Comparison of different machine learning algorithms for predicting maize grain yield using UAV-based hyperspectral images

Yahui Guo, Yi Xiao, Fanghua Hao, Xuan Zhang, Jiahao Chen, Kirsten M. de Beurs, Yuhong He, Yongshuo Fu

Abstract: Highlights•Machine learning and deep learning algorithms were performed and compared.•Proposing a new method for predicting maize yield using hyperspectral full spectra.•Two-band (2D) of RDVI were more sensitive with maize yield than RNDVI and RRVI.•Full spectra with Random Forest achieved highest accuracy for predicting maize yield.