SRI PADDY GROWTH SIMPLE PREDICTION MODEL

Transcription

1 International Journal of Civil Engineering and Technology (IJCIET) Volume 8, Issue 6, June 2017, pp , Article ID: IJCIET_08_06_046 Available online at ISSN Print: and ISSN Online: IAEME Publication Scopus Indexed SRI PADDY GROWTH SIMPLE PREDICTION MODEL N. A. I. Hasanah Student, Department of Mechanical and Biosystem Engineering, B. I. Setiawan Professor, Department of Civil and Environmental Engineering, C. Arif Lecturer, Department of Civil and Environmental Engineering, S. Widodo Lecturer, Department of Mechanical and Biosystem Engineering, ABSTRACT The System of Rice Intensification (SRI) is a paddy cultivation system that is known for its water management specialty. In practice, farmers regulate a water table in the paddy field to serve sufficient soil moisture to support the paddy growth. The paddy plant growth is represented by a tiller number produced during a cultivation season. The tiller number (N) increases with time (t), and differs on the different water level (h) applications. In this research, SRI paddy is cultivated in experimental pots under various water table treatments. The water table is controlled by using mariotte tubes and are set at -12, -7, -5, -3, 0, and +2 cm from the soil surface. The tiller number was measured in each pot every 3 days. A 3D surface from 3 parameters (N, h, t) was made. A simple multi-polynomial equation with R to predict N(h,t) was found after fitting the 3D surface. The SRI paddy growth simple prediction model can be used as a farmer s guide when planning to apply different water tables in their land. Key words: Fitting Surface, Multi Polynomial, Plant Growth and SRI editor@iaeme.com

2 N. A. I. Hasanah, B. I. Setiawan, C. Arif and S. Widodo Cite this Article: Hasanah, N. A. I., Setiawan, B. I., Arif. C, and Widodo, S. SRI Paddy Growth Simple Prediction Model. International Journal of Civil Engineering and Technology, 8(6), 2017, pp INTRODUCTION The System of Rice Intensification (SRI) involves changes in certain management practices to provide better growing conditions for rice plants than traditional practices, particularly in the rhizosphere[1]. SRI is actually a strategy of irrigated rice production, adapted to local conditions, that alters plant, soil, water and nutrient management practices (the means) with the purpose (the end) of: (a) inducing larger, better-functioning root systems, and (b) more abundant, diverse and active communities of soil biota that live in association with those root systems[2]. In SRI, rice was recognized as having great unattained internal potential for tillering and seeks to provide an optimum environment for plant to manifest such potential[3]. For SRI practice, the importance of keeping the soil unsaturated to get more air to plant roots is evident. It because soil moisture still play a crucial role [4]. The optimal value of soil moisture for SRI was found at (wet), (wet), (medium), and (dry) cm 3 /cm 3 for the initial, crop development, mid-season, and late season stages, respectively[5]. However, it was hard for farmers to understand the value of optimum soil moisture that should be kept in their field. In practice, farmers tended to apply sufficient water tables to serve good soil moisture. The different water table application could affect paddy growth[6], [7]. The reduction of water tables applied in a paddy field is one way of increasing water productivity based on a civil water engineering study[8]. Agriculture is the largest consumer of water and hence more effective use of water in agriculture is the highest priority[9]. The amount of water saved through water table reduction could be used for expanding the scheme to areas that were not receiving adequate irrigated water. This is especially important during the dry season and in years where rainfall is below normal, when rice farming needs to be sustained mainly through canal irrigation[10]. However, in fact farmers are generally hesitant to change the water table that they normally apply. It because possibly lead to decrease in productivity[11]. The aim of this research is to make a simple predictive model of rice plant growth that can be used to estimate the potential result when farmers implement another water table set-point. 2. METHODS The paddy growth parameter used is tiller number. Tillering in paddy is an important agronomic trait for grain production[12]. In this study, tillers that grow on the main stem of a paddy are calculated directly every 3 days during one SRI cultivation season. Paddy (Ciherang sp.) was cultivated in Bogor, Indonesia (S ; E ) with an elevation of m above sea level (Figure 1). The location belongs to A rainfall type (very wet) with the general rainy season occurring from September to February[13]. This experiment was conducted between July 2 and October For cultivation, 12 pots containing silt loam soil (Table 1) were used. Water treatment used for this experiment are water table commonly used by local farmers (-12, -7, -3, -5, 0, +2 from soil surface)[14]. Mariotte tubes were utilized in cultivation pots and used as a simple water level controller). The detail of the mariotte tube can be seen in Figure 2. In this system, water flows due to the pressure head difference between water level point (A) inside the tube and at the tube water output point (B). This tube is equipped with air holes and the height of the inside air hole (C) will be parallel to the height of the pot water table[15] editor@iaeme.com

3 SRI Paddy Growth Simple Prediction Model Figure 1 Paddy cultivation Figure 2 Detail of water table control by mariotte tube Table 1 Soil properties Parameter Unit Value Sand % 27 Silt % 62 Clay % 11 Bulk density g/cc 0.55 Particle density g/cc 2.05 Soil moisture at pf 1 %Volume 71.0 Soil moisture at pf 2 %Volume 27.5 Soil moisture at pf 2.54 %Volume 21.1 Soil moisture at pf 4.2 %Volume editor@iaeme.com

4 N. A. I. Hasanah, B. I. Setiawan, C. Arif and S. Widodo In this study, water table set-point in treatment (h) and paddy age (t) were used as inputs model to predict the tiller number (N). The tiller number data used in the model building is the average of the tiller numbers from two observation pots in every water table treatment. The prediction model built using Table Curve 3D v4.0 software, a three dimensional curve fitting program[16]. This program combines a powerful surface fitter with the ability to find the ideal equation to describe three dimensional empirical data[17]. N, h, t data will be used as XYZ data in 3D surface. It will automatically fit using Table Curve 3D. Fitted equations will be listed using R 2 as the statistical criteria and equation number as simplicity criteria. A simple SRI paddy growth prediction equation will be chosen from that list. 3. RESULTS AND DISCUSSION The number of tillers in various water table treatments were investigated at the interval of 3 days from transplanting to harvesting time. In this study, the first tiller appear in 18 days after transplantation (DAT), because the tiller is usually counted after around 5 leaves develop within the rate 3-4 days/leaves[18]. The number of tillers then increase along with the paddy age, shown in Figure 3. Figure 3 Tiller number during one season s cultivation in various water table treatment The maximum tiller number was found between 63 to 72 DAT before subsequently decreasing due to tiller death. The results show that, water table treatments -5, -7, and -12 cm showed more tillers than another treatments. Better aeration conditions in the soil are expected to occur in those treatments, indicated by soil moisture values that are always below 0.71 m 3 /m 3. Meanwhile, saturation conditions are created in the water table treatments of 0 and +2 cm from the soil surface. The favorable conditions for growth in an unsaturated condition were allowed to complete more phyllochrons of growth, producing more tillers and roots, before the flowering phase[19]. In saturated conditions, there might be an appearance of aerenchyma in the root, an adaptation mechanism that allows plants to transport atmospheric oxygen to the underground organs to maintain aerobic respiration and to oxidize various reducing compounds in the rhizosphere[20]. The aerenchyma could decrease root nutrient absorption capacity needed in tiller production. A simple prediction function was found by using Table Curve 3D. A curve in 3 dimension was built using the following variable data: editor@iaeme.com

5 SRI Paddy Growth Simple Prediction Model a. Independent variables: water table (h) and paddy age (t) b. Dependent variables: tiller number (N) From analysis, there are 418 equations with 230 listed with R 2 more than 90% with various complexities. The simplest model found with the highest R is the multi polynomial model (5 order):, Detail value of coefficient a, b, c, d, e, f, g, h, i, j, and k and the surface fitting can be seen in Figure 4. Figure 4Tiller numbers during one season of cultivation in various water table treatments The following SRI paddy growth simple prediction model can be used as a farmer s guide when planning to apply different water tables in their land. However, it should be noted that the tiller number (SRI plant growth) prediction function could be different in another location. It is because other growth factors (x), such as soil nutrient and radiation, differ. Therefore, N is the function of h, t, and x and can be list as:,,.,., N(h,t) found in this study can be used in another location if then value is known. Another way is if there is a set tiller number data in certain water table applications, the tiller number production potential in the same location could also be predicted using this approach:,, Farmers can predict their potential yield if they are willing to change the water table in their field using this approach. Farmers scepticism of SRI cultivation (unflooding) method can also be addressed editor@iaeme.com

6 N. A. I. Hasanah, B. I. Setiawan, C. Arif and S. Widodo 4. CONCLUSION Tiller number is a paddy growth parameter that easy to measure. The number of tillers during one cultivation season increases along with the paddy age and differs in various water table treatment. A multi polynomial model (5 order) was found during analysis using Table Curve 3D. The equation works well in predicting SRI paddy growth in various water table set-points (R 2 = 0.95) and could be used as a model predicting approach in SRI paddy cultivation in different locations. ACKNOWLEDGEMENTS The authors would like to thank the Ministry of Research, Technology and Higher Education, Indonesia and especially to Directorate General of Resources for Science, Technology, and Higher Education for their support, by a grant under PMDSU research project Automation of Irrigation and Drainage to Improve the Productivity of Land and Water and Reduce Greenhouse Gas Emissions Factor. REFERENCES [1] Chapagain, T., Riseman, A. and Yamaji, E. Assessment of System of Rice Intensification (SRI) and Conventional Practices under Organic and Inorganic Managements in Japan. Rice Sci., 18(4), 2011, pp [2] Uphoff, N. The System of Rice Intensification (SRI) as A Methodology for Reducing Water Requirements in Irrigated Rice Production. International Dialogue on Rice and Water: Exploring Options for Food Security and Sustainable Environments, Los Banos, 2006, pp [3] Veeramani, P., Singh, R. D. and Subrahmaniyan, K. Study of Phyllochron - System of Rice Intensification (SRI) Technique. Agric. Sci. Res. J., 2(6), 2012, pp [4] Meena, R. S. and Jha, R. Approximating Soil Physical Properties Using Geo-statisticals Models in Lower Kosi Basin, of Ganga River System, India Prone to Flood Inundation. International Journal of Civil Engineering and Technology (IJCIET), 8(5), 2017, pp [5] Arif, C., Mizoguchi, M., Setiawan, B. I. and Watanabe, T. Determining Optimal Soil Moisture for Irrigated Rice in Indonesia with System of Rice Intensification. The 12th Conference of International Society of Paddy and Water Environment Engineering: Agricultural water and rural environment for the future, Cheongju, 2013, pp [6] Talpur, M. A., Changying, J., Junejo, S. A., Tagar, A. A. and Ram, B. K. Effect of different water depths on growth and yield of rice crop. African J. Agric. Res., 8(37), 2013, pp [7] Pelletier, V., Gallichand, J., Gumiere, S., Pepin, S. and Caron, J. Water table control for increasing yield and saving water in cranberry production. Sustainability, 7(8), 2015, pp [8] Setiawan, B. I., Imansyah, A., Arif, C., Watanabe, T., Mizoguchi, M. and Kato, H. Effects of Groundwater Level on CH4 and N2O emissions under SRI Paddy Management in Indonesia. Taiwan Water Conserv., 61(4), 2013, pp [9] Kore, J. R., Nimbalkar, P. T. and Priyahirave. Crop Water Requirements and Irrigation Scheduling of Some Selected Crops Using Cropwat 8.0: A Case Study of Khadakwasla Dam Irrigation Project. International Journal of Civil Engineering and Technology (IJCIET), 8(5), 2017, pp [10] Kahimba, F. C., Kombe, E. E. and Mahoo, H. F. The Potential of System of Rice Intensification (SRI) to Increase Rice Water Productivity: a Case of Mkindo Irrigation Scheme in Morogoro Region, Tanzania. Tanzania J. Agric. Sci., 12(2), pp , editor@iaeme.com

7 SRI Paddy Growth Simple Prediction Model [11] Gupta, P. V. K., Reddy, J. P., Saradhi, T. P., Kedarnath, P. and Ramana, K.V. Water Pumping System for Inundated Agricultural Fields. International Journal of Mechanical Engineering and Technology (IJMET), 8(5), 2017, pp [12] Li, X., Qian, Q., Fu, Z., Wang, Y., Xiong, G., Zeng, D., Wang, X., Liu, X., Teng, S., Hiroshi, F., Yuan, M., Luo, D., Han, B., Li, J.Control of Tillering in Rice. Nature, 422, 2003, pp [13] Pratiwi, Santoso, E. and Turjaman, M. Karakteristik Habitat Pohon Penghasil Gaharu di Beberapa Hutan Tanaman di Jawa Barat (Habitat Characteristics of Gaharu Inducing Tree Species (Aquilaria spp.) in Several Forest Plantations in West Java). Info Hutan, 7(2), 2010, pp [14] Hasanah, N. A. I., Setiawan, B. I., Arif, C. and Widodo, S. Evaluasi Koefisien Tanaman Padi Pada Berbagai Perlakuan Muka Air (Crop Coefficient Evaluation at Various Water Table Treatments of Paddy). Irigasi, 10(2), 2015, pp [15] Thorel, L., Favraud, C. and Garnier, J. Mariotte Bottle in a Centrifuge : a Device for Constant Water Level. Int. J. Phys. Model. Geotech., 1, 2002, pp [16] Systat. Table Curve 3D: Automated Surface Fitting and Equation Discovery. Calivornia: Systat Software Inc., 2017, pp [17] Yip, C., Wong, Y. and Dessy, R. E. Successful Surface Fitting. Anal. Chem., 66(18), 1994, pp [18] Constantino, K. P., Gonzales, E. J., Lazaro, L. M., Serrano, E. C. and Samson, B. P. Plant Height Measurement and Tiller Segmentation of Rice Crops Using Image Processing.Proceedings of the DLSU Research Congress, Manila, 3, 2015, pp [19] Hidayati, N., Triadiati, and Anas, I. Photosynthesis and Transpiration Rates of Rice Cultivated Under the System of Rice Intensification and the Effects on Growth and Yield. Hayati J. Biosci., 23(2), 2016, pp [20] Pezeshki, S. R. and DeLaune, R. D. Soil Oxidation-Reduction in Wetlands and Its Impact on Plant Functioning. Biology (Basel)., 1(3), 2012, pp editor@iaeme.com