Assessment of genotypes and management strategies to improve resilience of winter wheat production

Abstract

Climate is a main factor that influences the winter wheat production. Changing the crop cultivars and adjusting the sowing dates are used as strategies to adapt to climate change. First, we evaluated the simulation ability of the Decision Support System for Agro-technology Transfer (DSSAT) CERES wheat model based on the experimental data with varied sowing dates and cultivars. Second, we designed optimal cultivars in three different environmental conditions with the highest grain yield in the North China Plain (NCP) based on model sensitivity analysis. Furthermore, we optimized the sowing dates for three sites with the above-derived cultivar parameters. The results showed that the DSSAT-CERES wheat model was suitable for winter wheat simulation after calibration and validation with a Normalized Root Mean Square Error (NRMSE) between 0.9% and 9.5% for phenology, 6.8% and 17.8% for above ground biomass, and 4.6% and 9.7% for grain yield. The optimal cultivars significantly prolonged the wheat growth duration by 14.1, 27.5, and 24.4 days at the Shangzhuang (SZ), Xingtai (XT), and Zhumadian (ZMD) sites compared with current cultivars, respectively. The vegetative growth duration (from sowing to anthesis) was prolonged 18.4 and 12.2 days at the XT and ZMD sites significantly, while shortened 0.81 days at the SZ site. The grain yield could be potentially improved by 29.5%, 86.8%, and 34.6% at the SZ, XT, and ZMD sites using the optimal cultivars, respectively. Similarly, the improvement of aboveground biomass at three sites was 5.5%, 47.1%, and 12.7%, respectively. Based on the guaranteed rate and analysis of variance, we recommended a later sowing date (from 15 September to 20 October) at the SZ and ZMD sites, and 15 September to 15 October at the XT site. In addition, the methodology of this study could be expanded to other regions and possibly to other crops.