Enhancing wheat quality through color sorting: a novel approach for classifying kernels based on vitreousness

Wheat is a major food crop used in producing bread, noodles, and cookies. Kernel vitreousness, closely related to protein content, is key to determining wheat's processing purpose. Traditionally, vitreousness is visually assessed, but studies on classifying vitreous and starchy kernels to improve quality are limited.

This study expands the use of a commercial color sorter to classify kernel vitreousness by G value, distinguishing vitreous from starchy kernels.

The system improved protein content and bread-making quality by classifying vitreous kernels, while reducing variability across 23 samples collected over four years. An industrial field test confirmed its applicability at scale. Genetic and environmental factors were also examined, revealing that varietal differences and flowering time were not significant contributors to variations in vitreousness. The findings suggest that color sorting is a reliable tool for enhancing wheat quality until more environmentally stable cultivars are developed, providing economic benefits through improved and consistent product quality.