Recent advancements in hyperspectral imaging and machine learning have revolutionized the non-destructive monitoring of crop nutritional status, enabling accurate prediction of plant element concentrations. Despite successes, the single-target regression method, which predicts concentrations individually, faces accuracy limitations for certain elements.