mahdi mokari; Meysam Abedinpour; hadi dehghan
Abstract
Presently, the main challenge of agricultural sector is improvement of crop water productivity (CWP). To evaluate the effect of water stress and planting date on grain yield, water productivity and yield components of wheat (Pishgam var.), an experiment was conducted as split plot based on complete ...
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Presently, the main challenge of agricultural sector is improvement of crop water productivity (CWP). To evaluate the effect of water stress and planting date on grain yield, water productivity and yield components of wheat (Pishgam var.), an experiment was conducted as split plot based on complete randomized design with three replications, at Kashmar Agricultural Research Station, in 2018-2019. Irrigation treatments included 100% of irrigation water requirement (IWR), 80% IWR, 60% IWR, and 40% IWR as the main treatments, and three planting dates including 23rd September, 23rd October and 23rd November as sub treatments. The results showed that water stress had significant effect on grain yield, water use efficiency (WUE), and harvest index (HI) at 1% probability level, such that with increasing water stress, the grain yield, HI and WUE was decreased. Also, the results showed that the effect of sowing date on grain yield, thousand kernel weight, and number of kernels per panicle, HI, and WUE was significant. The highest values of grain yield, HI, and WUE were 7227.33 kg/ha, 32.77 %, and 2.51 kg/m3, respectively, and belonged to 23rd October and 100% IWR treatment. The lowest of these values were 2000 kg/ha, 15.3%, and 1.14 kg/m3, respectively, related to 23rd November and 40% IWR treatment. The interaction between water stress and planting date had significant effect on all agronomic traits, except the number of kernels per panicle and WUE. According to the results of this study, irrigation treatment of 100% IWR and planting date of 23rd October can be considered for autumn wheat cultivar (Pishgam var.) in arid and semi-arid region of Kashmar.
Meysam Abedinpour; hadi dehghan; mahdi mokari; hadi Memarian
Abstract
This study was conducted to simulate water balance components at field scale, predict soil moisture profile, and grain yield in irrigated wheat fields in Neyshabur plain. In this regard, three farms were selected in different parts of the plain. AquaCrop input data including air, soil, and crop parameters ...
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This study was conducted to simulate water balance components at field scale, predict soil moisture profile, and grain yield in irrigated wheat fields in Neyshabur plain. In this regard, three farms were selected in different parts of the plain. AquaCrop input data including air, soil, and crop parameters were collected at each farm separately, then, the required model parameters and wheat crop data were calibrated. Root mean square error (RMSE), model efficiency (EF) and prediction error (Pe) were used to evaluate the model performance. The results of moisture simulation in soil profile showed that the model correctly simulated moisture content at different depths and times. The statistical parameters used for evaluating efficiency of the model at the calibration stage for simulating soil moisture in all farms were 0.027<RMSE<0.032, 0.80<EF<0.91, and 3.5<Pe<14%. These values at model validation stage were 0.025<RMSE<0.031, 0.82<EF<0.94, and 2.7<Pe<12%. The minimum and maximum percentages of model simulation error for grain yield and water productivity in all farms managed by the farmers were 4-8.8% and 4.6 to 9%, respectively. According to the results of the research, AquaCrop model can simulate soil moisture content, grain yield, and water productivity with acceptable accuracy under similar field conditions.
Hadi Dehghan; mahdi mokari; Meysam Abedinpour
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 ...
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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.
mahdi mokari; hadi dehghan; Meysam Abedinpour
Abstract
The simultaneous effect of salinity and drought stress are among the major factors that limit agricultural production in many parts of the world, especially in arid and semi-arid regions. Accordingly, a greenhouse research was carried out to study the simultaneous effect of salinity and water stress ...
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The simultaneous effect of salinity and drought stress are among the major factors that limit agricultural production in many parts of the world, especially in arid and semi-arid regions. Accordingly, a greenhouse research was carried out to study the simultaneous effect of salinity and water stress on yield and yield components of turnip (Purple Top White Globe var.) in Kashmar region. The experiment was performed as factorial arrangement in completely randomized design with three replications including two factors; salinity and irrigation water volume. Treatments consisted of four levels of water salinity (S1=0.7, S2=4, S3=8 and S4=12 dS/m) and three levels of water (W1=100%, W2=75% and W3=50 percent of water requirement), which were applied in a sandy-loam soil texture. The results showed that effects of salinity and water stress and their interaction were significant on biomass, shoot wet biomass, tuber and leaf dry weight (P<0.01). W1S1 and W2S1 treatments had higher biomass than the others. In all of the salinity levels, there was no significant difference between biomass in W1 and W2 irrigation levels. Based on the results of this research it could be concluded that turnip is more sensitive to salinity stress than drought stress. In other words, the results showed that the best level of salinity to reach the maximum biomass was S1. Therefore, the best treatment recommended for turnip planting in Kashmar region is W2S1.