Improving breadmaking quality of winter wheat using single kernel NIR protein sorting

Abstract

Near-infrared (NIR) spectroscopy predictions are routinely employed in the cereal and milling industries to ensure technological and sanitary quality. Devices capable of predicting and sorting wheat batches at the single kernel (SK) level have been developed for industrial application. This study aimed to characterize the impact of different winter wheat grades, sorted based on SK-NIR-predicted protein content, on rheological and end-use pan-bread quality. Unsorted, low, and high protein content fractions were analysed for grain, flour, dough, and bread technological quality. The results indicated a significant increase in all protein-related grading analyses, such as the Zeleny sedimentation index, flour protein content, wet gluten content, maximum torque of glutopeak, baking strength, dough water absorption, and stability, suggesting a stronger gluten network. Breadmaking trials further confirmed this impact on end-use product quality, with an increase in bread specific volume and modification of the texture profile. Pre-sorting based on protein quality grading demonstrates that higher quality breadmaking wheat should be selected for sorting to produce specialty flour while still valorizing the remains. In conclusion, SK-NIR sorting for high-protein bread-wheat production in challenging or low-input contexts is a mature technology for sustainable production and processing in the cereals industry.