Development of a rapid method for the determination of the spatial distribution of protein in wheat grain using mature resin section and image processing algorithm

Abstract

Slicing combined with image analysis offers a novel approach for protein quantification. However, preparing intact tissue sections and developing reliable algorithms for protein analysis remain major challenges in mature wheat grains. In this study, we developed a rapid resin sectioning method to obtain high-quality sections of mature wheat grains. The method is simple to perform, increases sectioning efficiency by at least 60 %, and reduces tissue-folding errors by over 90 %. Using a deep learning-based approach, we achieved automatic removal of background interference and high-throughput analysis of protein content. The protein area obtained through image analysis showed a strong correlation (r = 0.99) with protein content measured by chemical analysis. We developed an algorithm to identify spatial differences in endosperm proteins, which showed a strong correlation with the chemical analysis results (r = 0.80). The section preparation method combined with protein analysis algorithm was successfully applied to observe and quantify protein content in different scenarios. Overall, these findings establish a high-throughput method to quantify protein content in mature wheat grains with a spatial perspective from limited samples.

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