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Optimizing genotype-environment-management interactions to ensure silage maize production in the Chinese Maize Belt

Liangliang Zhang, Zhao Zhang*, Juan Cao, Yuchuan Luo, Ziyue Li

*Corresponding author:

ABSTRACT: Grain maize production exceeds the demand for grain maize in China. Methods for harvesting good-quality silage maize urgently need a theoretical basis and reference data in order to ensure its benefits to farmers. However, research on silage maize is very limited, and very few studies have focused on its energetic value and quality. Here, we first calibrated the CERES-Maize model for 24 cultivars with 93 field experiments and then performed a long-term (1980-2017) simulation to optimize genotype (G)-environment (E)-management (M) interactions in the four main agroecological zones across China. We found that CERES-Maize could reproduce the growth and development of maize well under various management and weather conditions with a phenology bias of < 5 days and biomass RRMSE values of < 5%. The simulated results showed that sowing long-growth-cycle cultivars approximately 10 days in advance could yield good-quality silage. The optimal sowing dates (from late May to July) and harvest dates (from early October to mid-November) gradually became later from north to south. A high energy yield was expected when sowing at an early date and/or with late-maturing cultivars. We found that Northeast China and the North China Plain were potential silage maize growing areas, although these areas experienced a medium or even high frost risk. Southwestern maize experienced a low risk level, but the low soil fertility limited the attainable yield. The results of this paper provide information for designing an optimal G×E×M strategy to ensure silage maize production in Chinese Maize Belt.