Improving Measurements of Agricultural Productivity through Methodological validation and Research (LSMS-ISA)

Transcription

1 Improving Measurements of Agricultural Productivity through Methodological validation and Research (LSMS-ISA) Progress Report -3 (Sept Dec. 2014) Report compiled by Ermias Betemariam Keith Shepherd Land Health Decisions (SD4) World Agroforestry Centre (ICRAF) December 2014

2 1. Project background and objectives Building on the ongoing Living Standards Measurement Study- Integrated Surveys on Agriculture effort and as part of a broader World Bank research agenda by the Development Economics Research Group (DECRG), the Living Standards Measurement Study (LSMS) team is initiating a multi-faceted research project aimed at improving the quality and relevance of agricultural statistics. The research agenda includes seven distinct components: (1) land area measurement, (2) soil fertility, (3) water resources, (4) labor inputs, (5) skill measurement, (6) production of continued and extendedharvest crops, and (7) computer-assisted personal interviewing for agricultural data. This report is on soil fertility measurement for which ICRAF is responsible. Measurement of monitoring of soil quality and land health are fundamental to developing a sound knowledge of problems and solutions for sustainable crop production and land management. Much of the current analysis on agricultural productivity is hampered by the lack of consistent, good quality data on soil health and how it is changing under past and current management. This is especially critical in the face of increased variability in weather conditions brought on by climate change. Renewed interest in increasing agriculture productivity to meet food security needs and increasing resilience of agricultural systems in developing countries, especially in sub- Saharan Africa, makes understanding soil fertility constraints and trends ever more important. Direct systematic measurement of soil fertility as part of household level data collection has rarely been attempted due to the high costs of soil sampling and analysis. Having panel samples of the soil of plots directly linked to the household panel survey of the LSMS-ISA provides an important opportunity for enhancing our understanding of trends in soil health and their impact on crop productivity among smallholders, as well as of the coping mechanisms adopted by farmers faced with deteriorating soil conditions. 2

3 New systematic surveillance frameworks for systematic and consistent monitoring of soil and land health have recently been developed based on new digital sensing technology (UNEP, 2012). In particular, new rapid low cost technology for assessing soil characteristics using infrared spectroscopy has made soil fertility characterization feasible in large studies (Shepherd & Walsh, 2002, 2007). These techniques are now being supplemented by other light-based techniques using laser and x-ray spectroscopy and are being applied to large areas sampling schemes in sub-saharan Africa under the Africa Soil Information Service project ( An important output from this project is the establishment of soil catalogues and creation of a country-specific handbook for Ethiopia detailing a protocol of analysis of soil samples collected from household surveys. This will enable the mapping of selfreported measures of land quality at the agro-ecological level to help in better decisionmaking. 2. Activities and progress Soil sample processing and analysis were the main activities planned during this reporting period. A summary of the planned activities and progress made during the reporting period are indicated in Table 1. 3

4 Table 1. Progress summary Activities (based on the project document) 1. Analysis of soil samples (approximately plots each) from country #1. SSA (MIR and LDPSA) executed on all samples; SSA (X-ray) and CSA on a subset of samples (approximately 25-33% of topsoils and 5-33% of subsoils, to be determined based on final samples size calculations and agreed upon by both parties). 2. Catalogues of soil samples to serve as reference in categorizing land quality of soils from different agro-ecological zones and enable functional mapping of SSA to CSA results in two LSMS-ISA countries 3. Establishing a prototype of soil infrared spectroscopy laboratory for services in rural areas 1 Milestones Milestone 1: Soil sample processing completed Milestone 2: Soil sample analyses completed Milestone 1: catalogues of soil ready Progress As indicated in the previous progress report (Report # 2, August 2014), 3611 soil samples processed locally in Ethiopia and submitted to the ICRAF s Soil-Plant Spectral Diagnostics Laboratory in Nairobi. During this reporting period additional 347 subsets of the total samples which were selected as references samples were submitted to the ICRAF s Soil-Plant Spectral Diagnostics Laboratory in Nairobi. All these samples were processed and submitted for conventional soil analyses (CSA). The 347 reference soil samples were analyzed using the CSA sample analysis (CSA) and used to predict soil properties for the remaining 3611 samples scanned for SSA: MIR, LDPSA and X-ray. A database for 3611 SSA data and 347 CSA soil samples from three agro-ecological zones of Ethiopia was established. The 347 soil reference samples used for CSA and the 3611 soil samples used for SSA were archived in ICRAF s Soil-Plant Spectral Diagnostics Laboratory in Nairobi. The required equipment to establish a model rural lab ordered. Activity 1: Soil sample analysis 1 This activity was not planned for the reporting period 4

5 Milestone 1: Soil sample processing As indicated in the previous progress report (Report # 2, August 2014), 3611 soil samples were processed locally in Ethiopia and submitted to the ICRAF s Soil-Plant Spectral Diagnostics Laboratory in Nairobi. During this reporting period 347 subsets of the total samples were selected as references samples were submitted to the ICRAF s Soil-Plant Spectral Diagnostics Laboratory in Nairobi. All these samples were processed and submitted for conventional soil analyses (CSA). The soil samples were collected from, Agro-ecological zones in the Oromiya region of Ethiopia (Fig. 1). According to FAO (1986), the three Agro-ecologigies are locally classified as Dega (altitude > 2300 m: West Arsi), Weyna Dega (altitude m: West Wellega), and kolla (altidude < 1500 m: Borena). West Wellega West Arsi Boren a Figure 1. Points where 3804 samples were collected in the Oromiya region of Ethiopia. All samples were collected from cultivated lands. Milestone 2: Soil sample analysis 5

6 The soil sample analyses task has been completed during this reporting period. The 347 reference samples went through conventional analysis and used to predict for the remaining 3611 samples. Table 2 indicates the type of soil data available for the 3611 samples collected from three Agro-ecological zones in Ethiopia. Table 2. Summary of list of samples of variables measured for 3661 samples collected from three Agro-ecological zones in Ethiopia Variables Units Variable description Sand % by volume Sand content of calgon dispersed particles after 4 minutes of ultrasonication Silt % by volume Silt content of calgon dispersed particles after 4 minutes of ultrasonication Clay % by volume Clay content of calgon dispersed particles after 4 minutes of ultrasonication Carbon % by weight Carbon content of acid treated sample to remove carbonates Nitrogen % by weight Nitrogen content of acid treated sample to remove carbonates ph Units Soil ph in water (soil: water ratio of 1:2 weight to volume basis) EC ds m^-1 Soil electrical conductivity (soil: water ratio of 1:2 weight to volume basis) m3_al mg kg^-1 Exchangeable aluminium concentration by Mehlich 3 extraction m3_b mg kg^-1 Boron concentration by Mehlich 3 extraction m3_ca mg kg^-1 Exchangeable calcium concentration by Mehlich 3 extraction m3_cu mg kg^-1 Copper concentration by Mehlich 3 extraction m3_fe mg kg^-1 Iron concentration by Mehlich 3 extraction m3_k mg kg^-1 Potassium concentration by Mehlich 3 extraction m3_mg mg kg^-1 Exchangeable Magnesium by wet method m3_mn mg kg^-1 Exchangeable Manganese concentration by Mehlich 3 extraction m3_na mg kg^-1 Exchangeable Sodium concentration by Mehlich 3 extraction m3_p mg kg^-1 Phosphorus by Mehlich 3 extraction Preliminary results Variation in soil organic carbon (SOC) and nitrogen were observed across the three Agro-ecological zones (Fig.1). The highest SOC concentration was measured in West Arsi (3.8%), followed by that in West Wellega (3.4%) and Borena (2.3%) areas. Generally, both SOC and Nitrogen concentrations showed a decreasing trend with depth (Fig. 1b,c). 6

7 (a) (c) (b) Figure 2. (a) SOC content distribtion for the topsoil (0-20 cm), (b) SOC distrbution in the topsoil and subsoil, and (c) Nitorogen distribtuion distribution in the top and subsoils in the three Agro-ecological zones. West Arsi has higher soil organic carbon and nitrogen content than West Wellega and Borena areas. Both soil SOC and Nitrogen concentrations showed a decreasing trend with depth. 7

8 Activity 2: Catalogues of soil samples A database for 3611 SSA data and 347 CSA soil samples from three agro-ecological zones of Ethiopia was established. The 347 soil reference samples used for CSA and the 3611 soil samples used for SSA were archived in ICRAF s Soil-Plant Spectral Diagnostics Laboratory in Nairobi to serve as catalogues of soil samples. Activity 3: Establishing a guideline for soil infrared spectroscopy services in rural areas As indicated in the previous progress report (Report # 2, August 2014), a guideline for establishing a soil infrared spectroscopy laboratory in rural areas was developed and the required equipment to establish a model rural lab were ordered. Further progress was made on developing the rural soil spectroscopy laboratory concept, in terms of sourcing a solar power option for running the portable spectrometer and testing of a new top scanning accessory that would obviate the need for fine grinding thus reducing analysis costs further and speeding up throughput from 80 samples per day to 300 samples per day. 3. Conclusions and perspectives Overall the project has progressed as expected. The soil monitoring system was tested in three agro-ecological zones in Ethiopia in which 3661 soil samples were collected along socio-economic survey. Having such samples of the soil of plots which can be linked to the household panel survey of the LSMS-ISA provides an important opportunity for enhancing the understanding of trends in soil health and their impact on crop productivity among smallholders, as well as of the coping mechanisms adopted by farmers faced with deteriorating soil conditions. Soil sample analyses work has been completed during this reporting period and its ready for writing a join World Bank- ICRAF country- specific handbook which will be submitted in Dec

9 References FAO Ethiopian Highlands Reclamation Study. Final Report, AG:UTF/ETH/037/ETH, FAO, Rome. Shepherd, K.D. & Walsh, M.G Development of reflectance spectral libraries for characterization of soil properties. Social Science Society of American Journal 66(3): Shepherd, K.D. & Walsh, M.G Infrared spectroscopy enabling an evidence-based diagnostic surveillance approach to agriculture and environmental management in developing countries. Journal of Near Infrared Spectroscopy 15: UNEP Land Health Surveillance: An Evidence-Based Approach to Land Ecosystem Management. Illustrated with a Case Study in the West Africa Sahel. United Nations Environment Programme, Nairobi. 9