Statistical model for maize yield forecasting for Jilin province,China
Yield forecasting in advance is required for export planning and policy decisions. Maize is the staple food in many coun-tries and is grown in varied climates from pie-humid to semiarid areas. Simulation models were used to predict crop yield in many coun-tries, crop-weather models were also used, especially in India. In this paper, an attempt was made to predict maize yield in Jilin, China by including climate, soil and management factors and ten variables were selected. Twenty-three years (197911980-2003/2004) data were used for the study. The ten variables were subjected to stepwise regression analysis and only six predictors were retained in the final mod-el(ModellV) with an R2=0.919.The Model IV with minimum parameters Y=-72125.573+34.952X1+ 22.92X2 +72.48X5-24.008X6 + 1252.852X7-12.119X8 +20.975X9 (R2=0.919) can be used to predict maize yield in Jilin, China.
Statistical modelYield forecastingMaizeJilin Province
NETL
NSTL
万方数据
