Statistical description of yield and yield components of wheat with soil physical, and chemical criteria using stepwise regression
Characterization of physical and chemical soil criteria is a key step in understanding the source of spatial variability in the productivity across agricultural fields (21). Crop yield variability can be caused by many factors, including spatial variability of soil texture, crop management, soil physical and chemical properties and nutrient availability (45). Understanding the spatial variability of soil physical and chemical characteristics is essential for crop management, as it is directly contributing to variability in growth and yield of crop (38 & 14). Hence, understanding their spatial variability across agricultural fields is essential in optimizing the application of agricultural inputs and crop yield and it could help significantly in managing the spatial variability in the productivity of soil agroecosystems (30 & 14). Therefore, the objectives of this study were: (i) evaluate the effect of soil physical and chemical criteria on yield indices of wheat and (ii) to investigate the correlation between physical and chmical soil properties and wheat yield.
Materials and Methods
Samplings were performed based on random-systematic method from 30 fields in Khorasan-e Razavi province during 2017 and 2018. Studied characteristics were texture, organic matter (OM), organic carbon (OC), total nitrogen (TN), available P, available K, pH and C:N ratio of soil and seed yield, biological yield, straw yield, 1000-seed weight and harvest index (HI) of wheat. Multiple regression model was used to identify the relationship between soil variables (independent variables) and wheat yield indices (dependent variables). In addition, determining the most important factors of soil physical and chemical properties which have on wheat yield criteria was done by stepwise regression analysis.
Results and discussion
The results revealed showed that the mean values of seed yield, straw yield, biological yield, 1000-seed weight and HI of wheat were observed with 3588.47 kg.ha-1, 7362.80 kg.ha-1, 10951.27 kg.ha-1, 35.40 g and 48.56%, respectively. The highest and the lowest standard errors were computed for biological yield (198.40) and 1000-seed yield (0.74), respectively. Also, The effect of soil textures was significant (p≤0.05) on soil chemical criteria and wheat yield. The maximum OM, OC, TN, available P, available K and pH were observed for sandy clay with 1.86%, 1.09%, 0.18%, 166.20 ppm, 0.05 ppm and 7.37, respectively. The maximum seed yield and biological yield were related for clay soil (with 4313.83 and 11924.86 kg.ha-1, respectively). The highest correlation coefficients were computed for OM (r=0.935**) and OC (r=0.933**) with 1000-seed weight. The most important factors influencing wheat yield by using step by step regression were OM, available P, TN and available K, respectively.
Longterm sustainability of agroecosystems depends on soil quality and its fertility. Poor soil management practices can lead to degraded soil and environmental quality and reduction in crop yields. Results suggest that novel management approaches are needed to maintain the longterm sustainability of soil resources and crop yields without seriously degrading the environment that this will help in reducing the cost of fertilization and improving soil and environmental quality without altering crop yields.
Article Type:
Research/Original Article
Electronic Journal of Crop Production, Volume:12 Issue: 1, 2019
143 - 160  
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