment (Crop 3) 2012 (Crop 5) 2012 (Crop 6) HR 1 LR Mean HR LR Mean HR LR Mean Grain or seed yield (t/ha) ST BP CT Mean LSD Tillage (T) ns 0.39* 1.03* Residue (R) ns 0.11** ns TxR ns ns ns Straw yield (t/ha) ST BP CT Mean LSD 0.05 Tillage (T) ns 0.28** 1.37** Residue (R) ns ns 0.74** TxR ns ns 1.50* 1 HR - high residue; LR - low residue, ST - strip tillage; BP - bed planting; CT - conventional tillage; 2 the least significant difference (LSD) at the P 0.05, ns - not significant, * - significant at P 0.05 and ** - significant at P Tillage and residue effects on crop performance of cereal-dominated system Grain and straw yield of wheat Grain yield of wheat was not affected by tillage and residue treatments in (Figure 2.5a1). In , grain yield of wheat was greater by 39 % in CT and 33 % in ST than BP (Figure 2.5b1). In , the yield of wheat was 9 % higher in ST and 7 % greater in BP than CT, and compared to LR, yield was 3 % higher in HR (Figure 2.5c1). 63

112 Grain yield (t/ha) Straw yield (t/ha) In , the straw yield of wheat with HR was 5 % higher than LR treatment (Figure 2.5a2). In , the straw yield of wheat was higher by 19 % in ST and 27 % in CT than BP; HR had 11 % greater straw yield than LR treatment (Figure 2.5b2). In , the straw yield of wheat with ST was higher by 11 % and 8 % than CT and BP, respectively; the straw yield of wheat was 5 % higher with HR than LR treatment (Figure 2.5c2) ST-HR a1) ST-LR BP-HR BP-LR CT-HR CT-LR ST-HR a2) BP-HR ST-LR BP-LR CT-HR CT-LR Residue ST BP CT Tillage treatment Tillage b1) ST BP CT b2) Tillage treatement Tillage Residue c1) ST BP CT Tillage Residue ST BP CT c2) Tillage treatment Tillage Residue ST BP CT Tillage and residue treatment Figure 2.5. Effects of tillage and residue on wheat grain yield (Figure a1-c1) and straw yield (Fig a2 c2). ST strip tillage, BP bed planting, CT conventional tillage; HR high residue, LR low residue. Values are means of four replicates, ± standard error of mean and the floating error bar on each figure represents the least significant difference (LSD) for significant effects only at P ST BP CT Tillage and residue treatment 64

113 Yield components of wheat Plant population and plant height In , the highest population was obtained with BP, especially with LR, but in ST and CT where plant population was reduced, there was no effect of residue level (Table 2.15). Overall, ST produced a lower plant population than other tillage types at 30 DAS in By harvest, there were no effects of tillage or residue on plant populations due to the decline in plant numbers in BP and CT. Table Tillage and residue effects on plant population and plant height (cm) of wheat. Tillage treatment 1 HR 1 LR Mean HR LR Mean HR LR Mean Plant population/m² at 30 DAS ST BP CT Mean LSD Tillage (T) 16.0** 25.3** ns Residue (R) ns ns 12.7* TxR 23.0* ns ns Plant population/m² at harvest ST BP CT Mean LSD 0.05 Tillage (T) ns 24.9** ns Residue (R) ns ns 9.7* TxR ns ns 26.0* Plant height (cm) ST BP CT Mean LSD 0.05 Tillage (T) ns ns 2.5** 65

114 Residue (R) ns 1.3* ns TxR ns ns ns 1 HR - high residue; LR - low residue, ST - strip tillage; BP - bed planting; CT - conventional tillage; 2 the least significant difference (LSD) at the P 0.05, ns - not significant, * - significant at P 0.05 and ** - significant at P In , the population was 73 % lower in BP and 35 % lower in ST, compared to CT (Table 2.15). In , the plant population at both sampling times under ST was higher than in the previous 2 years and was significantly higher with LR (Table 2.15). There were no treatment effects on plant height at harvest in In , plants grew significantly taller with HR than LR. In , the tallest plants were recorded in BP (Table 2.15). Tillers/plant In , the highest tiller number was in BP (8.3) vs 6.6 in CT and 7.6 in ST; HR had higher tillers/plant (8.0) than LR (7.3) (Table 2.16). In , the highest tillers/plant was again obtained with BP (13.0) followed by ST (9.8) and CT (8.6) (Table 2.16). The numbers of tillers were lower in than in the previous years, but tillage treatment had no effect on total tillers/plant while significantly higher numbers of effective tillers/plant were obtained with HR. 66

115 Table Tillage and residue effects on tillers and effective tillers per plant of wheat. Tillage treatment 1 HR 1 LR Mean HR LR Mean HR LR Mean Total tillers/plant ST BP CT Mean LSD Tillage (T) 0.80** 2.1* ns Residue(R) 0.44* ns ns TxR ns ns ns Effective tillers/plant ST BP CT Mean LSD 0.05 Tillage (T) 0.98* 1.5** ns Residue (R) ns ns 0.54* TxR ns ns ns 1 HR - high residue; LR - low residue, ST - strip tillage; BP - bed planting; CT - conventional tillage; 2 the least significant difference (LSD) at the P 0.05, ns - not significant, * - significant at P 0.05 and ** - significant at P Spikes/m², spike length and spikelets/spike In , the spikes/m 2 was not affected either by tillage or residue retention treatments (Table 2.17). In , the highest spike/m² (266) was counted with CT and lowest with BP (152) (Table 2.17). In , the higher spike/m² was obtained with ST (301) and BP (295) than CT (270); HR had higher spike/m² (295) than LR (283). Across three years, the spikes/m² was remarkably similar in CT and most variable with BP. 67

116 Table Tillage and residue effects on spikes/m², spike length (cm) and spikelets/spike of wheat. Tillage treatment 1 HR 1 LR Mean HR LR Mean HR LR Mean Spikes/m² ST BP CT Mean LSD Tillage (T) ns 59.8** 25.6* Residue (R) ns ns 12.5* TxR ns ns ns Spike length (cm) ST BP CT Mean LSD 0.05 Tillage (T) 0.48** ns 0.37** Residue (R) ns 0.48** 0.26** TxR ns ns 0.44* Spikelets/spike ST BP CT Mean LSD 0.05 Tillage (T) ns ns 0.83* Residue (R) ns ns 0.52** TxR ns ns ns 1 HR - high residue; LR - low residue, ST - strip tillage; BP - bed planting; CT - conventional tillage; 2 the least significant difference (LSD) at the P 0.05, ns - not significant, * - significant at P 0.05 and ** - significant at P In , the higher spike length was obtained with ST (17 cm) than CT (16.2 cm) (Table 2.17). In , HR significantly increased spike length from 18.2 to 19.2 cm (Table 2.17). In , the spike length of BPHR and CTHR (18.6 cm) were higher 68

117 than that of CTLR (17.7 cm) (Table 2.17). The spikelets/spike was unaffected by treatments in Year 1 and 2 (Table 2.17). In Year 3, the spikelets/spike of ST (22.1) and BP (21.8) were higher than that of CT (20.8), HR had higher spikelets/spike (22.0) than LR (21.1) (Table 2.17). Grains/spike, 1000-grain weight and harvest index The grains/spike and 1000-grain weight were not affected by tillage and residue or their combination in all the study years (Table 2.18). In , HI was greater with BP (43.1) and in , the greater HI ( ) was found with ST or CT than BP (38.8) (Table 2.18). Table Tillage and residue effects on grains/spike, 1000-seed weight and harvest index (%) of wheat. Tillage treatment 1 HR LR Mean HR LR Mean HR LR Mean Grains/spike ST BP CT Mean LSD Tillage (T) ns ns ns Residue (R) ns ns ns TxR ns ns ns 1000-grain weight (g) ST BP CT Mean LSD 0.05 Tillage (T) ns ns ns Residue (R) ns ns ns TxR ns ns ns Harvest index (HI) ST BP CT

118 Mean LSD 0.05 Tillage (T) 1.5* 2.3** ns Residue (R) ns ns ns TxR ns ns ns 1 HR - high residue; LR - low residue, ST - strip tillage; BP - bed planting; CT - conventional tillage; 2 the least significant difference (LSD) at the P 0.05, ns - not significant, * - significant at P 0.05 and ** - significant at P Correlation and regression of yield and yield components of wheat The contribution of different yield attributes to yield varied from year to year (Table 2.19). Grain yield had a significant positive correlation with plant height and spikes/m² in The correlation of straw yield with plant height, spikes/m²and grain yield was highly significant. Plant height and spikelets/spike were also correlated. There was a significant positive correlation of plant population/m², plant height, spikes/m² and 1000-seed weight with grain and straw yield of wheat in Among these yield attributes, grain yield had strong positive correlation with plant population/m² and spikes/m². Plant population, plant height and spikes/m² were correlated with one another. In , there was a significant positive correlation of plant height, spikes/m²andspikelets/spike with grain yield of wheat. Straw yield also had a significant correlation with spikelets/spike and grain yield of wheat. Spikes/m² and spikelets/spike were strongly correlated. 70

119 Table Correlation matrix of important yield attributes and yields of wheat Plant population Plant height Spikes /m² Spikelets /spike TSW Grain yield Straw yield Plant population 1 Plant height Spikes/m² Spikelets/spike -0.49* 0.49* TSW Grain yield ** 0.49* Straw yield ** 0.53** ** Plant population Plant height Spikes /m² Spikelets /spike TSW Grain yield Straw yield Plant population 1 Plant height 0.70** 1 Spikes/m² 0.88** 0.69** 1 Spikelets/spike TSW Grain yield 0.82** 0.49* 0.77** * 1 Straw yield 0.77** 0.70** 0.74** * 0.79** Plant population Plant height Spikes /m² Spikelets /spike TSW Grain yield Straw yield Plant population 1 Plant height Spikes/m² Spikelets/spike ** 1 TSW Grain yield * 0.43* 0.55** Straw yield ** ** 1 * - significant at 5% level and ** - significant at 1% level; TSW seed weight Considering the three years results, the correlations of plant population/m² and spikes/m² with yield were positive (R² = 0.34, R² = 0.45, R² = 0.027, respectively) and linear while spikelets/spike was not correlated with yield (Figure 2.6a-c). 71

120 a) y = 0.013x R² = b) y = 0.01x R² = 0.45 Grain yield (t/ha) Plant population per m2 c) Grain yield (t/ha) Spikes/m2 Figure 2.6. Regression of a) plant population and grain yield, b) spikes/m² and grain yield and c) spikelets/spike and grain yield for three years of results ( ) Yield performance of rice and mungbean in cereal-dominated system In the cereal-dominated system, the tillage and residue retention showed no significant effect on the grain and straw yields of rice (Crop 3 and Crop 6) and mungbean (Crop 5) (Table 2.20). Heavy rainfall damaged all pods of Crop 2 (mungbean), therefore no seed yield data could be collected. 72

121 Table Tillage and residue effects on grain and straw yield of rice and mungbean of wheat-mungbean-monsoon rice cropping system in Digram. Note; no yield results are available for Crop 2 (mungbean) due to crop damage by heavy rainfall. Tillage Rice Mungbean Rice treatment (Crop 3) 2012 (Crop 5) 2012 (Crop 6) HR 1 LR 1 Mean HR LR Mean HR LR Mean Grain yield (t/ha) ST BP CT Mean LSD Tillage (T) ns ns ns Residue (R) ns ns ns TxR ns ns ns Straw yield (t/ha) ST BP CT Mean LSD 0.05 Tillage (T) ns ns ns Residue (R) ns ns ns TxR ns ns ns 1 HR - high residue; LR - low residue, ST - strip tillage; BP - bed planting; CT - conventional tillage; 2 the least significant difference (LSD) at the P 0.05, ns - not significant, * - significant at P 0.05 and ** - significant at P Discussion Although there were some operational problems of VMP in implementing CA techniques initially (e.g. for wheat on BP in Year 2), yields of both lentil and wheat were comparable between ST and CT in the first two years. By the third year the yield advantage of both ST and BP over CT, and HR over LR, had become apparent, suggesting the feasibility of adopting CA practices in these rice-based cropping systems in Bangladesh. 73

122 2.4.1 Lentil In CT with LR, which is the current form of tillage and residue retention for lentil after rice, yields were ~1.8-2 t/ha and consistent across the three years, despite some differences in rainfall and temperature during those years. Such yields of lentil are consistent with levels achieved by researchers and leading farmers using recommended inputs for lentil. For example, the potential yield of lentil (BARI Masur 6) in Bangladesh is 2.25 t/ha (Uddin, 2008). Strip tillage with LR achieved comparable yields to CT with LR in Year 1, but levels dropped in Year 2 while in Year 3 they exceeded those of CT with LR. By contrast, ST along with HR achieved comparable yields to CT LR (the current practice) in Year 1 and 2 but in Year 3 significantly exceeded the conventional yield (2.5 vs 2 t/ha). Indeed the yield in ST HR increased progressively from 1.7 t/ha in Year 1 to 2 t/ha in Year 2 and 2.5 t/ha in Year 3. Hence, it was observed that the response to HR and ST was dynamic. It has been shown in the present study that the yield of lentil was comparable or higher under ST than under CT in the first year, by the third year after one year transition the yield advantage of both ST and BP; and HR over CT and LR. A study conducted in a loam soil at Grafton NSW, Australia by So et al. (2009) showed that the yield of soybean under NT system were less or equal during the first five years and outperformed compared to CT after one year transition in a 14 years soybean-oat rotation. However, Govaerts et al. (2005) reported that conversion from a conventional system to conservation systems requires several crop cycles before potential advantages become apparent. Also it was shown in the review of Giller et al. (2009) that the short-term effects of conservation tillage practices on crop yield could be variable (positive, negative or neutral). The depressed lentil yield under ST and LR in Year 2 may reflect a negative transitional phase between full tillage and minimum tillage, possibly associated with reduced mineralization of N, although as a legume, lentil growth should be relatively independent of soil mineral N supply (see Chapter 6 for further discussion of soil N dynamics). In Year 1, the lentil yield under BP was depressed relative to the current practice (i.e. CT with LR). This depressed yield was correlated with reduced number of branches/plant and pods/plant (see Tables 2.9 and 2.11) and with lower surface soil water (see Chapter 4). By Year 2, the yields were comparable across treatments and in 74

123 Year 3, BP with or without increased residue retention increased lentil yield relative to the current practice of CT and LR. Both Talukder et al. (2008) and Lauren et al. (2008) found that retention of crop residue significantly increased crop yields on permanent beds after only 1-2 cropping cycles in rice-wheat-maize and rice-wheat-mung cropping systems in Bangladesh. During the initial year, crop yields may be reduced due to the increased net N immobilization by microorganisms through decomposition of rice residue with high C:N ratio (Yadvinder-Singh. et al., 2004). However, the results of the present experiment for the second growing season showed no yield differences between BP and the current practice while in Year 3, BP out performed CT in yield. This corresponds with the timeframe for significant SOC and TN increases (see Chapters 5 and 6) which might be contributing to higher yield over time with ST and BP treatment in combination with HR. In the present study, HR significantly increased the yield of lentil in the second growing season while in third growing season the yield was not affected by residue management. In the second growing season after Crop 3, soil water content was greater with HR than LR which might contribute to a significant yield increase with HR in Crop 4 (see Chapter 4). A plausible reason for a positive effect of surface residue retention is the decrease in soil water loss through evaporation and increase in the amount of moisture stored in the root zone that is available to the plant (Govaerts et al., 2009). However in Year 3, regardless of treatments the higher stored soil moisture content at sowing and throughout the growing period may have negated the beneficial effects of residue retention on soil water availability. When the data were pooled across the three years, lentil yield was positively correlated with plant population. This suggests that part of the response to tillage and residue retention may be related to plant emergence and survival. Implementing ST and BP; and residue retention over the first two years of the study did not significantly affect plant population. Overall the plant population density was less in the first two years than in Year 3. However, the population density in the third growing season was satisfactory and influenced by tillage and residue. The higher plant population in the third growing season might be attributed to higher moisture availability at germination (see Chapter 4). A significantly higher plant population (20-25 %) was obtained in ST than CT in which might be due to better seed placement into moist soil with 75

124 machine sowing that increased emergence of lentil. In addition, better crop establishment due to high germination rates has been linked to proper placement of seed in the strip producing improved seed-soil contact. Licht and Al-Kaisi (2005a) also reported that strip tillage promoted corn (Zea mays L.) emergence in wet soils when compared to no-tillage and chisel plough. In addition, over time improvement of planter performance and operator skills with residue management for seeding in the rice-based system may have resulted in increased plant population under ST. Furthermore, improved soil physical properties could facilitate better plant emergence and survival under ST (see Chapters 3 and 4). Higher branching and podding of lentil in HR with BP and CT treatment from second growing season might be related to lower plant density (Table 2.9 and 2.11). Moosavi et al. (2014) similarly reported that the number of pods/plant decreased with increasing plant density of lentil. Moreover, Khourgami et al. (2012) recorded the higher number of branches/plant of lentil was obtained from lower plant density. In Year 1, yield components such as branches/plant and number of pods per plant were higher as a result of lower plant population in CT. The greater plant height and higher number of pods/plant might be contributed to increase yield of lentil under HR in Year 2 (Table 2.11 and Figure 2.3). During the growing season lentil plants were affected by foot and collar rot disease (Sclerotium rolfsii). Early in the third growing season, the seed zone of subsurface layers remained wet due to heavy rainfall for a few days but it resulted in foot and collar rot disease of lentil only in BP. This might be due to residue buried in the seeding zone and compaction of the soil surface layer on the top of beds by the bed shaper and pressing roller of the VMP: poor aeration favours Pythium disease incidence. Further the fungal pathogen might infect roots due to close contact of seed and residue in the seed zone of BP especially when the soil was wet. In addition, planting seeds of all crops in rotation in the same row on BP system may vulnerable to certain root diseases and their spread. Consequently, the mean plant population was decreased at harvest relative to emergence under BP with HR. However, finally the lower plant population did not decrease the yield due to recovery growth and compensation by other yield components in the BP treatment. Similarly, Govaerts et al. (2006a) observed higher root rot diseases in zero tillage with residue retention than in the traditional 76

125 agricultural system but disease did not depress crop yield of wheat or maize in wheatwheat and wheat-maize rotations. In summary, the higher seed yield of lentil under ST and BP; and HR retention compared to CT treatment in the third growing season can be attributed in part to higher plant population (Table 2.9). Further reasons for higher yield in the third growing season under ST and HR treatment might be due to greater soil water content (see Chapter 4), and increased organic carbon and nutrient levels (see Chapters 5 and 6) Wheat In the cereal-dominated system, overall the wheat yield in Year 1 was lower ( t/ha) than the potential yield t/ha (Bangladesh Agricultural Research Institute, 2014) due to sowing after the optimal time for Northwest Bangladesh. Delayed sowing of wheat after the optimum time (mid-november) results in 0.04 Mg/ha yield loss per day delay in the Indo-Gangetic Plains (Regmi et al., 2002). In the present trial, grain yields were not significantly affected by tillage and residue retention during the initial year. A similar result was found by Das et al. (2014) who reported that in Year 1 of the experiments, wheat grain yield was not affected by tillage and residue treatment in an irrigated cotton-wheat system. During the initial years of experimentation, Jat et al. (2014) also found poor grain yield of wheat under a permanent bed planting system in a rice-wheat rotation of the Eastern Gangetic Plains of South Asia. With timely planting in Year 2, the yield substantially increased under ST ( t/ha) and CT ( t/ha) but declined in BP ( t/ha), which was attributed to poor plant establishment and a lower plant population. The poor yield performance on BP in Year 2 was attributed to lack of experience of the VMP operator seeding on bed which resulted in shallow sowing depth of seeds on top of the bed where soils dried rapidly after sowing (especially with HR). Poor plant establishment limited plant population and thereby limited crop yield in BP. In Year 3, the overall yield was satisfactory ( t/ha) and greater yield ( t/ha) with ST and BP was probably due to sowing at the optimum time in moist soil. Wheat yields with ST and BP increased by 8-10 % over CT possibly because of efficient use of fertilizer and more effective weed control between the row 77

126 of ST and BP plot in Year 3. High residue increased yield by 3 % relative to LR in Year 3. Over time improvement of machine performance and operator skill in sowing seeds under such conditions may have improved the placement of seed in moist soil to improve seed germination. In the present study, it took three years to get the full benefits of ST and BP with high residue retention. After a transition period, wheat grain yields under ST and BP were significantly greater compared to CT in Year 3. Govaerts et al. (2005) reported that it could take some time (roughly 5 years) to get clear benefits but these conclusions are based on one crop per year grown in a low rainfall, low temperature and semi-arid environment while there were three crops per year grown in the present study under irrigation in a moderate to high temperature zone. However, Usman et al. (2010) showed from an experiment of tillage impacts on wheat yield under the rice-wheat system in western Pakistan that ZT and reduced tillage increased wheat yield over CT in the second year. Gangwar et al. (2006) also concluded that wheat yield in ST with residue retention was greater than CT and ZT with residue burning in sandy loam soils in a rice-wheat system in the IGP during the third year. In Year 1, although the overall plant population of wheat was not satisfactory, crops maintained similar plant density from sowing to harvest. In Year 2, overall the plant population was low in all treatments and unsatisfactory in BP. The lower plant population at BP was attributed to poor seed-soil contact as result of seeding on residue and insufficient soil moisture in the seeding zone for seed germination during crop establishment (moisture was not measured but visually observed in seeding zone of BP treatments). This lower plant population led to lower plant height and spikes/m² and finally contributed to depressed yield in BP in the second growing season. Jat et al. (2013) reported that fewer spikes of wheat under BP may lead to poor wheat performance compared to ST and CT. In case of BP, Yadvinder-Singh et al. (2009) also reported that soil moisture at the time of planting is a critical factor for determining tilth of beds on medium to fine-textured soils. With optimum moisture condition in the third growing season (see Chapter 4), plant establishment was better than in the previous two years. Most of the yield contributing characters in the third growing 78

127 season, namely plant height, effective tiller number, spike number, spike length and spikelets, were higher in ST and BP compared to CT. These important yield-related characters were positively correlated with the yield of wheat (Table 2.19). The greater plants/m², and increased spike/m² had positive linear relationships with grain yield of wheat (see Figure 2.6). High residue retention increased the straw yield of wheat from the first growing season and continued to do so in the succeeding years, which was associated with improved moisture availability with HR (see Figure 4.19, 4.21 in Chapter 4). However, the plant population of wheat dropped with HR in third growing season (Table 2.15). Perhaps the effects of denser mulching from rice residues impeded germination or crop establishment. In addition, heavy residue recycled from the previous six crops may hamper seed-soil contact. This suggestion is supported by Rieger et al. (2008) who reported that increased residue retention accounts for poor winter wheat (Triticum aestivum L.) crop establishment. In the third growing season, increased residue retention also increased grain yield of wheat. Significantly higher grains/spike and 1000-grain weight under HR retention might have accounted for higher grain yield of wheat (Kamkar et al., 2014). Prasad and Power (1991) reported that increased residue retention produced higher grain yield in a wide variety of crops. Crop residues generally improve soil moisture retention, SOC, N and other nutrient levels as they are a direct source of organic C and nutrients (Das et al., 2013). After three years, the improvement of soil physical properties (see Chapter 4) and the accumulation of SOC and TN levels (see Chapters 5 and 6) may be contributing to the increased yield of wheat with increased residue retention (see Chapters 5 and 6) Cropping system productivity In the legume-dominated system, although the yield of first rice crop (Crop 3) was not significantly affected by treatment, the yield of second mungbean (Crop 5) crop was greater under BP or CT. This might be attributed to the dry conditions and drying out of the soil which led to greater soil penetration resistance in the ST for mungbean at extreme dry conditions of summer. After two years, the yield of the second rice crop (Crop 6) in the system under ST and unpuddled transplanting was greater or similar to 79

128 CT (puddled) which might be attributed to improved soil conditions over time with minimal soil disturbance under ST (see Chapter 4, 5 and 6). In addition, this might be attributed to the soil not drying out with higher rainfall and better soil water content in the small cultivated area of ST. The findings of the present study of similar rice yield under unpuddled transplanted rice as compared to puddled transplanted rice for the initial years are in agreement with some findings in India (Bajpai & Tripathi, 2000). However, the poor yield of rice (Crop 6) under BP and unpuddled transplanting might be due to compaction and settling of bed soil as a result of submerged soils. In the cereal-dominated system, there were no yield differences of rice between puddled and unpuddled systems (see Table 2.20). By contrast, several authors reported lower yield of unpuddled rice as compared to puddled transplanted rice in the initial years (Kumar & Ladha, 2011; Jat et al., 2014). However, in both cereal- and legume-dominant rotations, the benefits of CA over the conventional system started to emerge from Crop 7 (third growing season), with the winter crop after rice. It has been demonstrated from the previous studies in the IGP that over time unpuddled transplanted rice followed by ST and BP to establish subsequent cool dry season crops alleviated puddling effects on soil and thereby favoring better plant establishment, root proliferation and increased crop ability to utilize sub-soil water, and nutrients that led to higher yield (Gangwar et al., 2006; Gathala et al., 2011b). Jat et al. (2014) concluded from seven years of a rice-wheat experiment in the Eastern IGP that the yield benefits of wheat under CA were immediate (from the first year) and the yield benefit of the cropping system began from the second year with an increasing trend over time though appreciable yield benefit of CA practices for rice crops after 3-4 years. In a study conducted by Adhikari et al. (2007) in the IGP of Nepal, the grain yield of rice in its second year was significantly affected by tillage, where ZT transplanted rice produced higher grain yield compared to full tillage. The trend of rice yield over two years and third year (Haque et al. 2016) in the present research; and the evidence from above mentioned studies in IGP suggests that unpuddled rice transplanting and ST and BP may also increase rice yield gradually and likely could be superior in the long run. 80

129 2.5 Conclusions This Chapter has evaluated the effects of CA practices (i.e. minimum or reduced tillage in the form of ST or BP, respectively, and high residue retention) relative to conventional practices (CT and LR) on crop yield performance during three years in intensive rice-based cropping systems in Northwest Bangladesh. In both legumedominated (lentil-mungbean-rice) and cereal-dominated (wheat-mungbean-rice) rotations on different soil types (calcareous alluvial and HBT, respectively), CA in intensive rice-based cropping sequences seems feasible. In the cool-dry season crops (lentil and wheat), yield under ST and BP was initially similar to CT in HBT and in alluvial areas, but by Crop 7, yields with ST and BP exceeded those with CT. These results suggest that ST and BP; and high residue can enhance crop yield of cool dry season crops in the intensive rice-based cropping systems but it takes 2-3 years (equivalent to 4-7 consecutive crops) before the yield benefit of CA practices can be clearly seen. The positive linear relationship between crop yield and plant population for both wheat and lentil suggested that the higher plant populations established with ST and BP; and HR contributed to higher yield. In the cereal-dominated system, the rice grain yields were equivalent in CA (ST and HR) and the conventional system (CT and LR). Although the mungbean yield was lower with ST, lentil yields were increased in ST while rice yield (Crop 3) was not significantly different to CT in legume-dominated system. However, the rice yield (Crop 6) was dropped in BP in legume-dominated system. Although CA techniques have started to show positive benefits on cool dry season crop after three years, ongoing studies are needed to confirm the long-term benefits that accrue from ST or BP and increased residue retention. Moreover, there is a need to understand the nature of the soil changes under ST or BP and HR that have contributed to increased crop yields. These are discussed in Chapters

130 3 Effects of tillage and residue management on soil strength, soil water and crop root growth in rice-based systems on silty loam soil in Bangladesh 3.1 Introduction Though puddling is commonly practiced for weed control, water retention and ease of transplanting for rice, the yield of the next crop after rice has been reported to decrease due to the deterioration of soil structure caused by puddling (Sharma et al., 2003; Mohanty et al., 2006). Adverse effects of puddling for rice on root growth of the following wheat crop have been shown (Kukal & Aggarwal, 2003a; Balwinder et al., 2011; Kumar & Ladha, 2011). Puddling results in breakdown of soil aggregates, destruction of macrospores, and formation of hard plough pan at shallow depths of soil (Gathala et al., 2011a). The soil strength of compacted soil layers below the puddled zone rapidly increases as the soil dries, and limits the depth of root exploitation in subsequent crops (International Rice Research Institute, 1986). As a result, drought may be induced in post-rice crops by restricting the root depth (Kukal & Aggarwal, 2003b). Sadras and Calvino (2001) calculated a 0.4 % wheat yield decline for each centimeter reduction of rooting depth. Components of conservation agriculture (CA) such as minimum tillage with residue retention have been recommended as a key measure to minimize the degradation of soil and increase water availability for crops (Huang et al., 2012; Bhatt et al., 2016). The CA systems may have advantages over conventional systems due to reduced soil disturbance and the protective effect of crop residues cover of the soil (Blanco-Canqui & Lal, 2009; Choudhury et al., 2014) and soil water conservation on dryland soils (Pittelkow et al. 2014). Further, CA improved the availability of soil water (Bescansa et al., 2006) and increased the number of soil biopores (Francis & Knight, 1993) that may facilitate root growth (Martino & Shaykewich, 1994). Wheat and lentil are contrasting crops commonly grown after rice in Northwest Bangladesh. The root systems of these crops may respond differently to the degraded 82

131 soil structure and the presence of plough pans in paddy fields. Conversely, they may respond differently to the short term and cumulative effects of minimum tillage and residue retention of previous crops in rice-based systems. There have been numerous studies on rice, maize and wheat root systems (Aggarwal et al., 2006; Martinez et al., 2008) but intensive study of legume root systems has been less common (Gregory, 1988), particularly on lentil root systems in relation to grain yield (Gahoonia et al., 2005). Ali et al. (2007b) studied the root systems of six different crops wheat, lentil, chickpea, barley, linseed and mustard after monsoon rice under water stress condition to identify alternative crops to deep rooting chickpea in the High Barind Tract of Bangladesh. They concluded that thin rooted barley is the most suitable alternative crop which could fit in this area due to its satisfactory yield and greater soil moisture extraction habit. However, to date, there has been no comprehensive study of the growth and distribution of crop root systems and their response to variation of soil penetration resistance (PR) and volumetric soil water content (%) (SWC) in rice-based systems under CA practices in Bangladesh. Two field experiments, described in Chapter 2, were used to examine the effects of different tillage and residue management on soil PR and water content and root distribution of the cool dry season crops, lentil and wheat. 3.2 Materials and method Two experiments were established in the rabi season (cool dry-winter season) during , and The lentil-mungbean-monsoon rice experiment was conducted at Alipur, Durgapur, Rajshahi and the wheat-mungbean-monsoon rice experiment at HBT, Digram, Rajshahi. Weather and site details were described in Chapter Treatment details Details of the treatments were described in Chapter 2. Briefly, tillage treatments consisted of strip tillage (ST), bed planting (BP) for non-rice crop, and unpuddled transplanting for the rice crop; and puddled transplanting for rice crop and 83

132 conventional tillage (CT) for the non-rice crop; and there were two levels of residue: high residue (HR) and low residue (LR) retention Measurement of soil water content and penetration resistance One day before root sampling, the SWC was measured with a MP406 capacitance sensor (ICT International, Armidale, NSW) at three random spots in each plot at 5 cm increments to 15 cm. After measuring SWC of surface 5 cm soil depth excavated to the surface 5 cm soil and measured the next depth (5-10 cm) and afterwards cm soil depth. At the same time, the soil PR was measured with a field hand-held penetrometer (Eijkelkamp, the Netherlands) at five random locations in each plot at 5 cm increments to 15 cm. Based on soil strength, cone number 1 (diameter: mm; base area: 1 cm²) or 2 (diameter: mm; base area: 2 cm²) of the penetrometer were used and calculated soil PR as per manual of Eijkelkamp penetrometer. The measurements of SWC and PR were in the tilled strip (IS) as well as the inter-row space between the strips or off the strip (OS) of ST, in the furrow and on centre of the bed for BP and between the plants in the CT plot Root sampling of lentil Five randomly pre-selected plants were sampled for root distribution at flower initiation [first year ( ) at days after sowing (DAS), second year ( ) at DAS and third year ( ) at DAS]. Soil was sampled under representative sections of plant rows from ST and BP plots and representative sections of plants under CT. Samples taken from a corner of each plot in order to minimize the soil disturbance of rest of the plot. Shoots were detached from the collar region of the plant and above-ground biomass was determined. Blocks of soil, 15 cm long (along the row) and 20 cm wide (across the row) was excavated manually. In Year 1, only one block was sampled down the soil profile at 0-15 cm as roots could not be found below cm soil depth. As roots were found up to cm in the succeeding two years, two blocks per plot were sampled down the soil profile at 0-10 and cm. The dimensions of each block were 15 x 20 x 15 cm³ in the first year and 15 x 20 x 10 cm³ in the following two years. Therefore, all the root and shoot characters of lentil were calculated and presented considering 300 cm² surface area. Extracted soil was soaked 84

133 in water in plastic buckets for 2 to 3 hours. The slurry was washed over a fine sieve (0.5 mm) and roots were collected by hand with the non-root material and organic debris picked out or washed off carefully, and the selected root mass was stored in a refrigerator until further assessment. The shoot and root samples were oven dried at 72 C for three days (until constant weight) to determine the shoot and root dry weight Nodulation of lentil For all the study years, nodulation was assessed just prior to flowering or at first flowering. For nodulation ranking, eight representative plants were selected per plot. In , the nodulation was ranked on a 0-5 scale based on the crown and effective nodules (pink colour nodule) following the procedure of (Rupela, 1990). However, this ranking system was found to be too insensitive for lentil nodulation rating therefore in and , the total as well as effective nodule (pink coloration inside) numbers/plant was counted separately. The average nodule ranking, nodule and effective nodule numbers of 5 randomly selected plants in each plot were counted. Also fresh weight and dry weight of 1000-effective nodule were measured in Root sampling of wheat Five randomly pre-selected plants were sampled for root distribution at booting to heading stage (at DAS) in the first year ( ) and at grain filling stage in the following two years [at DAS in second year ( ) and DAS in third year ( )]. The first year results on root development patterns suggested that some information might be missing when sampling at DAS (booting stage). Thus samplings were done at the maturity stage to get correct estimates of root growth of wheat in the final two years. Soil was sampled under representative sections of plant rows of ST and BP plots; and a representative section of plants of CT. Above-ground biomass was carefully excised at the soil surface. A block of soil was 10 cm deep, 20 cm long (along the row) and 20 cm wide (across the row) were excavated manually. Based on rooting depth, the digging continued to a depth of 40 cm in 10 cm increments in the first year, to a depth of 50 cm and 70 cm in the second year and third year. The 85

134 dimensions of each block were 20 x 20 x 10 cm³. Therefore, all the root and shoot characters of wheat were calculated and presented considering 400 cm² surface area. All other operations were performed as for lentil Measurement of root parameters Root volume (RV) was recorded by water displacement from a volumetric cylinder and root dry weights were recorded after oven drying at 70 C to a constant weight. Root length was measured by grid method of Newman (1966) modified by Tennant (1975). The root length was calculated as follows: Root length = 11/14 x number of intercepts x grid unit (cm) Root length density (RLD, root length/soil volume) and specific root length (SRL, root length/oven dry weight) were calculated for each sample. The above-ground shoots were dried in an oven at 70 C to a constant weight. The root to shoot ratio was calculated by dividing the total weight of roots by that of shoots Statistical analysis Data on SWC, PR, root volume, root length, RLD, root dry weight and SRL were analysed separately for lentil and wheat each year using GenStat 15th Edition (VSN International Ltd, United Kingdom). Mean values were calculated for each set of measurements, and analysis of variance (ANOVA) for split-plot design was performed to assess treatment effects on the measured variables. On an average ~80-90 % roots were confined to top 10 cm soil profile and the remaining ~10-20 % to cm for lentil and cm for wheat. Tillage was assigned in main-plots and residue retention levels in sub-plots while soil depth for the measurement of SWC and soil PR in sub-sub plots. Root for each depth were analysed separately for assessing root growth under tillage and residue retention. When the F-test was significant, treatment means were separated by least significant difference (LSD) at P A correlation matrix of different properties was based on Pearson correlation coefficients (P 0.01 and P 0.05). 86

135 3.3 Results Soil physical properties during root assessment of lentil at Alipur Volumetric soil water content Volumetric soil water content (SWC) was significantly affected by tillage, depth and the interaction of tillage and depth in (Figure 3.1a1). The SWC increased with increasing soil depth. The greater SWC was measured with CT and the lower SWC was in BP at all soil depths (0-5 cm, 5-10 cm and cm). In , the SWC was higher in BP and the lower SWC in ST at surface soil layer (0-5 cm) (Figure 3.1a2). Retention of high residue conserved higher SWC than low residue retention at all soil depths. In , the SWC was significantly affected by tillage, residue, depth and the interaction of tillage and depth (Figure 3.1a3). High residue retention increased SWC as compared to low residue retention. The SWC was significantly lower under CT than under ST and BP at all soil depths. 87

136 Volumetric soil water content (%) Soil penetration resistance (MPa) a1) ST-HR ST-LR BP-HR BP-LR CT-HR CT-LR Tillage Depth Tillage x Depth ST-HR b1) Tillage ST-LR BP-HR BP-LR CT-HR CT-LR Residue Depth Tillage x Depth HR LR HR LR HR LR a2) cm 5-10 cm cm Residue Tillage x Depth HR LR HR LR HR LR b2) cm 5-10 cm TillageX Depth cm Tillage Residue Depth HR LR HR LR HR LR a3) cm 5-10 cm cm Residue Depth TillageX Depth HR LR HR LR HR LR b3) cm 5-10 cm cm Tillage Residue Depth TillageX Depth HR LR HR LR HR LR 0-5 cm 5-10 cm cm Treatment 0.0 HR LR HR LR HR LR 0-5 cm 5-10 cm cm Treatment Figure 3.1. Tillage and residue effects on mean volumetric soil water content (%) (a1- a3) and mean penetration resistance (MPa) (b1-b3) at three soil depths (0-5 cm, 5-10 cm and cm) at Alipur during to The floating error bars indicate the average least significant difference (LSD) at P 0.05 for significant treatment and depth difference Soil penetration resistance In , soil PR was significantly affected by tillage, residue, depth and the interaction of tillage and depth (Figure 3.1b1). Regardless of treatments, PR increased with increasing soil depth but retention of high residue decreased PR. The lowest PR was in BP and the highest PR was in CT at all the study depths (0-5 cm, 5-10 cm and 10-88

137 15 cm). In , the soil PR was significantly affected by tillage, residue, depth and the interaction of tillage and depth (Figure 3.1b2). Irrespective of treatments, soil PR increased with increasing soil depth but retention of high residue again decreased soil PR. In BP, though there was no significant tillage effect on PR at 0-5 cm, it was lower at 5-10 cm and cm soil depths. In , the soil PR was significantly affected by tillage, residue, depth and the interaction of tillage and depth (Figure 3.1b3). Regardless of treatment, PR increased with increasing soil depth but retention of high residue decreased PR. Penetration resistance was not significantly affected by tillage in the surface layer (0-5 cm depth) but was lowest at 5-10 cm and cm depths Root characteristics of lentil In , the important rooting characteristics namely root volume and root length were greater at 0-15 cm soil depth with BP as compared to CT (Figure 3.2a and Figure 3.2c); and HR enhanced root volume and RLD relative to LR (Figure 3.2a and Figure 3.2d). However, the RDW, SRL, shoot weight and root shoot ratio in the first growing season was not significantly affected by different treatments. 89

138 Soil depth (cm) a) 0-15 cm Root volume (cm³) in ST-HR ST-LR BP-HR BP-LR CT-HR CT-LR at 0-15 cm T ns ; R**; TxR** b) Root dry wt. (g) in cm c) at 0-15 cm T ns ; R ns ; TxR ns Root length (m) in cm at 0-15 cm T * ; R ns ; TxR ns d) RLD (cm/cm 3 ) in cm e) SRL (m/g) in at 0-15 cm T ns ; R*; TxR ns cm Figure 3.2. Tillage and residue effects on lentil root distribution at 0-15 cm soil depth during the growing season. Root parameters measured are a) Root volume (cm³), b) Root dry weight (g), c) Root length (m), d) Root length density-rld (cm/cm³) and e) Specific root length-srl (m/g). Error bars indicate ± 1 standard error of the mean. at 0-15 cm T ns ; R ns ; TxR ns 90

139 Soil depth (cm) In , the root volume, root dry weight, RLD and root length at 0-10 cm depth were not affected by tillage; and compare to LR, root growth was higher with HR treatment (Figure 3.3a-d). At cm depth, greater root volume, root dry weight, root length and RLD were obtained in BP while the lowest was in CT (Figure 3.3a-d). a) Root volume (cm 3 ) in ST-HR 0-10 cm ST-LR BP-HR BP-LR CT-HR cm CT-LR at 0-10 cm T ns ; R**; TxR ns at cm T*; R ns ; TxR ns b) Root dry wt.(g) in cm cm at 0-10 cm T ns ; R*; TxR ns at cm T**; R ns ; TxR ns c) Root length (m) in cm cm at 0-10 cm T ns ; R**; TxR ns at cm T*; R ns ; TxR ns d) RLD (cm/cm 3 ) in cm cm at 0-10 cm T ns ; R**; TxR ns at cm T*; R ns ; TxR ns e) SRL (m/g) in cm at 0-20 cm T ns ; R ns ; TxR ns Figure 3.3. Tillage and residue effects on lentil root distribution at 0-10 cm and cm soil depth during the growing season. Root parameters measured are a) Root volume (cm³), b) Root dry weight (g), c) Root length (m), d) Root length density- RLD (cm/cm³) and e) Specific root length-srl (m/g). Error bars indicate ± 1 standard error of the mean. 91

140 Soil depth (cm) In , significantly higher root volume, root dry weight, root length, and RLD were measured in the surface layer (0-10 cm depth) under BP and HR relative to CT and LR, respectively (Figure 3.4a-d). At cm depth, the greater root volume, root dry weight, root length, and RLD were measured under BP than other tillage treatments. Below 10 cm soil depth, residue effects had disappeared (Figure 3.4a-d). a) 0-10 cm cm Root volume (cm 3 ) in ST-HR ST-LR BP-HR BP-LR CT-HR CT-LR b) at 0-10 cm T ** ; R**; TxR ns at cm T**; R ns ; TxR ns Root dry wt. (g) in cm cm c) at 0-10 cm T ** ; R**; TxR ns at cm T**; R ns ; TxR ns Root length (m) in cm cm at 0-10 cm T**; R**; TxR** at cm T**; R ns ; TxR ns d) RLD (cm/cm 3 ) in cm cm at 0-10 cm T**; R**; TxR** at cm T**; R ns ; TxR ns e) SRL (m/g) in cm cm at 0-10 cm T ns ; R**; TxR* Figure 3.4. Tillage and residue effects on lentil root distribution at 0-10 cm and cm soil depth during the growing season. Root parameters measured are a) 92 at cm T ns ; R ns ; TxR ns

141 Root volume (cm³), b) Root dry weight (g), c) Root length (m), d) Root length density- RLD (cm/cm³) and e) Specific root length-srl (m/g). Error bars indicate ± 1 standard error of the mean Root and shoot growth and their ratio for lentil The total root dry weights in and were greater with HR compare to LR. In , the root dry weight was higher under BP relative to that under other tillage treatments (Table 3.1). Although treatment differences in shoot growth and root to shoot ratio were not significant in the first two years, HR enhanced shoot growth and root to shoot ratio in BP relative to ST in (Table 3.1). Table 3.1. Total root dry weight, shoot dry weight and root to shoot ratio (g/g) of five lentil plants under different tillage and residue management at Alipur. Tillage treatment 1 HR 1 LR 1 Mean HR LR Mean HR LR Mean Root dry wt. (g/0.03 m²) ST BP CT Mean LSD Tillage (T) ns ns 0.095** Residue (R) ns 0.085* 0.041** T x R ns ns ns Shoot dry wt. (g/0.03 m²) ST BP CT Mean LSD 0.05 Tillage (T) ns ns ns Residue (R) ns ns 0.24** T x R ns ns ns Root to shoot ratio (g/g) ST BP CT

142 Mean LSD 0.05 Tillage (T) ns ns 0.041* Residue (R) ns ns ns T x R ns ns ns 1 HR - high residue; LR - low residue, ST - strip tillage; BP - bed planting; CT - conventional tillage; 2 the least significant difference (LSD) at the P 0.05, ns - not significant, * - significant at P 0.05 and ** - significant at P Nodulation of lentil In , there was no significant effect of treatment on nodule scores (Table 3.2). In , total and effective nodule numbers were higher in CT and BP, but significantly lower numbers in ST. Retention of high residue increased the total nodule number (Table 3.2). 94

143 Table 3.2.Tillage and residue effects on nodulation of lentil in legume-dominated rice-based system. Tillage Residue treatment 1 Mean Residue treatment 1 Mean treatment 1 HR LR HR LR Nodule score/plant ST BP CT Mean LSD 0.05 Tillage (T) ns Residue (R) ns T x R ns Total nodule number/plant Effective nodule number/plant ST BP CT Mean LSD 0.05 Tillage (T) 39.0* 10.3* Residue (R) 22.4** ns T x R ns ns Total nodule number/plant Effective nodule number/plant ST BP CT Mean LSD 0.05 Tillage (T) 15.7** 8.3** Residue (R) 11.7* 5.4* T x R ns ns 1 HR - high residue; LR - low residue, ST - strip tillage; BP - bed planting; CT - conventional tillage; 2 the least significant difference (LSD) at the P 0.05, ns - not significant, * - significant at P 0.05 and ** - significant at P

144 Volumetric soil water content (%) Soil penetration resistance (MPa) In , significantly higher total and effective nodule numbers were found in BP than the other tillage treatments (Table 3.2). Compared to LR, higher numbers of total and effective nodules were found with HR Soil physical properties during root assessment of wheat at Digram Volumetric soil water content In , irrespective of treatments, the SWC increased with increasing soil depth (Figure 3.5a1). The SWC at 0-5 cm was lower in BP than in other tillage treatments. However, the SWC contents at 5-10 cm and cm depths were lower with CT than ST and BP a1) ST-HR ST-LR BP-HR BP-LR CT-HR CT-LR Depth TillageX Depth ST-HR b1) Tillage ST-LR BP-HR BP-LR CT-HR CT-LR Depth HR LR HR LR HR LR a2) cm 5-10 cm cm Tillage Depth Tillage x Depth HR LR HR LR HR LR b2) TillageX Depth 0-5 cm 5-10 cm cm Tillage Residue Depth HR LR HR LR HR LR a3) cm 5-10 cm cm Residue Depth TillageX Depth HR LR HR LR HR LR b3) cm 5-10 cm cm Tillage Residue Depth HR LR HR LR HR LR 0-5 cm 5-10 cm cm Treatment HR LR HR LR HR LR 0-5 cm 5-10 cm cm Treatment Figure 3.5. Tillage and residue effects on mean volumetric soil water content (%) (a1- a3) and mean penetration resistance (MPa) (b1-b3) at three soil depths (0-5 cm, 5-10 cm and cm) at Digram during to The floating error bars 96

145 indicate the average least significant difference (LSD) at P 0.05 for significant treatment and depth difference. In , the SWC was significantly affected by tillage, depth and the interaction of tillage and depth (Figure 3.5a2). Irrespective of treatments, the SWC increased with increasing soil depth. The SWC at all depths were higher in BP than in other tillage treatments (Figure 3.5a2). In , regardless of treatments, the SWC increased with increasing soil depth and HR conserved higher SWC than LR (Figure 3.5a3). In BP, the SWC at 0-5 cm depth was lower while it was greater at cm depth (Figure 3.5a3) Soil penetration resistance The soil PR increased with soil depth irrespective of treatments in all the study years (Figure 3.5b1-b3). In , soil PR was significantly affected by tillage and depth (Figure 3.5b1). Soil PR at 0-10 cm depth was lower under BP while it was greater under CT. In , regardless of treatments, soil PR decreased with HR. As compared to CT, soil PR was lower in BP at all depths (0-5, 5-10 and cm). In , CT had significantly higher soil PR while BP had lower soil PR at 0-5 cm and 5-10 cm depths (Figure 3.5b3). High residue retention significantly decreased soil PR compared to LR. Below 10 cm depth, the soil was too hard to measure the soil PR (Figure 3.5b3) Root characteristics of wheat In , the root volume, root dry weight, root length, RLD and SRL at all soil depths (0-10 cm, cm, cm, cm and cm) were not affected either by tillage or residue (Figure 3.6a-e). The root growth gradually decreased with increasing soil depth across all tillage and residue treatments. About 80 % of root length and mass was found in 0-10 cm depth and remaining 20 % at cm depth (Figure 3.6c). 97

146 Soil depth (cm) a) Root volume (cm 3 ) in cm cm cm cm ST-HR ST-LR BP-HR BP-LR CT-HR CT-LR b) cm at 0-50 cm (10 cm increments of five soil depths) T ns ; R ns ; TxR ns Root dry wt (g) in cm cm cm cm c) cm at 0-50 cm (10 cm increments of five soil depths) T ns ; R ns ; TxR ns Root length (m) in cm cm cm d) cm cm 0-10 cm at 0-50 cm (10 cm increments of five soil depths) T ns ; R ns ; TxR ns RLD (cm/cm 3 ) in cm cm cm e) cm 0-10 cm at 0-50 cm (10 cm increments of five soil depths) T ns ; R ns ; TxR ns SRL (m/g) in cm cm cm cm at 0-50 cm (10 cm increments of five soil depths) T ns ; R ns ; TxR ns Figure 3.6. Tillage and residue effects on wheat root distribution at 0-50 cm soil depth (10 cm increments of five soil depths) during the growing season. Root parameters measured are a) Root volume (cm 3 ), b) Root dry weight (g), c) Root length (m), d) Root length density-rld (cm/cm 3 ) and e) Specific root length-srl (m/g). Error bars indicate ± 1 standard error of the mean. 98

147 In , the root volume, root dry weight, root length and RLD at 0-10 cm depth were greater with BP than other tillage treatments (Figure 3.7a-d). Compared with LR, HR significantly increased root volume, root dry weight, root length and RLD (Figure 3.7a-d). At cm depth, BP enhanced root growth by increasing all root parameters compared to other tillage treatments (Figure 3.7a-d). Regardless of treatments, root growth gradually decreased with increasing soil depth and the treatment effect on root growth disappeared below 20 cm depth. About 80 % of wheat roots were recorded in top 10 cm of soil (Figure 3.7a-d). 99

148 Soil depth (cm) a) b) 0-10 cm cm cm cm cm cm 0-10 cm Root volume (cm 3 ) in at 0-10 cm T**; R**; TxR ns at cm T**; R ns ; TxR ns ST-HR ST-LR BP-HR BP-LR CT-HR CT-LR at cm (10 cm increments of five soil depths) T ns ; R ns ; TxR ns Root dry wt. (g) in cm cm cm c) cm 0-10 cm at 0-10 cm T**; R**; TxR ns at cm T**; R ns ; TxR ns Root length (m) in at cm (10 cm increments of five soil depths) T ns ; R ns ; TxR ns cm cm cm d) cm cm 0-10 cm at 0-10 cm T**; R**; TxR ns at cm T**; R ns ; TxR ns at cm (10 cm increments of five soil depths) T ns ; R ns ; TxR ns RLD (cm/cm 3 ) in cm cm cm e) cm cm 0-10 cm at 0-10 cm T**; R**; TxR ns at cm T**; R ns ; TxR ns SRL (m/g) in at cm(10 cm increments of five soil depths) T ns ; R ns ; TxR ns cm cm cm cm at 0-50 cm except cm (10 cm increments of five soil depths) T ns ; R ns ; TxR ns Figure 3.7. Tillage and residue effects on wheat root distribution at 0-60 cm soil depth (10 cm increments of six soil depths) during the growing season. Root parameters measured are a) Root volume (cm 3 ), b) Root dry weight (g), c) Root length (m), d) Root length density-rld (cm/cm 3 ) and e) Specific root length-srl (m/g). Error bars indicate ± 1 standard error of the mean. 100 at cm T*; R ns ; TxR ns

149 In , all root parameters of wheat at 0-10 cm depth were greater in BP than other tillage treatments (Figure 3.8a-d). High residue retention significantly increased all root parameters of wheat at 0-10 cm depth (Figure 3.8a-d). At cm depth, all root parameters were greater with BP than in other tillage treatments but root growth beyond 10 cm depth was not influenced by different residue levels (Figure 3.8a-d). Treatment effects below 20 cm soil depth were not significant. Regardless of treatments, root growth gradually decreased with increasing soil depth: as in previous years, about 80 % of root growth was limited to the top 10 cm depth (Figure 3.8a-d). 101

150 Soil depth (cm) a) b) 0-10 cm cm cm cm cm cm cm 0-10 cm Root volume (cm 3 ) in at 0-10 cm T*; R*; TXR ns at cm T**; R ns ; TxR ns Root dry wt. (g) in ST-HR ST-LR BP-HR BP-LR CT-HR CT-LR at cm(10 cm increments of five soil depths) T ns ; R ns ; TxR ns cm cm cm c) cm cm 0-10 cm cm at 0-10 cm T*; R*; TxR ns at cm T**; R ns ; TxR ns Root length (m) in at cm (10 cm increments of five soil depths) T ns ; R ns ; TxR ns cm cm cm d) cm cm 0-10 cm cm cm cm cm at 0-10 cm T**; R**; TxR ns at cm T**; R ns ; TxR ns RLD (cm/cm 3 ) in at cm(10 cm increments of five soil depths) T ns ; R ns ; TxR ns e) cm cm 0-10 cm at 0-10 cm T*; R**; TxR ns at cm T**; R ns ; TxR ns SRL (m/g) in at cm(10 cm increments of five soil depths) T ns ; R ns ; TxR ns cm cm cm cm at 0-10 cm T ns ; R ns ; TxR ns at cm T ns ; R ns ; TxR ns Figure 3.8. Tillage and residue effects on wheat root distribution at 0-70 cm soil depth (10 cm increments of seven soil depths) during the growing season. Root parameters measured are a) Root volume (cm 3 ), b) Root dry weight (g), c) Root length (m), d) Root length density-rld (cm/cm 3 ) and e) Specific root length-srl (m/g). Error bars indicate ± 1 standard error of the mean. 102 at cm(10 cm increments of five soil depths) T ns ; R ns ; TxR ns

151 3.3.7 Root and shoot growth, and their ratio of wheat Neither root nor shoot weight nor their ratio was significantly affected by treatments in (Table 3.3). However, in , the root and shoot weights were greater with BP than other tillage treatments. Further, HR increased root weight, shoot weight and root to shoot ratio as compared to LR treatment (Table 3.3). In , the root dry weight was greater in BP than in other tillage treatments, with HR increased root dry weight compared to LR (Table 3.3). Table 3.3. Total root dry weight, shoot dry weight and root to shoot ratio (g/g) of five wheat plants under different tillage and residue management at Digram. Tillage treatment 1 HR LR Mean HR LR Mean HR LR Mean Root dry wt.(g/0.04 m²) ST BP CT Mean LSD Tillage (T) ns 0.13** 0.29** Residue (R) ns 0.23** 0.17** T x R ns ns ns Shoot dry wt. (g/0.04 m²) ST BP CT Mean LSD 0.05 Tillage (T) ns 8.8** ns Residue (R) ns 7.7* ns T x R ns ns ns Root to shoot ratio (g/g) ST BP CT Mean LSD 0.05 Tillage (T) ns ns ns Residue (R) ns * ns 103

152 T x R ns ns ns 1 HR - high residue; LR - low residue, ST - strip tillage; BP - bed planting; CT - conventional tillage; 2 the least significant difference (LSD) at the P 0.05, ns - not significant, * - significant at P 0.05 and ** - significant at P Discussion The changes of SWC and soil PR due to tillage and residue at the time of root assessment and their potential connection with root growth are presented in the current Chapter. However, the detailed effects of tillage and residue on SWC and soil PR, and other important soil physical properties, throughout the cropping cycle are presented in Chapter Soil penetration resistance and soil water content The soil PR was reduced (P 0.05) by BP and HR throughout the study at all depths measured. The similar findings of lower values of soil PR in different soil layers of effective root zone (0-50 cm) under permanent BP and ZT compared to CT were also reported by Parihar et al. (2016). The decrease in soil PR under BP could be attributed to the construction of beds by heaping of pulverized top soil (in Year 1) and confining wheel traffic to the furrow of the bed. Naresh et al. (2014a) also found the lowest soil PR in BP compared to CT and ZT. Reduced soil PR also became apparent in the treatment with unpuddled rice followed by ST with HR for the non-rice crop. In the rainfed legume-dominated site, the soil PR with unpuddled rice followed by ST with HR decreased by % at 5-15 cm depth and in the irrigated cereal-dominated site by % at 0-10 cm depth, compared to puddled rice followed by CT with LR. These results are consistent with those of Singh et al. (2016) and Saha et al. (2010), who reported that soil PR decreased under ZT compared to CT at 0-15 cm and cm depths. The findings of the present study indicated that over time unpuddled rice and ST with HR gradually improved soil physical properties such as increasing SWC and lowering soil PR while diminishing existed plough pan as a consequence of puddled rice cultivation. However, in case of the cereal-dominated system the soil PR of the surface soil was also lower in ST. By 104

153 contrast in CT, repeated tillage and puddling contributed to increased soil compaction and thereby enhanced soil PR (Kukal & Aggarwal, 2003b; Parihar et al., 2016). Retention of HR decreased the soil PR compared to LR and soil PR increased with increasing soil depth throughout the years at all soil depths in the present study. Similar results were reported by Singh et al. (2016), who found that residue retention reduced soil PR compared to removal of rice and maize residue. They also found that the soil PR increased with increasing soil depth. Over time retention of HR gradually decreased soil PR which should facilitate improved root growth over LR. Rahman et al. (2005) and Chakraborty et al. (2008) also found that residue retention decreased soil PR and thereby increased root growth. In the present study, the SWC decreased in BP more than in ST and CT at Alipur, a rainfed legume-dominated zone in Year 1. The raised and pulverized soil of the new bed might have caused this. The SWCs however were not significantly different at Digram, an irrigated site, except in Year 2. Probably equal amount of irrigation application and greater transpiration during vegetative stage of wheat resulted in nonsignificant differences in SWC due to tillage at Digram. In Year 2, the SWC was significantly higher for BP compared to ST and CT at all depths. The reduced uptake of soil water by the lower plant population in Year 2 (see table 2.15 in Chapter 2) might have contributed to this. The higher SWC also could promote root growth of existing wheat plant in BP. In Year 3, with increasing soil depth, the SWC increased in ST and BP while it decreased in CT. The greater SWC at deeper soil profile of ST and BP might be associated with improved infiltration rate with time. The improvement of soil aggregate stability with time and preservation of water conducting pores as a result of minimal soil disturbance increased the infiltration rate in soil under ZT and with residue retention (Dwivedi et al., 2012; Singh et al., 2016). Further, residue retention on ST and BP protected the surface soil from evaporation and increased the infiltration rate. By contrast, constant rice puddling and intensive tillage for cultivation of dryland crop disrupted soil structure and thereby decreased infiltration rate under CT, consistent with observations by Singh et al. (2016). In addition to lower infiltration rate, high evaporation as a result of bare and pulverized soil led to decreased SWC in 105

154 CT. Several researchers of India also reported that the infiltration rate increased with ZT and residue retention than with CT and residue removal (Gathala et al., 2011b; Jat et al., 2013). The SWC was higher under HR compared to LR in progressive years, probably due to the protection from evaporation and increased infiltration rate Root distribution as affected by tillage and residue over time Both legume- and cereal-dominated trials were carried out in silty loam soil with low levels of soil organic carbon (SOC) (0.61 % at Alipur and % at Digram) (see Chapter 2) compared to a good agricultural soil (~1.16 % SOC) (Bangladesh Agricultural Research Council, 2012). Puddling is used for rice cultivation followed by intensive tillage for the establishment of succeeding cool dry season crops in both areas. Silty loam soils are prone to soil physical changes due to puddling for rice cultivation (Hobbs et al., 1994) which can impair root growth of cool dry season crops after rice. All the given measurements of roots such as root volume, RDW, root length, RLD and SRL were similarly affected by tillage and residue. However, most commonly RLD is used to measure root distribution in the soil profile (Qin et al., 2004; Chopart et al., 2008). Hence the following discussion focuses on RLD. Root growth of lentil and wheat in the surface soil (0-10 and cm) was highest in BP and with HR throughout the study. Although there were no clear differences between ST and CT at surface 10 cm depth in all years, the root growth at cm depth in ST started to increase over CT from the Year 2 onwards. The raised bed planting system offers a favorable condition for root growth. Initial tillage operations to form the bed loosen the soil and reduce the soil PR. The present results are in good agreement with other studies (Aggarwal et al., 2006; Hossain et al., 2008; Singh et al., 2013), which also found higher root growth in bed planting systems. Over time (after three years) accumulation of high residue in BP and ST systems increased SWC and decreased PR through induced cracks and bio-pores (old root channels) in the undisturbed mid-row space of beds and thus favoured better root growth in BP and ST than CT. Singh et al. (2014b) and Bonfil et al. (1999) reported that the improved balance between micro- and macro-porosity and residue retention under ZT accounted 106

155 for better root growth of wheat over CT. In the present study, BP and HR also provided a favourable environment for better nodule formation in roots compared to other treatments. A favourable rhizosphere environment enhanced nodulation in BP (Kumar et al., 2015). Pramanik et al. (2009) reported that better drainage and quick re-aeration of the root zone after irrigation under BP increased nodulation. Nodule formation is sensitive to unfavourable soil moisture condition (Kulathunga et al., 2008). In the current study, higher SWC in BP with HR may explain the increased nodulation. Likewise, the lower soil BD or PR in BP with HR also might be conducive to greater nodulation, consistent with observations by Aggarwal and Goswami (2003). However, in the present study, root sampling in BP was only at the centre of the bed, which is equivalent to 62 % area of bed planting plot, while there was no sampling in the remaining % of the furrow portion of the BP plot. This sampling bias may influence the results of root growth in BP. The explanation of root sampling method could able to clear the above statement. During sampling soil for the assessment of root growth, a sample block of soil was selected with the surface dimensions 15 cm long (along the row) X 20 cm wide (across the row) X 10 cm deep for lentil and 20 cm long (along the row) X 20 cm (across the row) X 10 cm deep wide for wheat for all treatments. Sample block was collected from the middle of inter-row to the middle of the next inter-row (20 cm wide) for ST. In case of BP system, row spacing was 20 cm at the centre of the bed and sampling location was 10 cm in either direction from one of the rows (Figure 4.3). Since bed is trapezoidal with 30 cm wide at the bed top, hence it was 15 cm (from the middle of inter-row to the edge of the bed) of 20 cm sampling wide on bed top. There was remaining 5 cm from edge of the bed to slope of the bed, which was covered by some part of furrow (of 0-5 cm furrow). However, the total furrow of the BP was not considered for the assessment of root growth which led to biased sampling in favour of BP system. However, by scaling the value of root growth to the furrow dimensions of the bed (55 cm furrow-furrow distance) or to one hectare, the root growth of BP system likely to be equal or even less than other treatments. Since the root growth of furrow was not counted in the present study, hence the root growth was not scaled to 107

156 the furrow dimensions of the bed and only presented the root growth on BP which is biased. The RLD was similar in CT and ST in Years 1 and 2, however higher RLD was found in ST than CT in Year 3. The reason behind the increase of RLD in ST after three years might be due to the improvement of SOC as a result of greater deposition of higher organic input in ST (see Chapter 5 for SOC results). The restricted root growth at depth was associated with a pre-existing plough pan. In the experimental field, farmers had regularly cultivated puddled monsoon rice followed by intensive tillage with residue removal for two other dryland crops. Over time implementation of unpuddled rice followed by ST for cool dry season crop together with HR tended to decrease the hard pan, as reflected by lower soil PR at cm depth (Table 3.1) and at 5-10 cm depth (Table 3.6) and thereby enhanced root growth in Year 3. However, both BP and ST systems took three years to overcome the detrimental effects of puddling and rigorous tillage practices of the non-rice crop. After three years, the RLD improved significantly compared to the first two years. These results are consistent with those of Pearson et al. (1991) who reported that tillage effects on root growth of wheat was less or similar in the first three years, however the growth was greater in successive years under minimum tillage compared to CT Rooting patterns of wheat and lentil Lentil and wheat have contrasting root systems that may result in varied responses to tillage and residue retention. The root system of lentil consists of a slender tap root with a mass of fibrous lateral roots at shallow depth (Saxena, 2009). The root system of wheat is fibrous, denser and penetrates deeper than that of lentil. Although root growth of lentil extended up to 20 cm depth, ~90 % of roots were concentrated in the surface 10 cm depth. The root growth of lentil and wheat below 20 cm depth was not significantly different under different tillage and residue treatments. Though the root growth of wheat reached 70 cm depth, ~80-90 % roots were distributed in the top 10 cm profile. The distribution of lentil roots at 0-10 cm and cm depths due to tillage treatments was significantly different (P<0.01) both in Years 2 and 3. In Year 2, about 90 % lentil roots in ST, 89 % in BP and 95 % in CT were restricted to the surface 10 cm of soil. In Year 3, there were 86 % of roots in ST and 90 % in BP while 92 % of 108

157 lentil roots were confined to the surface 10 cm in CT. Like lentil, the vertical rooting depth of wheat roots was in the following order: ST>BP>CT. The results of the vertical distribution of root under different tillage treatments suggested that least roots were distributed in the deeper soil profile under CT. Greater root growth deeper in the soil profile under ST and BP may allow greater extraction of water and nutrients from a greater soil volume. Similar results have been reported by Singh et al. (2014b) who found maximum wheat roots (about 96 %) in the surface 0-15 cm depth with CT compared to 87 % with ZT in a rice-wheat system of the IGP Root distribution related to soil water content and penetration resistance The RLD was associated with the changes of soil PR and SWC due to different tillage and residue treatments in all years. The soil PR might be the major influential factor for enhancing root growth of cool dry season crops after rice in the current study. The critical values of soil PR that limits root growth for most of the field crops is 2-3 MPa (Aggarwal et al., 2006). During root assessment in Year 1 in the rainfed legumedominated system, the SWC and PR in BP were significantly (P 0.05) lower than those in CT and ST at all soil depths (0-5, 5-10 and cm). Repeated loosening of surface soil on centre of the bed and the greater accumulation of SOC (see Chapter 5) and N (see Chapter 6) was associated with a decreased soil PR at top of the BP in Year 2 and Year 3. The increased SWC under HR resulted in decreased soil PR in Year 3 as compared to LR. Retention of HR on the soil surface led to greater accumulation of SOC and total soil N (see Chapters 5 and 6) and improvement of soil physical condition such as increased SWC and decreased soil PR in Year 3. This favourable condition under HR possibly led to improvement in root growth and thus increased yield of lentil and wheat in Year 3 (see Chapter 2). Similarly in the North China Plain, Mu et al. (2016) also found that crop residue retention compared to residue removal resulted in improvement of SWC and N status, and reduction in soil PR, leading to increased root mass density and crop yield. 109

158 3.4.5 Above-ground shoot growth and yield influenced by rooting patterns Although the root growth under ST and BP, with HR, was significantly greater compared to CT and LR, the shoot growth was only higher in later years with BP and HR. The better root growth deeper in the soil profile under ST was not associated with shoot growth, however gradual improvement of root growth in ST increased yield in Year 3 (see Chapter 2). The shoot growth is largely controlled by other limiting factors such as differences in plant density, and other limitations on shoot growth that may have masked the root response. For example, Busscher and Bauer (2003) and Moreno et al. (1996) reported that root growth was reduced without affecting shoot growth and yield in compacted soil. Guan et al. (2014) found that root growth was reduced in compacted soil without affecting water and nutrient uptake. 3.5 Conclusion The results of the three year s study of these rice-based systems demonstrated that over time improvement of root growth of cool dry season crops under ST and HR might be associated with the gradual improvement of soil physical properties such as soil PR and SWC. Further, over time unpuddled rice and ST with high residue cover gradually reduced sub-soil compaction and improved SWC which enhanced root growth at deeper soil profile compared to CT and LR. Hence, establishing rice by transplanting into unpuddled soil resulted in positive effects on root growth of subsequent cool dry season crops at deeper soil layers. The gradual improvement of soil physical properties and root growth in the deeper soil profile probably resulted in increased crop yield. In contrast, existing hard pan beneath the tilled layer at cm soil depth as a result of consistent use of puddling rice cultivation followed by CT restricted the root growth relative to ST. In the current study, there was better root growth in BP compared to other treatments. This is probably associated with the root sampling only on the bed top where loosened top soil was heaped thereby enhancing root growth. The bed top has a unique opportunity to enhance root growth through the loosening and pulverizing of soil in the seeding zone from the beginning of the experiment. However, increased 110

159 shoot growth in BP was not associated with improved root growth, probably other limiting factors controlled shoot growth in the present study. Although the results of these experiments are from an initial three years study, further improvements of root growth with CA-based management, especially unpuddled rice followed by ST with HR, are possible through ongoing changes in soil physical properties, SOC and N. In this study, although the tillage and residue effects on root growth of lentil and wheat disappeared beyond 20 cm soil depth, greater relative root growth occurred in the deeper soil profile under ST which could facilitate greater absorption of nutrients and water from the larger volume of soil profile. Therefore, more detailed assessment of maximum rooting depth is important for assessing the benefits of minimum tillage and increased residue on cool dry season crops in the long term (~5-6 years) in rice-based systems on silty loam soils. Also, further long-term experiments in rice-based system under different soil and environment conditions are needed to evaluate the performance of ST and BP, and retention of HR, on root growth of cool dry season crops following rice. 111

160 4 Effects of tillage and residue management on soil physical properties in rice-based cropping systems in Bangladesh 4.1 Introduction In Chapter 3, root growth of cool-dry season crops (lentil and wheat) under different tillage and residue treatments was related to soil penetration resistance (PR), bulk density (BD) and soil water content (SWC). The root growth data and related soil physical properties such as the soil PR and SWC were assessed only at one growth stage, near flowering. In brief, the main findings were as follows. The soil PR was lower in BP and with HR compared to ST and CT, and with LR treatments at all depths of measurement. The soil PR in Crop 7 clearly declined in ST and HR relative to CT and LR, which suggests an improvement of soil structure and a weakening of the plough pan over time under ST and HR treatment. Similarly by Crop 7, the SWC increased with increasing soil depth with ST and BP, and with HR compared to CT and LR, likely due to the improvement of infiltration rate and reduce evaporation under ST and BP, and HR. The objective of the present Chapter was to investigate the temporal effects of different tillage and residue management on several soil physical properties during lentil and wheat crops within the two rice-based cropping systems. 4.2 Materials and methods Treatments and crop management Complete details of treatments and crop management procedure are given in Chapter 2. Briefly, tillage treatments consisted of strip tillage (ST), bed planting (BP) and conventional tillage (CT) with two levels of residue applied high (HR) and low residue (LR) retained. The two rice-based cropping systems were studied during the cropping seasons of , and , viz. lentil-mungbean-monsoon rice at Alipur, Durgapur, Rajshahi and wheat-mungbean-monsoon rice at HBT, Digram, Godagari, Rajshahi. Site and weather details are described in Chapter 2. During rice establishment, soil was puddled in CT while unpuddled transplanting of rice (Haque et 112

161 al., 2016) was followed in ST and BP. In the cropping sequence, the crop numbers 1, 4 and 7 were lentil or wheat (winter crop), the crop numbers 2 and 5 were mungbean and the crop numbers 3 and 6 were monsoon rice Soil bulk density Soil bulk density at 0-5, 5-10 and cm layers was determined using soil cores (Black & Hartge, 1986). Briefly, three spots identified randomly per plot and then the samples for each depth taken one above the other. The sample of BD were taken once before crop sowing and again after harvest of cool dry season crops using a stainless steel core sampler of volume 61.8 cm³. The soil BD was collected from: in between the rows and in the rows of ST plots; at centre of the bed and in the furrow of BP; and between the plants of the CT plots. In order to compare seed bed or field condition under different treatments, ST average value of in the strip (IS) and off the strip (OS) were compared with centre of the bed and CT treatment in the present study. However, the difference between OS vs IS and centre of the bed vs furrow of the bed were also examined. The collected soil cores were trimmed to the exact volume of the cylinder. Each soil core sample sealed in the aluminum box, weighed wet and then dried in an oven at 110 C for about 72 hours until constant weight; and then reweighed to determine the gravimetric SWC and the mass of dry soil per unit volume of soil core to calculate the BD Soil temperature Soil temperature was measured using Maxim s i-button temperature sensors (Haight, 2009). For each site, six i-buttons (one for each treatment) were used for only Replication-2. The soil temperature of the experimental site was most likely to be homogenous for as the soils under a soil series are characterized by homogenous number and kinds of soil horizons that have similar characteristics (Huq & Shoaib, 2013). Hence, the representative data from one replication was considered to be sufficient to understand the treatment effects. Soil temperatures were recorded continuously throughout the third growing season of the cool dry season crop, from planting to harvesting, at two hours intervals at 5 cm soil depth. Temperature was 113

162 measured in between the plant row at center of the bed in BP, in the inter-row space of ST and between the plants in CT plot Volumetric soil water content Calibration of MP406 soil water probe meter for Alipur and Digram A MP406 soil water probe (θprobe) (ICT international, Australia) was used to measure the volumetric SWC. The SWC was measured at three random spots across the plot at 5 cm soil depth increments to 15 cm at both sites. The MP406 measures the soil dielectric constant by frequency domain reflectometry (Vance 2013). The regression equations for each site are: Alipur, y = 1.49x- 25.2, r² = 0.58 Digram, y = 0.80x+2.01, r² = Gravimetrically calculated Volumetric water content (%) MP406 Volumetric water content (%) Figure 4.1. Relationship between volumetric water content (SWC) (%) (calculated from the gravimetric soil water content) and MP406 volumetric water content (θprobe) (%) for the data collected at 5 cm increments down the soil profile collected after 7 crops at Alipur (, ) and Digram (, ) in The soil profile depth was to 15 cm. Symbols are data points and the line represents the regression equation shown above. The dielectric constant is shown in millivolts (mv), and converted to SWC using an inbuilt calibration. The gravimetric soil water contents were converted to SWC using BD 114

163 (Cresswell & Hamilton, 2002). The pairs of data (n =72) comprising calculated SWC and volumetric soil water content from the MP406 (θprobe) were used to construct calibration curves, specific to the Alipur and Digram soils (Figure 4.1) Soil penetration resistance At the same time as volumetric soil water content (%) (SWC) measurement, soil PR was measured with a field hand-held penetrometer (Eijkelkamp, the Netherlands). Five measurements per plot were made at each depth (5 cm increments to 15 cm) for computing the average soil PR. Based on soil strength, cone number 1 (diameter: mm; base area: 1 cm²) or 2 (diameter: mm; base area: 2 cm²) of the penetrometer were used and calculated soil PR as per manual of Eijkelkamp penetrometer. In the ST treatment, the measurements of soil BD, SWC and soil PR were in the tilled strip (IS) as well as the inter-row space between the strip or off the strip (OS) of ST (Figure 4.2). Measurements were between the plants in the CT plot and in the furrow and on centre of the bed of BP (Figure 4.3). Figure 4.2. Schematic diagram of strip tillage plot showing the location of measurements of soil water content and penetration resistance in between the strips (closed black circle) and in the strip (open black circle) in a strip-tillage plot. 115

164 4.2.6 Sampling time and location The SWC, soil PR and soil BD samples were collected every year at the end of the rice season (when the soil was nearly at field capacity condition) and again after harvest of the winter crop (lentil/wheat) during , and These measurements were also taken before starting of the experiment in 2010 as baseline information and after the first, third, fourth, sixth and seventh cropping seasons in the sequence (after lentil/wheat and rice). The SWC and soil PR was measured at dry condition after the dryland crop (Crop 1 and 4). After the rice crop (Initial, Crop 3 and 6), the wet soil was drained until it reached field capacity before the measurement of SWC and soil PR. After Crop 7, the soil was pre-wetted, and then drained until it reached field capacity before taking SWC and PR measurements. Also the trend of SWC and soil PR after planting of winter crops lentil and wheat, were measured at five days interval until 35 days after sowing (DAS) in the third growing season. In order to compare seed bed conditions under different treatments, average values of in the strip (IS) and off the strip (OS) for ST were compared with centre of the bed and CT. However, the comparisons between OS (off-the strip) and IS (in the strip); and between BT (from the bed top) and BF (from the level of the bed top in the furrow) of the bed planting (BP) system were also examined. In case of BP system, soil samples were taken at 5 cm increments to a depth of 15 cm considering the bed top as 0 (zero) cm when sampling in either bed or furrow. Thus there was no value of 0-5 cm increment sampled in the furrow as the furrow is 5 cm deep. Mention that since the formation of bed, the bed height and furrow depth lessened over time after all crops and it is noteworthy after rice crop. Finally after rice and non-rice crop when the soil was settled on bed, the actual depth of furrow was about 5 cm from the level of the bed top. Therefore, the top level of furrow from the level of the bed top was considered as 0-5 cm depth, which is gap. The above procedures in relation to sampling location of ST and BP also followed for the measurement of soil carbon concentrations (see Chapter 5) and soil total nitrogen concentrations (see Chapter 6). 116

165 Figure 4.3. Schematic diagram of the newly formed bed. The blue circles indicates the sampling spot of centre of the bed (closed symbol) and furrow of the bed (open symbol) for soil moisture, soil penetration resistance and bulk density measurements Statistical analysis Data were analysed separately for lentil and wheat each year using GenStat 15th Edition. Mean values were calculated for each set of measurements at each depth, and analysis of variance (ANOVA) for a split-plot (main plot: tillage and sub-plot: residue) and split-split-plot (main plot: tillage, sub-plot: residue and sub-sub-plot: cropping cycle) were employed to assess treatment effects on the measured variables. When the F-test was significant, treatment means were separated by least significant difference (LSD) at P Results The main effects of tillage and residue levels on SWC, soil BD and PR are presented in this chapter. As the interaction effects of tillage and residue on SWC, soil PR and BD were not significant for most of the times of measurement, the significant interaction effects of tillage and residue are presented Alipur 117

166 Soil bulk density Tillage effects The soil BD was measured at three different depths (0-5 cm, 5-10 cm and cm) at different times during the study period including initial (before starting of the experiment), after rice (after Crop 3 and 6) and after the non-rice winter crop (after Crop 1, 4 and 7) (Figure 4.4). Across all sampling dates, the soil BD increased with increasing soil depth (Figure 4.4). The tillage impact on soil BD at 0-5 cm depth became apparent after Crops 4 and 6. The soil BD of ST (1.36 g/cc) and CT (1.37 g/cc) were significantly lower than that of BP (1.45 g/cc) after Crop 4. After Crop 6, the BD of ST (1.37 g/cc) was significantly lower than that of CT and BP (1.44 g/cc). At 5-10 cm soil depth, ST and CT (1.52 g/cc) had greater BD than BP (1.48 g/cc). At cm soil depth, the soil BD of ST (1.71, 1.76, 1.64 and 1.64 g/cc) and CT (1.76, 1.74, 1.64 and 1.65 g/cc) were significantly higher than that of BP (1.64, 1.61, 1.55 and 1.54 g/cc) after Crop 1, 3, 6 and 7, respectively (Figure 4.4). At 0-5 cm soil depth, the interaction of tillage and cropping cycles on BD was significant (P 0.05, LSD 0.039), whilst it was not significant at 5-10 cm and cm soil depth (Figure 4.4). At 0-5 cm soil depth, the soil BD of ST and BP (1.36 g/cc) was lower after Crop 7 than the initial BD value (1.54 g/cc). However, the soil BD of BP treatment fluctuated between formation of the new bed (initial), the permanent bed (after rice, after Crop 3 and 6) and after reshaping of the bed (after Crop 4 and 7) (Figure 4.4). 118

167 Bulk density (g/cc) cm ST BP CT 1.65 T X CC T T Initial 1 After 2 1 C 3 After 43 C After 5 4 C After 6 6 C After 7 7 C cm Cropping Cycle T cm T T T T Initial 1 After 2 1 C 3 After 43 C After 5 4 C After 6 6 C After 7 7 C 8 Cropping Cycle Figure 4.4. Tillage effects on soil bulk density over cropping cycles-initially and after Crops 1, 3, 4, 6 and 7 at 0-5 cm, 5-10 cm and cm soil depths in Alipur. Values are means across residue levels. The error bars for each data point represents ± 1 standard error. The floating error bars on the figure at each depth represent the least significant difference (LSD) at P 0.05 for tillage after each crop (T) and interaction between tillage and cropping cycle (TXCC) Residue effects At 0-5 cm soil depth, the soil BD under HR (1.43, 1.41 and 1.35 g/cc) was lower than under LR (1.45, 1.43 and 1.38 g/cc) after Crop 3, 6 and 7, respectively (Figure 4.5). At 5-119

168 Bulk density (g/cc) 10 cm soil depth, the soil BD under HR (1.50 g/cc) was lower than under LR (1.52 g/cc) only after Crop 7. At cm soil depth, residue effects on soil BD were not apparent across all treatments after all crops (Figure 4.5) cm HR LR Initial 1 After 2 1 C 3 After 4 3 C After 5 4 C After 6 6 C After 7 7 C cm Cropping Cycle Initial 1 After 2 1 C 3 After 4 3 C After 5 4 C After 6 6 C After 7 7 C cm HR LR Cropping Cycle Initial 1 After 21 C 3 After 4 3 C After 5 4 C After 6 6 C After 7 7 C 8 Cropping Cycle Figure 4.5. Residue effects on soil bulk density after different cropping cycles initially and after Crops 1, 3, 4, 6 and 7 at 0-5 cm, 5-10 cm and cm soil depths in Alipur. Values are means across tillage treatments. The error bars for each data point represents ± 1 standard error. The floating error bars on the figure at each depth represent the least significant difference (LSD) at P 0.05 for residue after each crop. 120

169 The interaction effects of tillage and residue management were not significant across all depth of measurements except at cm soil depth (Table 4.1). Table 4.1. Soil bulk density (g/cc) at three different depths (0-5 cm, 5-10 cm and cm) under tillage and residue after different crop in legume-dominated system in Alipur. Tillage 1 Residue 1 Cropping cycles LSD Initial After Crop 1 After Crop 3 After Crop 4 After Crop 6 After Crop 7 Tillage (T) Residue (R) TXR Soil depth (0-5 cm) ST HR LR BP HR LR ns 0.01** ns CT HR LR Soil depth (5-10 cm) ST HR LR BP HR LR ns ns ns CT HR LR Soil depth (10-15 cm) ST HR LR BP HR ** ns 0.1* 1.70 LR CT HR LR HR - high residue; LR - low residue, ST - strip tillage; BP - bed planting; CT - conventional tillage; 2 the least significant difference (LSD) at the P 0.05, ns - not significant, * - significant at P 0.05 and ** - significant at P After Crop 1 and 3, the soil BD was higher with ST and CT ( g/cc) and lower with BP after Crop 4, 6 and 7 ( g/cc) (Table 4.1). 121

170 Volumetric soil water content and penetration resistance Tillage effects The effects of tillage on soil water content (SWC) and penetration resistance (PR) after different crops are presented in Figure 4.6. The SWC was not affected due to tillage after Crop 3 to 6 at 0-5 cm soil depth and from Crop 1 to 4 at 5-10 cm and cm soil depth (Figure 4.6). After Crop 1, the SWC at 0-5 cm soil depth of BP (11.1 %) was significantly (P 0.05) lower than that of CT (13.6 %) and ST (13.2 %) (Figure 4.6). Similarly, the SWC at 0-5 cm soil depth of BP (33.9 %) was significantly (P 0.05) lower than that of CT (35.7 %) and ST (34.6 %) after Crop 7 (Figure 4.6). By contrast, the SWC at 5-10 cm soil depth of BP (33 and 34 %) was higher than that of ST (31 and 33 %) and CT (32 and 33 %) after Crop 6 and 7, respectively (Figure 4.6). Similarly, the SWC at cm soil depth of BP (31.7 % and 33.8 %) was higher than that of CT (29.2 and 31.5 %) and ST (29.0 and 32.3 %) after Crop 6 and 7, respectively (Figure 4.6). After Crop 1, the soil PR at 0-5 cm soil depth of BP (1.2 MPa) was significantly (P 0.05) lower than that of CT (2.9 MPa) and ST (2.4 MPa) (Figure 4.6). After Crop 7, however the soil PR at 0-5 cm soil depth of BP (0.46 MPa) and CT (0.45 MPa) were significantly (P 0.05) lower than that of ST (0.51 MPa) (Figure 4.6). At 5-10 cm soil depth, the soil PR of BP (3.1, 0.7 and 1.0 MPa) was lower than that of CT (7.0, 1.2 and 1.3 MPa) and ST (5.1, 1.3 and 1.3 MPa) after Crop 1, 6 and 7, respectively (Figure 4.6). Similarly, the soil PRs measured at cm depth were 1.9 and 1.8 MPa in BP, which was significantly (P 0.05) lower than 2.5 and 2.4 MPa in CT and 2.4 and 2.1 MPa in ST after Crop 6 and 7, respectively (Figure 4.6). 122

171 Volumetric soil water content (%) Soil penetration resistance (MPa) cm ST BP CT cm ST BP CT After Crop 1 After Crop 3 After Crop 4 After Crop cm 0 10 After Crop 1 After Crop 3 After Crop 4 After Crop 6 After Crop cm After Crop 1 After Crop 3 After Crop 4 After Crop 6 After Crop cm 0 10 After Crop 1 After Crop 3 After Crop 4 After Crop 6 After Crop cm After Crop 1 C 1 After Crop 3 C 3 After Crop 4 C 4 After Crop 6 C 6 After Crop 7 C 7 Cropping Cycle 0 After Crop 1 C 1 After Crop 3 C 3 After Crop 4 C 4 After Crop 6 C 6 After Crop 7 C 7 Cropping cycle Figure 4.6. Dynamic changes of volumetric soil water content (%) and penetration resistance (MPa) due to tillage after Crops 1, 3, 4, 6 and 7 at 0-5 cm, 5-10 cm and cm soil depths in Alipur. Values are means across residue levels. Error bars were ± 1 standard error of the mean and floating bar indicates significant difference at P 0.05 level between treatments on that time of measurement Residue effects The effects of residue on SWC and soil PR after different crops are presented in Figure 4.7. The SWC at 0-5 cm soil depth was 36.9, 36.1 and 35.0 % in HR treatments which were significantly (P 0.05) higher than 35.7, 35.3 and 34.5 % in LR treatments after 123

172 Volumetric soil water content (%) Soil penetration resistance (MPa) Crop 1, 6 and 7, respectively (Figure 4.7). The SWC at 5-10 cm soil and cm soil depth with HR (14.7 and 18.0 %) was greater compared to LR (12.7 and 16.2 %) after Crop 4 (Figure 4.7). The soil PR at 0-5 cm soil depth of HR (0.5, 4.5, 0.4 MPa) was lower than that of LR (0.6, 5.3 and 0.5 MPa) after Crop 3, 4 and 7, respectively (Figure 4.7). At 5-10 cm soil depth, the soil PR under HR (7.0 and 1.1 MPa) was lower than under LR (8.0 and 1.2 MPa) after Crop 4 and 7, respectively (Figure 4.7). The soil was too dry to insert the penetrometer at cm soil depth, hence the measurement of soil PR were not taken after Crop 1 and 4 (Figure 4.7). However, the soil PR with HR was lower (2.0 MPa) as compared to LR (2.2 MPa) after Crop 7 at cm soil depth (Figure 4.7) cm HR LR cm HR LR cm After Crop 1 After Crop 3 After Crop 4 After Crop 6 After Crop cm After Crop 1 After Crop 3 After Crop 4 After Crop 6 After Crop cm After Crop 1 After Crop 3 After Crop 4 After Crop 6 After Crop cm After Crop 1 After Crop 3 After Crop 4 After Crop 6 After Crop After Crop 1 C1 After Crop 3 C3 After Crop 4 C4 After Crop 6 C6 After Crop 7 C7 Cropping Cycle Figure 4.7. Dynamic changes of volumetric soil water content (%) and penetration resistance (MPa) due to residue after Crops 1, 3, 4, 6 and 7 at 0-5 cm, 5-10 cm and After Crop 1 C1 After Crop 3 C3 After After Crop 4 C4 After After Crop 6 C6 After After Crop 7 C 7 Cropping cycle

173 15 cm soil depths in Digram. Values are means across tillage treatments. Error bars were ± 1 standard error of the mean and floating error bars indicate significant difference at P 0.05 level between treatments on that time of measurement Trends of volumetric soil water content and penetration resistance following planting of lentil Tillage effects Across all treatments, the SWC continued to decrease and soil PR increase at all depths of measurement from sowing to 35 DAS in Crop 7 (Figure 4.8a1-a3 and Figure 4.8b1- b3). The BP and ST had significantly higher surface SWC (0-5 cm) than that of CT at all depths of measurement (Figure 4.8a1). At 5-10 cm depth, there was no effect of tillage treatments on SWC except at 35 DAS, which was the last reading taken. The SWC of BP (24 %) and ST (25 %) were significantly (P 0.01) lower than that of CT (26 %) at 35 DAS (Figure 4.8a2). At cm soil depth, the SWC of BP and ST (30 %) was significantly higher than that of CT (29 %) at 5 DAS and 10 DAS (Figure 4.8a3). After 10 DAS when cm soil depth was monitored, no differences of SWC were seen for tillage treatments (Figure 4.8a3). The soil PR values at 0-5 cm soil depth of different tillage types followed the order of ST = BP>CT while the order was CT>ST>BP at 5-10 cm and cm soil depths (Figure 4.8b1-b3). The soil PR of CT (1.3, 1.3 and 1.6 MPa) was lower compared to BP (1.5, 1.5 and 1.8 MPa) and ST (1.6, 1.6 and 1.8 MPa) at 20, 25 and 30 DAS, respectively at surface soil (0-5 cm depth) (Figure 4.8b1). However, the soil PR was consistently and significantly greater with CT while lower with ST and BP in all days of measurement at 5-10 cm and cm soil depth (Figure 4.8b2-b3). 125

174 Volumetric soil water content (%) Soil penetration resistance (MPa) 40 a1) 0-5 cm ST BP CT 6.0 b1) 0-5 cm ST BP CT a2) 5-10 cm b2) 5-10 cm a3) cm b3) cm Days after sowing Days after sowing Figure 4.8. The volumetric soil water content (%) (a1-a3) and soil penetration resistance (b1-b3) at 0-5 cm, 5-10 cm and cm soil depths for different tillage treatments at 5 days after sowing (DAS) to 35 DAS during lentil planting in 2013 in Alipur. Values are means across residue levels. Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of tillage on that dates of measurement and error bars indicate ± 1 standard error of the mean Residue effects Following sowing of lentil (Crop 7), the SWC continued to decrease while soil PR increase irrespective of tillage treatments (Figure 4.9). The SWC of HR was consistently and significantly greater than that of LR at 0-5 cm soil depth at all dates of 126

175 Volumetric soil water content (%) Soil penetration resistance (MPa) measurement except at 35 DAS (Figure 4.9a1). Similarly, the SWC at 5-10 cm soil depth under HR was significantly greater than under LR at all dates of measurement except at 30 and 35 DAS (Figure 4.9a2). At cm soil depth, the SWC under HR was also greater compared to SWC under LR only at 5, 20, 30 and 35 DAS but treatment differences were absent for all other measurements (Figure 4.9a3). At 0-5 and 5-10 cm soil depth, the soil PR under HR was significantly lower than under LR at all dates of measurement except at 35 DAS (Figure 4.9b1 and b2). Similarly, at cm soil depth, except at 10 DAS, the soil PR under HR was significantly lower than under LR at all dates of measurement (Figure 4.9b3). 40 a1) 0-5 cm HR LR 6.0 b1) 0-5 cm HR LR a2) 5-10 cm b2) 5-10 cm a3) cm b3) cm Days after sowing Days after sowing Figure 4.9. The volumetric soil water content (%) (a1-a3) and soil penetration resistance (b1-b3) at 0-5 cm, 5-10 cm and cm soil depths for different residue treatments at 5 days after sowing (DAS) to 35 DAS during lentil planting in 2013 in 127

176 Alipur. Values are means across tillage treatments. Floating error bars indicate the Penetration resistance (MPa) least significant difference (LSD) at P 0.05, for the effects of tillage on that date of measurement and error bars indicates ± 1 standard error of the mean Relationship between soil physical properties Relation between soil bulk density and penetration resistance The soil PR increased with an increase in soil BD after all crops in Alipur (Figure 4.10ae.). Penetration resistance (MPa) Penetration resistance (MPa) Penetration resistance (MPa) a) y = 13.67x R² = c) Bulk density (g/cc) y = 12.72x R² = e) Bulk density (g/cc) y = 6.05x R² = 0.88 Penetration resistance (MPa) b) y = 6.11x R² = d) Bulk density (g/cc) y = 5.40x R² = Bulk density (g/cc) Bulk density (g/cc) Figure Relationship between soil penetration resistance (MPa) and bulk density (g/cc) after different crop determined: a) after Crop 1; b) after Crop 3; c) after Crop 4; 128

177 d) after Crop 6; e) after Crop 7 during in Alipur. Values are for all three depths (0-5 cm, 5-10 cm and cm). The line represents the regression equation shown above in the graph Depth distribution of soil physical parameters at bed planting and strip tillage system in Alipur Distribution of soil bulk density The soil BD was not significantly different due to the sampling position from bed top (BT) and from the level of the bed top in the furrow (BF) of the BP except at 5-10 cm soil depth, where the soil BD of BT was higher than that of BF (Figure 4.11a). Bulk density (g/cc) a) BT vs BF Initial BT BF Bulk density (g/cc) b) Initial OS IS OS vs IS cm 5-10 cm cm cm 5-10 cm cm Sampling position and depth Sampling position and depth Figure 4.11.Variation of soil bulk density after Crop 7 in Alipur relative to depth from the bed top (BT) and from the level of the bed top in the furrow (BF) of the bed planting system (a); and in the strip (IS) and off-the strip (OS) of strip tillage system (b). For comparison, initial values (before starting the experiment) are also shown. Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of sampling positions. The soil BD was not significantly different between measurements taken in the strip (IS) and off-the strip (OS) except at cm soil depth, where the IS value was higher than that of OS of ST (Figure 4.11b). 129

178 Distribution of volumetric soil water content After Crop 7, the variation of SWC found similar between BT and BF at all depths of study (Figure 4.12a). The SWC for IS and OS in the ST exhibited significant difference only in the depth of 5-10 cm, where the SWC of OS was higher than IS (Figure 4.12b). Volumetric soil water content (%) a) Initial BT BF 0-5 cm 5-10 cm cm Volumetric soil water content (%) b) OS vs IS Initial OS IS 0-5 cm 5-10 cm cm Sampling position and depth Sampling position and depth Figure Variation of volumetric soil water content (%) after Crop 7 in Alipur relative to depth from the bed top (BT) and from the level of the bed top in the furrow (BF) of the bed planting system (a); and in the strip (IS) and off-the strip (OS) of strip tillage system (b). For comparison, initial values (before starting the experiment) are also shown. Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of sampling positions Distribution of soil penetration resistance Regardless of treatment, the soil PR increased with increasing soil depth for all measurements (Figure 4.13a and 4.13b). The soil PR of BT was higher than that of BF in 5-10 cm and cm soil depths (Figure 4.13a). The differences of soil PR due to sampling position of ST were not significant in 0-5 cm and cm soil depths. The soil PR of OS was significantly lower than that of IS in the 5-10 cm depth (Figure 4.13b). 130

179 Soil penetration resistance (MPa) a) Initial BT BF BT vs BF BT vs BF 0-5 cm 5-10 cm cm Soil penetration resistance (MPa) b) OS vs IS Initial OS IS 0-5 cm 5-10 cm cm Sampling position and depth Sampling position and depth Figure 4.13.Variation of soil penetration resistance (MPa) after Crop 7 in Alipur relative to depth from the bed top (BT) and from the level of the bed top in the furrow (BF) of the bed planting system (a); and in the strip (IS) and off-the strip (OS) of strip tillage system (b). For comparison, initial values (before starting the experiment) are also shown. Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of sampling positions Soil temperature at Alipur The trend in soil temperature with time at 0-5 cm soil depth was little affected by tillage and residue management during the lentil season in (Figure 4.14a and 4.14b). Generally, the soil temperature decreased with days after sowing irrespective of treatments and minimum values were measured at DAS during both day and night (Figure 4.14a and 4.14b). Afterwards, the temperatures tended to rise and reached a peak at DAS, the end of measurement. The maximum soil temperature at day and minimum at night varied between 25.8 and 24.0 C and 12.6 to 13.7 C, respectively. The day soil temperature was generally higher in CT and BPLR and lower in BPHR than other treatments at all dates of measurement except at and DAS (Figure 4.14a). When the temperature was monitored at and DAS, the maximum soil temperature was recorded in STLR. Afterwards when the atmospheric temperature started to warm the soil temperature remained lower with STHR up to 127 DAS (Figure 4.14a). However, the maximum (23.3 C) and 131

180 minimum night soil temperature (13.7 C) of BPLR was higher at all dates of measurement. While the night soil temperature of BPLR was higher than other treatments from beginning to 103 DAS (Figure 4.14b). When the soil temperature reached at peak across all treatments at DAS (19.9 C) and DAS (22.3 C), the lowest soil temperatures were recorded from STHR treatment (19.9 C and 22.3 C) compared to other treatments (Figure 4.14b). 30 ST HR BP HR CT HR Day temperature ( C) 25 ST LR BP LR CT LR Mean soil temperature ( C) a) 25 b) Night temperature ( C) Days after sowing Days after sowing Figure The variation of mean soil day (a) and night soil temperature ( C) (b) due to different treatments during wheat growing season at Alipur in Values are means of seven day intervals. 132

181 4.3.2 Digram Soil bulk density at different depth Tillage effects The soil BD increased with increasing soil depth across all sampling dates (Figure 4.15). The tillage impact on soil BD became visible after Crop 1 and tillage effects were significantly different after Crop 1, 4 and 6 at 0-5 cm depth (Figure 4.15). At 0-5 cm soil depth, the soil BD of ST (1.36 g/cc) was significantly lower than that of CT (1.43 g/cc) and BP (1.40 g/cc) after Crop 1. The soil BD of ST (1.23 g/cc) was significantly lower than that of BP (1.35 g/cc) and CT (1.29 g/cc) after Crop 4. After Crop 6, the soil BD of ST (1.23 g/cc) was significantly lower than that of BP (1.29 g/cc) and CT (1.30 g/cc) (Figure 4.15). At 5-10 cm depth, the soil BD (1.46 and 1.36 g/cc) of BP was lower than CT (1.51 and 1.42 g/cc) and ST (1.50 and 1.40 g/cc) after Crop 1 and 6, respectively (Figure 4.15). At cm soil depth, the soil BD of BP (1.57, 1.51, 1.46 and 1.43 g/cc) was significantly (P 0.05) lower than the BD of CT (1.69, 1.59, 1.59 and 1.59 g/cc) and ST (1.63, 1.60, 1.58 and 1.54 g/cc) (Figure 4.15). The interaction between tillage and cropping cycles on soil BD was significant at 0-5 cm soil depth (P 0.05, LSD 0.029) and at cm soil depth (P 0.05, LSD 0.065) (Figure 4.15). At 0-5 cm soil depth, the soil BD of ST was lowest after Crop 6 (1.23 g/cc) while the highest soil BD was measured after Crop 1 with CT (1.43 g/cc). At cm soil depth, the lowest soil BD was measured in BP (1.43 g/cc) after Crop 6 and the highest BD measured after Crop 1 in CT (1.69 g/cc) (Figure 4.15). 133

182 Bulk density (g/cc) T 0-5 cm ST BP CT T X CC T T cm 1.65 T T cm T TXCC T T 0 Initial 1 After 2 1 C 3 After 4 3 C After 5 4 C After 6 6 C 7 Cropping Cycle T Figure Tillage effects on soil bulk density over cropping cycles - initially and after Crops 1, 3, 4 and 6 at 0-5 cm, 5-10 cm and cm soil depths in Digram. Values are means across residue levels. The error bars for each data point represents ± 1 standard error. The floating error bars on figure at each depth represent the least significant difference (LSD) at P 0.05 for tillage after each crop (T) and interaction between tillage and cropping cycles (TXCC) Residue effects The soil BD under HR (1.25 and 1.38 g/cc) was lower than that under LR (1.30 and 1.40 g/cc) at 0-5 cm and 5-10 cm soil depth, respectively (Figure 4.16). However, the 134

183 Bulk density (g/cc) residue effects on soil BD were absent after all crops at cm soil depth (Figure 4.16) cm HR LR cm cm Initial 1 After 2 1 C 3 After 43 C After 54 C After 6 6 C 7 Cropping Cycle Figure Residue effects on soil bulk density after different cropping cycles initially and after Crops 1, 3, 4 and 6 at 0-5 cm, 5-10 cm and cm soil depths in Digram. Values are means across tillage treatments. The error bars for each data point represents ± 1 standard error. The floating error bars on figure at each depth represent the least significant difference (LSD) at P 0.05 for residue after each crop Volumetric soil water content and penetration resistance 135

184 Tillage effects Figure 4.17 shows the dynamic nature of SWC and soil PR at 0-5, 5-10, cm soil depth under different tillage systems after different crops. When the soil depth of 0-5 cm was monitored, no differences in SWC were seen for tillage treatments over time (Figure 4.17). At 5-10 cm, the SWC of BP (21 % and 17 %) was significantly (P 0.05) lower than that of CT (25 % and 20 %) and ST (23 % and 19 %) after Crop 1 and 4 (Figure 4.17), whilst after Crop 6 and 7, the SWC of BP (36 % and 33 %) was significantly higher than that of CT (33 % and 31 %) and ST (34 % and 30 %) (Figure 4.17). At cm soil depth, the SWC of BP (31.6 % and 32.5 %) and ST (30.0 % and 30.3 %) was higher than that of CT (28.4 % and 29.8 %) after Crop 6 and 7 (Figure 4.17). At 0-5 cm soil depth, the soil PR of BP (0.7 MPa) was significantly lower than that of ST (1.3 MPa) and CT (1.6 MPa) after Crop 1 (Figure 4.17). However, the soil PR of BP (2.0 MPa) was significantly higher than that of ST (1.6 MPa) and CT (1.5 MPa) after Crop 4 (Figure 4.17). After Crop 7, the soil PR of BP (0.6 MPa) and ST (0.7 MPa) was lower than that of CT (0.9 MPa) at 0-5 cm soil depth (Figure 4.17). At 5-10 and cm soil depths, the soil PR of BP was consistently lower than that of CT and ST after all crops and the order of soil PR was CT>ST>BP (Figure 4.17). At 5-10 soil depth, the soil PR was lower with BP (1.5, 2.3, 3.7, 0.6 and 0.8 MPa) and higher with CT (4.4, 3.9, 5.3, 1.4 and 1.8 MPa) after Crop 1, 3, 4, 6 and 7, respectively (Figure 4.17). The soil PR of ST (2.6, 0.9 and 1.5 MPa) was lower than that of CT (4.4, 1.4 and 1.8 MPa) after Crop 1, 6 and 7 (Figure 4.17). Similarly, at cm soil depth, the soil PR of BP (5.9, 6.4, 6.9, 2.1 and 1.8 MPa) was lower than that of CT (10.0, 8.3, 7.8, 4.1 and 3.2 MPa) and ST (8.3, 7.4, 7.3, 2.6 and 2.7 MPa) (Figure 4.17). The soil PR of ST was also significantly lower than that of CT at cm soil depths (Figure 4.17). 136

185 Volumetric soil water content (%) Soil penetration resistance (MPa) cm ST BP CT cm ST BP CT cm After Crop 1 After Crop 3 After Crop 4 After Crop After Crop 1 After Crop 3 After Crop 4 After Crop 6 After Crop cm cm After Crop 1 After Crop 3 After Crop 4 After Crop 6 After Crop cm After Crop 1 After Crop 3 After Crop 4 After Crop 6 After Crop After Crop 1 C1 After Crop 3 C3 After Crop 4 C4 After Crop 6 C6 After Crop 7 C7 Cropping Cycle 0 After After Crop 1 C1 After After Crop 3 C3 After After Crop 4 C4 After After Crop 6 C6 After After Crop 7 C 7 Cropping cycle Figure Dynamic changes of volumetric soil water content (%) and penetration resistance (MPa) due to tillage after Crops 1, 3, 4, 6 and 7 at 0-5 cm, 5-10 cm and cm soil depths in Digram. Values are means across residue levels. Error bars were ± 1 standard error of the mean and floating error bar indicates significant difference at P 0.05 level between treatments on that time of measurement Residue effects At 0-5 cm soil depth, the SWC of HR (19, 41 and 33 %) was 1-2 % higher than that of LR (17, 40 and 31 %) after Crop 4, 6 and 7, respectively (Figure 4.18). At 5-10 cm soil depth, the SWC of HR (23.3 and 32.0 %) was higher as compared to LR (22.8 and 30.9 %) after Crop 1 and 7 (Figure 4.18). At cm soil depth, there were no differences in SWC due to residue treatments after all crops (Figure 4.18). 137

186 Volumetric soil water content (%) Soil penetration resistance (MPa) cm HR LR cm HR LR cm After Crop 1 After Crop 3 After Crop 4 After Crop 6 After Crop After Crop 1 After Crop 3 After Crop 4 After Crop 6 After Crop cm After Crop 1 After Crop 3 After Crop 4 After Crop 6 After Crop cm cm After Crop 1 After Crop 3 After Crop 4 After Crop 6 After Crop After Crop 1 C1 After Crop 3 C3 After Crop 4 C4 After Crop 6 C6 After Crop 7 C7 After Crop 1 C1 After Crop 3 C3 After Crop 4 C4 After Crop 6 C6 After Crop 7 C7 Cropping Cycle Cropping cycle Figure Dynamic changes of volumetric soil water content (%) and penetration resistance (MPa) due to residue after Crops 1, 3, 4, 6 and 7 at 0-5 cm, 5-10 cm and cm soil depths in Digram. Values are means across tillage treatments. Error bars were ± 1 standard error of the mean and floating error bar indicates significant difference at P 0.05 level between treatments on that time of measurement. At 0-5 cm soil depth, the soil PR of HR (1.4 MPa) was significantly (P 0.05) higher than that of LR (1.0 MPa) after Crop 1 but the soil PR of HR (0.7 MPa) was lower than that of LR (0.8 MPa) after Crop 7 (Figure 4.18). At 5-10 cm soil depth, the soil PR of HR (3.2 MPa) was significantly (P 0.05) higher than that of LR (2.5 MPa) after Crop 1 (Figure 4.18). At cm soil depth, residue effects on soil PR disappeared at all sampling times (Figure 4.18). 138

187 Table 4.2. Soil penetration resistance (MPa) at three different depths (0-5 cm, 5-10 cm and cm) under tillage and residue after different crop in cereal-dominated system in Digram. Tillage Residue Soil penetration resistance (MPa) Initial After Crop 1 After Crop 3 After Crop 4 After Crop 6 After Crop cm soil depth ST HR LR BP HR LR CT HR LR LSD Tillage (T) 0.4** ns 0.3* ns 0.1** Residue (R) 0.3** ns ns ns 0.1** TXR ns ns ns ns ns 5-10 cm soil depth ST HR LR BP HR LR CT HR LR LSD 0.05 Tillage (T) 1.3** 0.9** 1.0* 0.3** 0.2** Residue (R) 0.3** ns ns ns ns TXR 1.3* ns ns ns ns cm soil depth ST HR LR BP HR LR CT HR LR LSD 0.05 Tillage (T) 1.7** 0.9** 0.5* 0.7** 0.4** Residue (R) ns ns ns ns ns TXR ns ns ns ns ns 139

188 1 HR - high residue; LR - low residue, ST - strip tillage; BP - bed planting; CT - conventional tillage; 2 the least significant difference (LSD) at the P 0.05, ns - not significant, * - significant at P 0.05 and ** - significant at P The interaction effects of tillage and residue treatment on soil PR were not significantly different except at 5-10 cm soil depth (Table 4.2). At 5-10 cm soil depth, the soil PR was higher in CTHR and lower in BPLR (Table 4.2) Trends of volumetric soil water content and penetration resistance following planting of wheat Tillage effects The trends of soil drying and penetration resistance at 0-5 cm, 5-10 cm and cm from 5 to 30 DAS at 5 days interval are shown for tillage treatments (Figure 4.19). Across all treatments, the SWC continued to decrease and soil PR increase at all depths of measurements from sowing until 30 DAS (Figure 4.19a1-a3 and 4.19b1-b3). After sowing, the plots under BP continued to have the higher surface SWC for most days of measurement than ST and CT, but significant differences were only found at 5, 10 and 15 DAS (Figure 4.19a1). There were no differences of SWC for the depths 5-10 cm and cm (Figure 4.19a2-a3). The soil PR continued to increase with days after sowing regardless of treatments at all depths studied (Figure 4.19b1-b3). At 0-5 cm soil depth, the soil PR of BP was greater than that of CT and ST at all dates of measurement except at 25 DAS (Figure 4.19b1). The differences of soil PR at 5-10 cm and cm soil depths due to different tillage followed the order of CT>ST>BP (Figure 4.19b2-b3). Except at 15 DAS for cm soil depth, the soil PR of BP was lower as compared to ST and CT at all dates of measurement at 5-10 cm and cm (Figure 4.19b2-b3). 140

189 Volumetric soil water content (%) Soil penetration resistance (MPa) 40 a1) 0-5 cm ST BP CT 6.0 b1) 0-5 cm ST BP CT a2) 5-10 cm b2) cm a3) cm b3) cm Days after sowing Days after sowing Figure The volumetric soil water content (%) (a1-a3) and soil penetration resistance (b1-b3) at 0-5 cm, 5-10 cm and cm soil depths for different tillage treatments at 5 days after sowing (DAS) to 35 DAS during wheat planting in 2013 in Digram. Values are means across residue levels. Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of tillage on that date of measurement and error bars indicates ± 1 standard error of the mean Residue effects Following sowing of wheat (Crop 7), the trend of soil drying and penetration resistance at 0-5 cm, 5-10 cm and cm from 5 DAS to 30 DAS at 5-day intervals are shown between residue treatments (Figure 4.20). The SWC continued to decrease with days after sowing irrespective of residue treatments. However, the SWC of HR was 141

190 Volumetric soil water content (%) Soil penetration resistance (MPa) significantly higher than that of LR at 0-5 cm and 5-10 cm soil depth only at 5 and 10 DAS (Figure 4.20a1-a2). There was no effect of residue on SWC at cm depth, except at 10 DAS, when the SWC of HR was significantly higher than that of LR treatment (Figure 4.20a3). 40 a1) 0-5 cm HR LR 6.0 b1) 0-5 cm HR LR a2) 5-10 cm b2) 5-10 cm a3) cm b3) cm Days after sowing Figure The volumetric soil water content (%) (a1-a3) and soil penetration resistance (b1-b3) at 0-5 cm, 5-10 cm and cm soil depths for different residue treatments at 5 days after sowing (DAS) up to 35 DAS during wheat planting in 2013 in Digram. Values are means across tillage treatments. Floating error bars indicate Days after sowing 142

191 Penetration resistance (MPa) the least significant difference (LSD) at P 0.05, for the effects of tillage on that dates of measurement and error bars indicate ± 1 standard error of the mean. At 0-5 cm soil depth, the soil PR of HR was significantly lower than that of LR at 5, 10 and 15 DAS (Figure 4.20b1). When the depth 5-10 cm was monitored, no differences of soil PR were seen between residue treatments over time (Figure 4.20b2). At cm soil depth, HR had lower soil PR compared to LR at 5 and 10 DAS (Figure 4.20b3) Relationship between soil physical properties Relation between soil bulk density and penetration resistance The soil PR increased with an increase in soil BD after Crop 1, 3, 4 and 6 in Digram (Figure 4.21a-d). Penetration resistance (MPa) Penetration resistance (MPa) a) y = 26.11x R² = Bulk density (g/cc) y = 15.02x R² = c) Bulk density (g/cc) Figure Relationship between soil penetration resistance (MPa) and bulk density (g/cc) after different crop determined: a) after Crop 1; b) after Crop 3; c) after Crop 4; Penetration resistance (MPa) b) y = 13.42x R² = Bulk density (g/cc) 12 y = 8.16x R² = d) Bulk density (g/cc)

192 Bulk density (g/cc) Bulk density (g/cc) d) after Crop 6 during in Digram. Values are for all three depths (0-5 cm, 5-10 cm and cm). The line represents the regression equation shown above in the graph Depth distribution of soil physical parameter at bed planting and strip tillage system in Digram Distribution of soil bulk density The soil BD was not significantly different (P 0.05) due to the sampling position of BT and BF of the BP except at 5-10 cm soil depth after Crop 6 (Figure 4.22a). The soil BD of BT was higher than that of BF in the 5-10 cm soil depth (Figure 4.22a). In the event of ST, the soil BD of IS exhibited higher than that of OS in the depth of cm after Crop 7 (Figure 4.22b) a) BT vs BF Initial BT BF b) Initial OS IS OS vs IS cm 5-10 cm cm cm 5-10 cm cm Sampling position and depth Sampling position and depth Figure Variation of soil bulk density after Crop 6 in Digram relative to depth from the bed top (BT) and from the level of the bed top in the furrow (BF) of the bed planting system (a); and in the strip (IS) and off-the strip (OS) of strip tillage system (b). For comparison, initial values (before starting the experiment) are also shown. Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of sampling positions. 144

193 Distribution of volumetric soil water content After Crop 7, the SWC of BT was higher (P 0.05) than that of BF in the depth of 5-10 cm depth (Figure 4.23a). In case of ST, the SWC of OS was higher (P 0.05) than that of IS at 5-10 cm soil depth (Figure 4.23b). Volumetric soil water content (%) a) BT vs BF Initial BT BF 0-5 cm 5-10 cm cm Sampling position and depth Volumetric soil water content (%) b) OS vs IS Initial OS IS 0-5 cm 5-10 cm cm Sampling position and depth Figure Variation of volumetric soil water content (%) after Crop 7 in Digram relative to depth from the bed top (BT) and from the level of the bed top in the furrow (BF) of the bed planting system (a); and in the strip (IS) and off-the strip (OS) of strip tillage system (b). For comparison, initial values (before starting the experiment) are also shown. Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of sampling positions Distribution of soil penetration resistance The soil PR increased with increasing soil depth for both BP and ST after Crop 7 (Figure 4.24). The differences of soil PR due to sampling position of BP system were not significant in 0-5 cm and cm depths (Figure 4.24a). The soil PR of BT was higher (P 0.05) than that of BF in the 5-10 cm (Figure 4.24a). In the case of ST, the soil PR was significantly differed (P 0.05) due to sampling position in all the depths of study (Figure 4.24b). The soil PR of OS was significantly higher (P 0.05) than that of IS at all depths of study (Figure 4.24b). 145

194 Soil penetration resistance (MPa) a) BT vs BF Initial BT BF Soil penetration resistance (MPa) b) Initial OS IS OS vs IS OS vs IS OS vs IS 0-5 cm 5-10 cm cm 0-5 cm 5-10 cm cm Sampling position and depth Sampling position and depth Figure Variation of soil penetration resistance (MPa) after Crop 7 in Digram relative to depth from the bed top (BT) and from the level of the bed top in the furrow (BF) of the bed planting system (a); and in the strip (IS) and off-the strip (OS) of strip tillage system (b). For comparison, initial values (before starting the experiment) are also shown. Floating error bars indicate the least significant difference (LSD) at P 0.05, for the effects of sampling positions Soil temperature at Digram The soil temperatures were tracked during day and night from planting to harvesting of the wheat crop (from 3-10 to DAS) (Figure 4.25a and 4.25b). The soil temperatures both at day and night remained stable during the first 59 DAS in all treatments (Figure 4.25a and 4.25b). After 59 DAS, the soil temperature tended to rise and reached a peak at DAS (Figure 4.25a and 4.25b). The day soil temperature was higher with CT (maximum soil temperature was 20.3 C at DAS and minimum temperature was 16.1 C at DAS) than those recorded in ST and BP from beginning to 80 DAS. Afterwards, the warmer soil temperature was tracked in BP from DAS to DAS (Figure 4.25a). However, the night soil temperature was slight higher with ST than those recorded in CT and BP from beginning to 59 DAS; and afterwards from DAS to DAS, the night temperatures tracked in BPLR were higher than other treatments (Figure 4.25b). 146

195 ST HR BP HR CT HR ST LR BP LR CT LR Day soil temperature ( C ) Days after sowing Mean soil temperature ( C) a) b) Night soil temperature ( C ) Days after sowing Figure The variation of mean soil day (a) and night soil temperature ( C) (b) due to different treatments during wheat growing season at Digram in Values are means of seven day intervals. 4.4 Discussion Soil bulk density and penetration resistance Treatment effects on soil BD were not clearly apparent until after Crop 6 when the ST had lower soil BD of surface soil than CT. The lower soil BD at ST could be attributed to the development of better soil structure and increased porosity as a result of improvement of SOC (see Chapter 5) in the surface soil (0-5 cm). The results of the 147

196 present study are consistent with the findings of Singh et al. (2016), who reported that the soil BD was higher in transplanted puddled rice followed by conventionally tilled maize than in the conventionally direct-seeded rice/conventionally tilled maize and zero-tillage direct-seeded rice/conventionally tilled maize treatments in a rice-maize system. Puddling of soil for rice cultivation in CT, involves the destruction of the soil aggregates and reduced soil porosity and thereby increased subsoil compaction and soil BD in medium-textured soil in India (Gathala et al., 2011b). Bhattacharyya et al. (2015) demonstrated that the plots under mungbean residue + direct seeded rice followed by ZT wheat with rice residue retention and zero tilled relay summer mungbean reduced soil BD compared to transplanted rice-conventionally tilled wheat. Ball et al. (1997) reported that the soil BD modified as a result of improvement of soil organic matter by practicing of conservation agriculture. Although the soil BD was not significantly different between ST and CT below 5 cm soil depth, the soil PR was consistently lower with ST than CT treatment at 5-10 cm and cm soil depths especially at Digram. The emergence of differences of soil PR earlier in the experiment than soil BD indicated that the soil PR is a more sensitive indicator than soil BD to changes in soil physical properties. The soil PR was least at surface 0-5 cm soil depth of BP after Crop 1 due to loose and pulverized soil on top of the raised bed as reported by other researchers who noted the loosening effect of tillage decreased the soil BD at the surface layer of young beds relative to CT treatment (Naresh et al., 2012; Jat et al., 2013). However, subsequently the soil BD of surface soil under BP tended to increase up to Crop 6, particularly after rice crops. This tendency may be attributed to slaking, settling, reconsolidating and compacting of pulverized and loose soil of refreshed beds by ponding of standing water and then drying of the compacted soil following the end of the monsoon rain. For the subsurface soil (5-10 cm and cm soil depth), the soil PR under BP was consistently lower than that under CT and ST which might be due to the initial burial of crop residue when beds are reformed. In addition, increased SWC (Figure 4.5 and 4.19) and SOC (see Chapter 5) as the repeated burial of residue when re-shaping beds may contribute to the reduced soil BD in the subsurface soil. Further Govaerts et al. (2006b) 148

197 reported that BP had a unique natural opportunity to decrease compaction by confining traffic to the furrow bottoms. At the end of Crop 6 and 7, deposition of increased crop residue of successive crops decreased soil BD and PR under HR at 0-5 cm and 5-10 cm soil depth. The improvement of SOC (see Chapter 5) in surface soil (0-5 cm) after Crop 6 and 7 under HR likely resulted in better soil structure, increased soil porosity and thereby decreased in soil BD at 0-5 cm. The findings of the present study are in conformity with those reported earlier by several other researchers in different regions (Bhattacharyya et al., 2008; Govaerts et al., 2009; Singh et al., 2016), which demonstrated the positive effects of residue retention on soil BD at 0-10 cm depth. Retention of residue together with NT in the Chinese Loess Plateau increased SOM and biotic activity, resulting in decreased soil BD of the surface soil layer (Chen et al., 2008). The results of the present study suggested that HR is effective in reducing soil BD and PR, which might be enhanced root growth and contribute to increased yield of lentil and wheat following rice (see Chapters 2 and 3) Volumetric soil water content The increased SWC in subsurface soil of BP and ST found in the present study may indicate greater water infiltration induced by conservation tillage and surface residue retention over the year s duration of the study. That ZT and residue retention enhanced infiltration rate compared to CT and residue removal has been reported by several researchers (Gathala et al., 2011b; Jat et al., 2013). The higher SOC under ZT was associated with increased SWC at 0-15 cm soil depth than CT in a rice-wheat system in the Indian Himalayas (Bhattacharyya et al., 2008). The continuity of water conducting pores and improvement of soil aggregation enhanced infiltration under ZT due to minimal soil disturbance compared to CT (dry and wet) (Dwivedi et al., 2012). In the present study, over time retention of high residue and undisturbed soil in ST increased SOC (see Chapters 5) which suggests the potential for improved surface soil structure and enhanced infiltration rate after years (after Crop 6-7). The lower soil PR in subsurface soil (5-15 cm soil depth) after Crop 7 suggested that the plough 149

198 pan had been reduced with time in ST. In the current study, the increased SWC under OS at 5-10 cm soil depth than IS can also be attributed to enhanced infiltration as a result of residue retention and undisturbed soil of OS. Similar root growth (see Chapter 3) under different tillage suggests that increased water use is not the reason for lower SWC in the CT treatment. After Crop 1, the SWC of BP at 0-5 cm soil depth was lower than in other tillage treatments at Alipur, a rainfed area. This can be attributed to the more rapid drying following formation of the bed due to the heaping of pulverized and loose soil to form the bed. Between Crop 1 and Crop 7, the SWCs of the surface soil were not significantly different between tillage treatments. After Crop 7 at Alipur, the SWC of the surface soil was higher with CT as compared to ST and BP. At the Alipur experimental site for the last decade, monsoon rice was generally grown by using conventional puddled transplanting system followed by dryland crops grown by intensive tillage with residue removal. Generally puddling created a soil condition favourable for wetland rice by retaining water in the root zone through reducing infiltration as a result of the compacted plough pan (Sharma & De Datta, 1986). Consequently, poor soil structure in the surface 0-7 cm soil layer and a hard plough pan below 7-8 cm soil depth existed before the experiment regardless of treatment. By contrast, the minimal soil disturbance and the increase residue retention under ST create the possibility of restoration of soil structure and alteration of soil strength and SWC by increases in soil aggregation and by changes in the size, continuity, geometry and stability of pores (Shaver et al., 2002). The implementation of CT decreased SWC faster with days after sowing likely due to higher evaporation loss as compare to ST and BP plus HR in the present study. The surface soil under CT had warmer day temperatures and decreased SWC compared to ST and HR treatments in the present research. These findings are in agreement with Licht and Al-Kaisi (2005b) who observed that intensive tillage disturbs soil and increases air pockets which tended to enhance evaporation loss and accelerated soil drying and heating. By contrast, anchored residue retention on ST and BP reduced evaporation and runoff leading to increased surface SWC at ST and BP compared to CT. 150

199 In a study of rainfed Mediterranean condition, Vita et al. (2007) found that the storage of SWC increased by 20 % under NT due to lower evaporation than CT. The increased SWC at ST and HR also might be associated with reduced soil temperature in the present study, as reported by Limon-Ortega et al. (2002). High residue retention during each of the 7 crops was associated with increased SWC after Crop 6 and 7. Although residue effects on SWC were significantly different at surface soil, the effects however disappeared at deeper layers. The drying of soil at 0-5 cm and 5-10 cm soil depth was greater in LR compared to HR suggesting that less residue retention increased surface evaporation. Rasmussen (1999) reported that high residue retention on soil surface decreased evapotranspiration and increased SWC at surface 10 cm soil depth. Rahman et al. (2005) and Chakraborty et al. (2008) reported that rice straw mulch was effective in conserving SWC compared to bare soil. Higher SWC under HR favoured higher uptake of water at all depth of measurements which was associated with an increased yield (see Chapter 2) and root growth of cool dry season crops, lentil and wheat (See Chapter 3). The soil BD had a positive relation with soil PR in the present study. Tarkiewicz and Nosalewicz (2005) found that the changes in soil PR are dependent on SWC, BD and SOC in a similar texture of soils. In this study, the lower soil PR and higher SWC might be due to improvement soil structure (soil BD) and SOC in ST and HR compared to CT and LR especially after Crop 7 (See Chapter 5). The findings are well supported by Bescansa et al. (2006) those who reported greater SWC in conservation tillage might be attributed to improvement in organic matter and soil structure. Further, the greater SOC reduced soil BD in ST and HR compared to CT and LR. In a similar value of SWC across all treatments, the soil PR was positively correlated with soil BD (Sharma & De Datta, 1986). In the present study, the soil PR increased with decreasing SWC regardless of treatments except after the dryland crop. The soil PR decrease with increasing SWC is in agreement with the results reported in other studies (Mapfumo & Chanasyk, 1998; Kumar et al., 2012). However, this relationship was reverse after dryland crop. For growing dryland crop, tillage is used to create a loose and pulverized soil (all parts of CT and most parts of BP; and seed zone of ST) for better seed bed 151

200 preparation. This pulverized and loose soil immediately after tillage reduced the soil PR as well as decreased SWC, due to enhanced evaporation System differences Irrespective of treatment differences, the soil BD was lower in the cereal-dominated system at Digram than in the legume-dominated system at Alipur. This might be due to its inherent soil properties with less sand and higher SOC at Digram than Alipur (See Chapter 5 and 6). The SWC was significantly different due to tillage after Crop 1 and 7 at Alipur while no differences were found at surface soil of Digram. Probably 2-3 times irrigation application for wheat crop negated the treatment effects of tillage. Further, residue effects on SWC were more pronounced in the legume-dominated system in Alipur, than the cereal-dominated system in Digram. This could be because the short canopy structure of lentil allowed soil to receive more radiation energy during crop growth. In contrast, the closed canopy of wheat resulted in less solar radiation capture by the soil of Digram irrespective of all treatments; hence this may result in insignificant differences between treatments on SWC in the surface soil. 4.5 Conclusion The results from a 2.5-year study demonstrated that ST and BP for non-rice crops and HR followed by unpuddled rice cultivation facilitated better soil physical conditions as compared to CT and LR followed by puddled rice cultivation in two rice-based cropping systems in Bangladesh. Strip tillage and unpuddled rice coupled with HR decreased soil BD and PR while increasing SWC below the surface for rice-dryland cropping systems. In Chapter 3, it was reported that reduced soil disturbance and HR also improved in SWC and decreased soil PR of the surface soil. By contrast with ST, the BP system with unpuddled soils for rice had mixed effects on soil physical properties. Although there was lower soil PR at surface soil after Crop 1 (dryland crop) in BP, due to loose and pulverized soil of the newly constructed bed, there was an increasing tendency to increase soil PR by settling soil after the rice crop, indicating that the positive effects of BP in the dryland crop were lost by ponded rice cultivation. After sowing, the SWC was greater in surface soil of ST and BP due to retention of surface residue. The above 152

201 results demonstrated that gradual improvement in soil physical properties such as soil BD at surface soil (0-5 cm) and the SWC at subsurface soil (5-10 cm and cm) layer in ST as well as by switching from puddling by unpuddled rice is likely to be superior to CT and BP in the long run. However, the physical soil properties of rice-based system need to be monitored throughout the year. In addition, the present study needs to be continued for a longer period to evaluate the performance of unpuddled rice followed by ST/BP dryland crop with high residue retention in rice-based systems representing different soil, climatic, and socio-economic conditions in the IGP. After long-term periods, other physical properties such as soil aggregation, and water loss pathways such as infiltration, deep drainage, runoff, evaporation need to be quantified to understand the water balance under CA practices. 153

202 5 Short-medium term effects of conservation management practices on soil organic carbon pools in rice-based systems in Bangladesh 5.1 Introduction Soil organic carbon (SOC) depletion is one of the potential reasons suggested for decline in crop yield and productivity in high-input intensive rice-based systems of the Indo-Gangetic Plains (IGP), where 2-3 crops per year are grown on the same piece of land (Duxbury et al., 1989; Ladha et al., 2003a). The current form of tillage and residue removal for the crops grown after rice in the IGP is known to decrease SOC which may in turn decrease crop yield. The soil conditions of rice-based crop rotations are distinct from other lowland or dryland soils as rice and non-rice crops are generally grown sequentially under contrasting hydrological environments alternating between wetting and drying resulting in aerobic and anaerobic conditions, respectively (Zhou et al., 2014; Dossou-Yovo et al., 2016). The deterioration of SOC is accelerated in rice-based systems due to the crushing of soil aggregates by intensive multiple cultivations each year involving puddling for rice and rigorous tillage for non-rice crop cultivation (Six et al., 2004; Shibu et al., 2010). However, prolonged submergence of lowland soils and anaerobic conditions decrease the rate of heterotrophic respiration (microbial decomposition) in the anoxic soil while carbon fixation by algal photosynthesis adds to SOC (Dossou-Yovo et al., 2016). In contrast, upland aerobic conditions hasten the oxidation of accumulated SOC and losses of carbon dioxide (CO₂) to the atmosphere (Nakadai et al., 1996). Al-Kaisi and Yin (2005) reported that the extent of CO₂ emission is highly related to the frequency and intensity of tillage of the soil. Tillage hastens CO₂ evolution by improving soil aeration, and increasing contact of soil and crop residue (Angers et al., 1993). Additionally tillage could increase the exposure of SOC in inter and intra-aggregate zones to microbes for rapid oxidation (Jastrow et al., 1996). Crop management practices, viz. tillage and residue management, can influence soil CO₂ emission but their impacts on soil CO₂ emission are complex and varied (La Scala Jr et al., 2006). However, CO₂ emission can be reduced by using conservation agriculture practices (Mosier et al., 1991). 154

203 Soil organic carbon has a profound effect on soil structure, which in turns affects soil aeration and soil pore size distribution (Al-Kaisi & Yin, 2005; Nayak et al., 2012). It also improves infiltration rates, plant available soil water storage and serves as a buffer against rapid changes in soil reaction (ph). Apart from maintaining and enriching soil nutrient supply, it also reduces the loading of CO₂ and methane (CH4) into the atmosphere (Dahal & Bajracharya, 2010; Srinivasarao et al., 2014). It is also a key source of microbial energy and nutrients. Hence, the maintenance of SOC and nutrient cycling are invaluable for improving crop productivity and sustainability (Blair et al., 1995; Franzluebbers, 2010). Information on SOC-stocks in farmland soil is important due to their effects on climate change and crop production (Majumder et al., 2008). The SOC-stocks mirror the longterm balance between SOC input and losses through different pathways, and it is an indicator of carbon dynamics under different management practices (Farage et al., 2007). Unlike SOC concentrations, the stock account for changes in both SOC concentrations and bulk density (Liu et al., 2014b). However, it is difficult to detect changes in SOC in the short- and medium-term because of the large pool of recalcitrant SOC relative to annual inputs (Li et al., 2012) and its high spatial variability (Blair et al., 1995). In contrast, water soluble carbon (WSC) is an important labile organic C fraction which can respond more rapidly than total SOC to soil management factors like different tillage and residue retention (Chan et al., 2002; Haynes, 2005; Roper et al., 2010). It could be used as a primary energy source and an indicator of the carbon availability for soil microorganisms (Stevenson, 1994). Furthermore, the WSC is the entire pool of water extractable organic carbon either sorbed on soil particles or dissolved in interstitial pore water (Tao & Lin, 2000). It is a small portion (~1-3 %) of the total SOC (Tao & Lin, 2000; Ohno et al., 2007; Scaglia & Adani, 2009; Li et al., 2012) but is considered as an important mobile and reactive soil carbon source (Lu et al., 2011). This fraction acts as a substrate for microbial activity, a primary source of mineralizable N, S, and P and its leaching greatly influences the nutrient content and ph of groundwater (Haynes, 2005). 155

204 The study of SOC sequestration in paddy soils is necessary as paddy soils in the IGP are degrading. Also paddy soils have a greater SOC storage than dryland soils (Xu et al., 2013). Sequestration of SOC which involves the storage of carbon as organic matter also contributes to the mitigation of CO₂ emission from soil (Lal, 2004b; Das et al., 2013). Thus, SOC sequestration is a potential strategy for restoring the degraded soils, improving crop productivity and diversity, reducing atmospheric CO₂ emission and thereby mitigating climate change (Wang et al., 2010). Residue decomposition, soil respiration and SOC mineralization are the major sources of CO₂ emission in agricultural land (Luo & Zhou, 2006). Soil respiration involves CO₂ production by roots, soil microbes, and soil fauna within soil and litter layers (Luo & Zhou, 2006). Figure 5.1 shows the CO₂ production process in soil (Luo & Zhou, 2006). Figure 5.1. Schematic representation of CO₂ production processes in soil. Those processes are root respiration, rhizosphere respiration, litter decomposition, and oxidation of SOM. Adapted from Luo and Zhou (2006). Although the effect of minimum tillage and residue retention on SOC and its fractions has been studied in many parts of the world, this information is scarce for intensive rice-based systems in the Eastern IGP. There is thus a clear need to understand the changes in SOC and its fractions when intensive rice-based systems, as practiced in Bangladesh, are converted to conservation agriculture practices. It was hypothesized 156