The deep learning approach combined with spectroscopic sensing techniques has shown great potential for quality evaluation of food and agro-products. Current advances in deep learning-based qualitative analysis include variety identification, geographical origin detection, adulteration recognition, and bruise detection, whereas quantitative analysis includes multiple component content prediction for fruits, grains, and crops. The main advantage of deep learning approach is the decreasing the dependence on human domain knowledge by end-to-end analysis and the improved precision and...