Novel models for simulating maize growth based on thermal time and photothermal units: Applications under various mulching practices - Zhen-qi LIAO; Jing ZHENG; Jun-liang FAN; Sheng-zhao PEI; Yu-long DAI; Fu-cang ZHANG; Zhi-jun LI (Journal of Integrative Agriculture, 2023)
Maize (Zea mays L.) is one of the three major food crops and an important source of carbohydrates for maintaining food security around the world. Plant height (H), stem diameter (SD), leaf area index (LAI) and dry matter (DM) are important growth parameters that influence maize production. However, the combined effect of temperature and light on maize growth is rarely considered in crop growth models. Ten maize growth models based on the modified logistic growth equation (Mlog) and the Mitscherlich growth equation (Mit) were proposed to simulate the H, SD, LAI and DM of maize under different mulching practices based on experimental data from 2015–2018. Either the accumulative growing degree-days (AGDD), helio thermal units (HTU), photothermal units (PTU) or photoperiod thermal units (PPTU, first proposed here) was used as a single driving factor in the models; or AGDD was combined with either accumulative actual solar hours (ASS), accumulative photoperiod response (APR, first proposed here) or accumulative maximum possible sunshine hours (ADL) as the dual driving factors in the models. The model performances were evaluated using seven statistical indicators and a global performance index. The results showed that the three mulching practices significantly increased the maize growth rates and the maximum values of the growth curves compared with non-mulching. Among the four single factor-driven models, the overall performance of the MlogPTU Model was the best, followed by the MlogAGDD Model. The MlogPPTU Model was better than the MlogAGDD Model in simulating SD and LAI. Among the 10 models, the overall performance of the MlogAGDD–APR Model was the best, followed by the MlogAGDD–ASS Model. Specifically, the MlogAGDD–APR Model performed the best in simulating H and LAI, while the MlogAGDD–ADL and MlogAGDD–ASS models performed the best in simulating SD and DM, respectively. In conclusion, the modified logistic growth equations with AGDD and either APR, ASS or ADL as the dual driving factors outperformed the commonly used modified logistic growth model with AGDD as a single driving factor in simulating maize growth.