Orthogonal polynomial models to describe yield response of rice to nitrogen and phosphorus at different levels of soil fertility

Yield responses of rice (Oryza sativa L. cv JD1187)to variable rates and combinations of fertilizer nitrogen (N) and phosphorus(P), to available soil N and P, and to cation exchange capacity (CEC) wereexamined in 41 field trials. The trial sites were located in the rice-growingregion of Hebei Province, Northern China, covering a diversity of soilfertilitylevels. Relationships between crop yields, fertilizer rates and soil nutrientsupply were established using an orthogonal polynomial model. The optimumeconomic fertilizer rates at different levels of soil N and P supply wereestimated by using fertilizer-yield response functions and soil properties foraparticular site. A difference in trend coefficients, reflecting yield responseto fertilizer, was observed, which was mainly dependent on variance of soilfertility across 41 experimental sites under the relatively consistent climateand farming practice. The results of correlation analysis showed that there wasa positive correlation between trend coefficient T₀ and yieldwithoutfertilizer (Y₀) (r = 0.80**). Trend coefficientT₁, the major effect of N fertilizer on yield, showed negativerelationships with the quadratic transformation of alkali-hydrolysable N(N_s) and CEC (r = –0.60**). Trend coefficientT₂, the major effect of P fertilizer on yield, had negativerelationships with the logarithmically transformed data of soilNaHCO₃-extractable P (P_s) (r = –0.57**).Trend coefficients T₃, T₄ and T₅, representinglinear interaction of N and P, and quadratic trend of N and P, respectively,showed no significant correlation with soil fertility variables. Yieldresponsesto N and P fertilizers, optimum economic fertilizer rates and gross profit fromfertilization decreased with increase in available soil N and P, and CEC. Themodel was validated in 19 field trials. The results suggest that the modeldeveloped in this study can reasonably predict optimum economic fertilizerratesthrough routine soil tests in the rice production region. The model can also beextrapolated to other regions and include other variable factors, provided thatnew relationships between yield response to fertilizer and site variables areestablished and incorporated into the model.