Classification of Proso Millet (Panicum miliaceum L.) Seeds Based on Physical and Nutritional Approaches Through Machine Learning and Data Mining Algorithms

The notion that morphometric signatures and decision based on NIR-based compositional data have some synergy in proso millet can be utilized to offer an applicable, repeatable, and cost-effective decision framework to address critical processes including the control of seed purity, quick verification of variety, and quality classification is supported.