Micro computed tomography analysis of barley during the first 24 hours of germination.

Abstract

Background Grains make up a large proportion of both human and animal diets. With threats to food production, such as climate change, growing sustainable and successful crops is essential to food security in the future. Germination is one of the most important stages in a plant's lifecycle and is key to the success of the resulting plant as the grain undergoes morphological changes and the development of specific organs. Micro-computed tomography is a non-destructive imaging technique based on the differing x-ray attenuations of materials which we have applied for the accurate analysis of grain morphology during the germination phase. Results Micro Computed Tomography conditions and parameters were tested to establish an optimal protocol for the 3-dimensional analysis of barley grains. When comparing optimal scanning conditions, it was established that no filter, 0.4 degrees rotation step, 5 average frames, and 2016 × 1344 camera binning is optimal for imaging germinating grains. It was determined that the optimal protocol for scanning during the germination timeline was to scan individual grains at 0 h after imbibition (HAI) and then the same grain again at set time points (1, 3, 6, 24 HAI) to avoid any negative effects from X-ray radiation or disruption to growing conditions. Conclusion Here we sought to develop a method for the accurate analysis of grain morphology without the negative effects of possible radiation exposure. Several factors have been considered, such as the scanning conditions, reconstruction, and possible effects of X-ray radiation on the growth rate of the grains. The parameters chosen in this study give effective and reliable results for the 3-dimensional analysis of macro structures within barley grains while causing minimal disruption to grain development.

Plant phenotyping relevance

大麦の発芽中の穀粒形態を対象に、マイクロCTの撮像条件・再構成・放射線影響を検討し、3次元形態解析プロトコルを開発・検証しているため。

Code and data availability

The paper's µ-CT datasets of germinating barley grains are held in the Sheffield Hallam SHURA repository but are only available on request from the corresponding author; no public URL, code, or trained models are provided. Other URLs in the article are cited references or generic databases, not paper-specific assets.

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