The increased frequency of climate extremes associated with ongoing climate change has the potential for significant impacts on maize grain yield in maize-producing regions worldwide. In this study, we used a modeling approach to investigate the effects of different types of climatic extremes on maize grain yield in Northeast China. We combined annual mean air temperature and accumulated precipitation data and divided the climate years into 9 categories, using the 10th and 90th percentiles as extreme thresholds. The climate data were represented by 1 normal climate type, 4 individual climate extremes, and 4 combined climate extremes. Changes in the frequencies of climate extremes and their impacts on maize grain yields were analyzed for two 30-year periods (period I: 1960–1989; period II: 1990–2019) using the Agricultural Production Systems sIMulator (APSIM-Maize). Compared with period I, the occurrences of the normal climate and all 3 cold-related climate extremes (i.e., cold-normal, cold-humid, and cold-dry) decreased during period II, while occurrences of the other climate extremes increased. Moreover, according to the APSIM-Maize model, the estimated yield in the years with a normal climate decreased by 4.01%; the 3 cold-related climate extremes increased yields by 26.56%, 12.10%, and 6.68%, respectively; the 2 warm-related climate extremes (warm-normal and warm-dry) and normal-humid years decreased estimated yields by 6.39%, 24.12%, and 5.10%, respectively. The increase in the occurrence of warm-humid years increased the estimated yield by 11.69%. This work confirms the adverse effects of warmer temperatures in the absence of excess rainfall on grain yield and highlights the importance of extremely dry or wet conditions under normal temperature conditions.

The reasonable assessment of maize varieties in different ecological regions can allow temperature resources to be fully exploited and reach the goal of high yield and efficiency and is thus an important direction of modern maize development in China. In this study, a logistic power nonlinear growth model was used to simulate the accumulated temperature required for kernel dehydration to moisture contents of 25%, 20%, and 16% for various maize cultivar, which were divided into six types based on the accumulated temperature required for kernel dehydration to a moisture content of 25%. The relationship between the yield of maize cultivars and the accumulated temperature required for kernel dehydration to a moisture content of 25% was found to follow a unary function model. Changing the planted maize variety was found to increase economic returns by more than 7000 RMB/hm2 in Ningxia, Northwest China. Under the conditions of mechanical grain harvesting, economic benefits can be further increased by means of selecting high yields and fast-dehydrating varieties, selling when the grain dehydration is below 16%. A better way to achieve grain dehydration to a moisture content below 16% is to postpone the harvest date as much as possible rather than drying after the harvest at physiological maturity. The areas of various types of maize varieties can be dehydrated to moisture contents of 25%, 20%, and 16% were marked. Based on the distribution of heat resources in different regions of Ningxia from the normal sowing date to October 31 before winter irrigation, the appropriate cultivars for various regions in the province were determined based on production benefits. Therefore, in different areas of Ningxia, selecting suitable maize varieties according to temperature resources can reach a high yield and mechanical kernel harvesting, and ultimately obtain higher economic benefits. Keywords: maize, dehydration, grain yield, economic return, mechanical kernel harvesting DOI: 10.25165/j.ijabe.20201401.6035 Citation: Li H Y, Wang Y H, Xue J, Xie R Z, Wang K R, Zhao R L, et al. Allocation of maize varieties according to temperature for use in mechanical kernel harvesting in Ningxia, China. Int J Agric & Biol Eng, 2021; 14(1): 20–28.