Spatial regression analysis on influence factors of maize lodging stress

A regression model was applied to analyze the reason causing the spatial distribution of maize lodging in the main maize-growing areas, in order to guide the promotion of new maize varieties. Multivariate stepwise regression method was adopted in this study to select the decisive factors of maize lodging in the Huang-Huai-Hai summer maize area. The aim was to figure out whether there was spatial nonstationarity and spatial dependence between the lodging stress and its relative determinants by comparing with the analysis results from the ordinary least squares linear regression model and geographically weighted regression model. The results demonstrated that geographically weighted regression model was better than the ordinary least squares linear regression model when analyzing the special heterogeneity of maize lodging; Daily precipitation was the main environmental determinant of maize lodging stress and it had a positive influence on maize lodging stress; The relationships of soil nitrogen content, planting density and daily average wind speed changed with space position positively and negatively; Therefore analyzing the causes of maize lodging stress according to the local conditions is necessary for providing an objective and effective guidance of plant production to farmers.