Critical Evaluation of the Cgrain Value™ as a Tool for Rapid Morphometric Phenotyping of Husked Oat (Avena sativa L.) Grains

Abstract

Mechanised non-contact, non-destructive imaging methodologies have revolutionised plant phenotyping, increasing throughput well beyond what was possible using traditional manual methods. Quantifying the variation in post-harvest material such as seeds and fruits, usually the economically important part of the crop, can be critical for commercial quality assessment as well as breeding and research. Therefore, reliable methods that gather metrics of interest, quickly and efficiently, are of widespread interest across sectors. This study focuses on evaluating the phenotyping capabilities of the Cgrain Value™, a novel grain imaging machine designed for quality and purity assessment and used primarily in commercial cereal production and processing. The performance of the Cgrain Value™ in its generation of high-throughput quantitative phenotypic data is compared with a well-established machine, MARVIN, assessing repeatability and reproducibility across a range of metrics. The findings highlight the potential of the Cgrain Value™, and some shortcomings, to provide detailed three-dimensional size, shape, and colour information rapidly, offering insights into oat grain morphology that could enhance genome-wide association studies and inform the breeding efforts in oat improvement programmes.

Plant phenotyping relevance

オート麦種子の形態形質を取得する画像計測機器を対象に、既存機器との反復性・再現性を比較評価しており、フェノタイピング手法の技術検証が中心である。

Code and data availability

The supplied blocks contain no data availability, code availability, or supplementary-material statements. The paper describes Cgrain/MARVIN phenotyping of an oat mapping population, but no public dataset, images, analysis code, or model checkpoints are deposited or linked; machine code is explicitly proprietary and 'a

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