Analysis of kernel dry down process after physiological maturity of spring maize based on diffusion theory in the North China

Mechanical grain harvesting (MGH) can significantly improve the production efficiency of Maize. Therefore, MGH is the development direction of maize production. The moisture content of grain after physiological maturity (MCAM) is the key to the quality of MGH, which is affected by variety, density and climate. Accurately estimating MCAM, analysis the main influencing factors, and finally determining the harvest time of maize and selecting the appropriate harvest varieties, are of great significance to the development of corn harvest in North China. Therefore, in 2017 and 2018, field spring maize experiments were carried out in Botou, Nandagang, Yutian of Hebei Province and Yuci of Shanxi Province for two years. Seven common varieties and three densities of each variety were set up every year to monitor MCAM, variety characteristics, meteorological data and managements. The results showed that the model based on diffusion theory can simulate MCAM well. The year, site and variety had a significant influence on the moisture content at physiological maturity (M0) and the moisture diffusion rate (k) which are parameters of the model. Stepwise linear regression analysis showed that ET0, the maximum temperature and the amount of irrigation had significant positive effects on M0. ET0 during 30 days after physiological maturity and the rainfall in the middle-late grain-filling stage had significant positive effects on k, and rainfall during the whole growth period had significant negative effects on k. The number of bract layers is the most influential to M0 (positive effect), and the number of leaves is the most influential to k (negative effect). According to the model calculation, the MCAM can be reduced to 28% almost in all the circumstances and the MCAM can be reduced to 25% in half of the circumstances at 10 days after physiological maturity. The area under the dry down curve (AUDDC) within 10 days after physiological maturity of each variety was calculated by the model. Compared with the average AUDDC, it was found that Jingnongke 728, Zhang1453, Huanong 887, Guangde 5 and Jinkeyu 3306 were the varieties with excellent dry down performance.