Determination of Water-Salinity-Yield Production Function for Spinach Plant

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Due to the quantitative and qualitative decline of groundwater resources, it is essential to optimize the water use in agriculture. One of the methods to optimize water use in agriculture, especially in arid and semi-arid regions, is to use yield-water-salinity functions. Therefore, this study was performed for prediction of spinach yield and yield components and determination of optimal production function under salinity and water stress conditions in Kashmar region, Iran. A factorial experiment was performed in a completely randomized block design with four replications including three salinity levels (i.e. S1= 0.75, S2=4, S3= 8 dS/m) and three levels of irrigation (including full irrigation (100% of water requirement)) = I1, I2=75% I1, and I3= 50% I1). Yield and yield components data of spinach (including leaf area, plant height, stem height, root length, plant dry weight, and root dry weight) were fitted to different production functions including simple linear, Cobb-Douglas, quadratic, and transient models. Optimal production function of spinach was determined after determining the coefficients of different functions. To evaluate different functions, the statistical indices of normalized mean square error, mean absolute error, modeling efficiency, agreement index and explanation coefficient were used. The results showed that the coefficient of determination (R2) for estimation of the biomass weight by quadratic, transcendental, simple linear, and Cobb-Douglas functions were 0.938, 0.890, 0.888 and 0.867, respectively. Most of the values of normalized mean square error and mean absolute error belonged to the simple linear functions and Cobb- Douglas. According to the results of this research, the quadratic production function is recommended as the optimal production function for yield and yield components of spinach.
Language:
Persian
Published:
Journal of Water Research in Agriculture, Volume:34 Issue: 1, 2020
Pages:
79 to 91
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