Integrated Growth Model of Typical Crops in China with Regional Parameters

The analysis of common properties of growth for crops is the basis for further understanding crop growth in different regions. We used four typical crops of China, winter wheat, summer maize, rice, and cotton, to build an integrated model suitable for simulating the growth of different crops. The rates and characteristics of crop growth were systematically analysed based on semirelative and fully relative logistic models of crop growth, and a comprehensive, fully relative logistic model for the four crops was established. The spatial distributions of the maximum leaf area index (LAI(max)) and maximum dry-matter accumulation (DMA(max)) for the four crops were analysed. The semirelative and fully relative growth models exhibited different characteristics of crop growth. The essential characteristics of growth and the characteristics of the crops at each stage of growth were better represented by the fully relative logistic growth model than by the semirelative model. The comprehensive, fully relative logistic model fitted the growth of all four crops well. LAI(max) and DMA(max) varied greatly amongst the four crops and were strongly regionally distributed. These indicators for the same crop were differentially spatially variable, and the two indicators were not significantly correlated, except for rice. LAI(max) and DMA(max) in different regions could be obtained using a binary quadratic equation of water consumption and growing degree days for the crops. This study provides a novel method for quantitatively judging the status of crop growth, predicting crop yields, and planning for regional agricultural planting.

Automated summary

The analysis of common growth properties among crops is crucial for understanding crop growth in different regions. In this study, a comprehensive model was developed to simulate the growth of four typical crops in China: winter wheat, summer maize, rice, and cotton. The rates and characteristics of crop growth were examined using semirelative and fully relative logistic models, and a comprehensive logistic model was established. The spatial distribution of key growth indicators, such as maximum leaf area index (LAI(max)) and maximum dry-matter accumulation (DMA(max)), were analyzed for the four crops. The results showed that the fully relative logistic model better represented the essential characteristics of growth and the characteristics of the crops at each stage of growth compared to the semirelative model. The comprehensive logistic model successfully fitted the growth of all four crops. LAI(max) and DMA(max) varied greatly among the crops and showed strong regional distribution. These findings provide a novel method for quantitatively assessing crop growth, predicting yields, and planning agricultural planting at a regional scale.