A precise and high-throughput assay for stem structural characteristics deepens understanding of lodging resistance in sorghum.

Abstract

Background Plant stem structural characteristics are crucial factors determining plant lodging resistance, while high throughput methods for rapid surveys of these traits are still lacking in sorghum. Results Among 103 sorghum accessions, two kinds of stem powders (dry and water-washed) were subject to visible and near-infrared spectra acquisition, and 16 models (combinations) for stem structural characteristics were generated, revealing that the support vector machine regression model has significant positive effects on the prediction of stem structural characteristics while powder type and pretreatment of spectra has minor effects on the prediction of stem structural characteristics. In addition, we found that stem structure characteristics were positively correlated with agronomic traits but negatively correlated with lodging index which is the criterion that negatively accounts for plant lodging resistance. Conclusion This study for the first time provided a precise and high throughput method for the prediction of sorghum stem structural characteristics based on spectra, which could facilitate the improvement of lodging resistance in crop breeding.

Plant phenotyping relevance

ソルガム茎の構造形質を可視・近赤外スペクトルと回帰モデルで高スループット推定する手法を開発しており、植物形質取得が研究の中心である。

Code and data availability

The paper's VIS/NIR spectra and stem structural phenotype data are not publicly deposited: 'NIR spectra data will be made available on request' from the first author. The only code mentioned (R packages isotree and prospectr) are generic third-party libraries, not authors' analysis code. Supplementary files contain the

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