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.

Plant phenotyping relevance

成熟コムギ粒のタンパク質分布を画像処理で定量する切片作製法と深層学習アルゴリズムを開発し、化学分析との相関で検証しており、表現型取得・抽出法が研究の中心である。

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