Optimize the irrigation and fertilizer schedules by combining DSSAT and genetic algorithm.

Abstract

As one of the main food crops in the world, the yield of maize directly affects the food security of the world. The optimization of irrigation and fertilizer schedules is also one of the hot issues in the world. However, the traditional optimization methods are mainly based on field experiment or crop model. The research on combining crop model with optimization algorithm to optimize irrigation and fertilizer schedule is rare. In this paper, the genetic algorithm (GA) and DSSAT crop model were combined to provide theoretical basis for the optimization of irrigation and fertilizer schedules of maize in China. On the basis of field experimental data in previous references, the model was calibrated and verified, and get a well simulation result with RMSE ranged from 0.262 to 0.580Mg/ha. After that, GA and DSSAT were run to obtain the optimized irrigation and fertilizer schedules. Compared with the results of previous references, the new optimization schedules can improve the yield (1.9 ~ 2.6%) and economic benefits (7.3 ~ 8.9%). It is proved that this method has a good optimization effect, and the method also has a wide range of research prospects.