Simulating Sugarcane Elongation by a Multi-Parameter Generalized Logistic Model with Meteorological Effect

Abstract

Sugarcane is a raw material used to produce sugar and ethanol. Its growth is influenced by meteorological factors. This study aimed at providing a modeling framework to simulate sugarcane stalk elongation by considering the planting stage and meteorological factors. Using plant height data and meteorological data collected in Guangxi (China) during 2018–2022, combined with the cumulative temperature function, a multi-parameter generalized logistic model was constructed to simulate changes in plant height for spring planting and ratoon sugarcane. The meteorological effects on sugarcane growth were further quantified. Expressions of six models simulating sugarcane growth were given by fitting the data. The results showed that the selected model could simulate the elongation period of sugarcane well, and it simulated Guitang No. 42 sugarcane most effectively. Sensitivity analysis showed that effective cumulative temperature and cumulative precipitation had the greatest influence on sugarcane growth and growing duration. It was also found that increasing rainfall to the optimum level in August was the most favorable for sugarcane growth.