Fig. 6From: High-throughput phenotyping for non-destructive estimation of soybean fresh biomass using a machine learning model and temporal UAV dataThe importance of each predictor variable in (a) random forest (RF) and (b) partial least squares regression (PLSR) model for prediction of soybean fresh biomass (FB). Canopy cover – CC, plant height – PH, triangular greenness index – TGI, and green chlorophyll index – GCIBack to article page