High throughput phenotyping of morpho-anatomical stem properties using X-ray computed tomography in sorghum.

Abstract

BACKGROUND: In bioenergy/forage sorghum, morpho-anatomical stem properties are major components affecting standability and juice yield. However, phenotyping these traits is low-throughput, and has been restricted by the lack of a high-throughput phenotyping platforms that can collect both morphological and anatomical stem properties. X-ray computed tomography (CT) offers a potential solution, but studies using this technology in plants have evaluated limited numbers of genotypes with limited throughput. Here we suggest that using a medical CT might overcome sample size limitations when higher resolution is not needed. Thus, the aim of this study was to develop a practical high-throughput phenotyping and image data processing pipeline that extracts stem morpho-anatomical traits faster, more efficiently and on a larger number of samples. RESULTS: A medical CT was used to image morpho-anatomical stem properties in sorghum. The platform and image analysis pipeline revealed extensive phenotypic variation for important morpho-anatomical traits in well-characterized sorghum genotypes at suitable repeatability rates. CT estimates were highly predictive of morphological traits and moderately predictive of anatomical traits. The image analysis pipeline also identified genotypes with superior morpho-anatomical traits that were consistent with ground-truth based classification in previous studies. In addition, stem cross section intensity measured by the CT was highly correlated with stem dry-weight density, and can potentially serve as a high-throughput approach to measure stem density in grass stems. CONCLUSIONS: The use of CT on a diverse set of sorghum genotypes with a defined platform and image analysis pipeline was effective at predicting traits such as stem length, diameter, and pithiness ratio at the internode level. High-throughput phenotyping of stem traits using CT appears to be useful and feasible for use in an applied breeding program.

Plant phenotyping relevance

CT撮像と画像解析パイプラインを開発し、ソルガム茎の形態・解剖学的形質を高スループットに抽出・検証しているため、フェノタイピング手法が中心である。

Code and data availability

The paper's MATLAB image analysis algorithm and CT-derived datasets are not publicly deposited; the authors state they are available only on reasonable request. No public paper-specific asset URL is provided (the terraref.org link refers to an unrelated project).

No evidence-backed public reproduction asset is currently recorded.