Optimization of N and P fertilizer rates on yield and quality indices of wheat using a Response-Surface Methodology

Response surface methodology (RSM) is defined as statistical technique for optimization of multiple parameters which determine optimum process conditions by combining experimental treatments (5,10,11). In this work, optimization of N and P fertilizers on yield, yield components and seed quality of wheat using RSM were studied.
Materials and methods: An experiment was conducted with 13 treatments and two replications at the Research Field of Ferdowsi University of Mashhad during the growing season of 2015-2016. The treatments were allocated based on low and high levels of N fertilizer (0 and 400 kg Urea per ha, respectively) and P fertilizer (0 and 100 kg triple super phosphate per ha, respectively). Biological yield, seed yield, harvest index, growth criteria and yield components (such as tiller No./m2, plant height, spike length, seed No./ spike, seed weight/ spike, seed weight/ plant, spike No./ plant, spike weight/ plant and dry weight of stem per m2) and seed quality characteristics (including N percentage, protein percentage and P percentage) were calculated as dependent variables and changes of these variables were evaluated by a regression model. Lack-of-fit test was used to evaluate the quality of the fitted model. The adequacy of the model was tested by analysis of variance. The quality of the fitted model was judged using the determination coefficient (R2). Finally, the optimum levels of N and P fertilizers were calculated based on three scenarios including economic, ecological and economic-ecological.
Results and discussion: The results showed that effect of linear component was significant on harvest index, spike length, yield components (such as seed weight per plant, spike No./plant, spike weight per plant and tiller No./m2), N percent and protein percent of seed. Effect of square component was significant on biological yield, seed yield, tiller No./m2, seed weight per plant and spike weight per plant, N percent, protein percent and P percent of seed. Interaction effect of full quadratic was significant on plant height, spike length and seed No./spike and N percent of seed. Lack of fit test had no significant effect on the studied traits. The full square model for the response variables gave insignificant lack-of-fit indicating that the data of experimental were satisfactorily explained. The highest observed and predicted values of seed yield were recorded for 400 kg Urea per ha+100 kg triple super phosphate per ha and 200 kg Urea per ha+50 kg triple super phosphate per ha with 717.54 and 594.89 kg.ha-1, respectively. The maximum observed and predicted amounts of seed N percent (with 1.72 and 1.62 percent, respectively) and seed protein percentage (with 10.76 and 10.02percent, respectively) were recorded for 400 kg Urea per ha+50 kg triple super phosphate per ha. Both seed yield and N and P percent of seed were considered in economic-ecological scenario, so the estimated levels for N and P fertilizers were 141.41 kg Urea.ha-1 and without P fertilizer.
Conclusion: Increasing rates of N and P fertilizers up to optimum rates increased yield and seed quality of wheat. Nutrient optimization enhances nutrient absorption and yield in the wheat cropping systems may reduce the dependence on external sources of chemical fertilizers that increase the costs of production and can potentially contribute to environmental contamination. The optimization of soil nutrients provides information on the sustainability of cropping systems and potential environmental pollutions. Generally, nutrient optimization is a useful technique widely used in modern agriculture.