Prediction of sugar beet yield and quality parameters with varying nitrogen fertilization using ensemble decision trees and artificial neural networks

•Sugar beet nitrogen fertilization was optimized using leaf nutrient status samples.•Root yield and yield quality parameters were used as training and test data.•Ensemble decision trees and artificial neural network regression were used.•Na had high variable importance for root yield and sucrose content.•The top accuracy had a median R2 of 0.927 and ranged from 0.842 to 0.998.