Fresh corn yield prediction based on GA-BP neural network

Fresh corn has attracted much attention because of its advantages such as rich nutrition, wide use and large market potential. At present, the fresh corn planting area in China is gradually expanding, and the efficient prediction of fresh corn yield is of great significance to make accurate management decisions during its growth period. Aiming at the problems of low testing accuracy and poor robustness of traditional BP neural network in yield prediction, the BP neural network model is optimized by using Genetic Algorithm（GA） and the GA-BP neural network model is constructed. In this study, based on meteorological factors（atmospheric humidity, atmospheric temperature, rainfall）, field water and heat factors and fresh maize yield obtained from field IOTs during 2010—2021 at the South Asia Institute of Tropical Crops in Guangdong Province, BP neural network, GA-BP neural network model and PSO（particle swarm optimization algorithm） were used to predict and correlate the fresh maize yield in the selected areas. The results showed that the fresh maize yield was significantly correlated with monthly minimum soil temperature, monthly average soil temperature, monthly maximum atmospheric temperature and monthly average atmospheric humidity. and the correlation coefficients was higher than 0.8, and the correlation coefficient was significantly correlated with monthly maximum temperature, monthly average soil water content, monthly average atmospheric temperature and monthly rainfall, and the correlation was weak with monthly minimum atmospheric temperature, as shown by Pearson correlation coefficients. The accuracy of the GA-BP neural network model was significantly higher than that of the PSO-BP and BP neural network models, with R~2 reaching 0.956 4 and a high degree of fit between the predicted and experimental values. Therefore, the GA-BP neural network model can be used to predict the yield of fresh corn more scientifically and rationally, which is an important guidance for the adjustment of fresh maize production and management measures.