Regional growth model for summer maize based on a logistic model: Case study in China

The growing degree days (GDD) is an important factor for crop growth because it affects dry matter formation and crop yield. In this study, the universal logistic models were established employing GDD and the relative GDD (RGDD) as the main parameters to characterize summer maize growth indices such as plant height (H), leaf area index (LAI), and dry matter accumulation (DMA). The relationships were analyzed between the growth indices, harvest index (HI), water consumption, and yield in maize. By considering China as an example, the results showed that the logistic model performed well at simulating the changes in the summer maize growth indices in different regions and the universal model parameters were within specific ranges. Furthermore, the logistic model with RGDD as the independent variable was more suitable for modeling summer maize growth in large areas than GDD. The relationship between the maximum LAI and HI was described by a quadratic polynomial function. HI was optimal (0.53) when the maximum LAI was about 5.13. The maximum LAI, maximum H, and maximum DMA could be described by a quadratic polynomial function of water consumption during the growing season. The summer maize yield could be predicted with a binary quadratic equation using the maximum GDD and water consumption. This study confirmed that a logistic model can be used to establish a universal growth model for summer maize in large areas. Reasonable ranges of parameters were recommended for the logistic model, as well as the reasonable water consumption and each growth index value for summer maize. These results will be helpful for predicting the growth and yield of summer maize.