Three-dimensional image analysis specifies the root distribution for drought avoidance in the early growth stage of rice.

Abstract

Background and aims Root system architecture (RSA) plays a key role in plant adaptation to drought, because deep rooting enables better water uptake than shallow rooting under terminal drought. Understanding RSA during early plant development is essential for improving crop yields, because early drought can affect subsequent shoot growth. Herein, we demonstrate that root distribution in the topsoil significantly impacts shoot growth during the early stages of rice (Oryza sativa) development under drought, as assessed through three-dimensional image analysis. Methods We used 109 F12 recombinant inbred lines obtained from a cross between shallow-rooting lowland rice and deep-rooting upland rice, representing a population with diverse RSA. We applied a moderate drought during the early development of rice grown in a plant pot (25 cm in height) by stopping irrigation 14 days after sowing. Time-series RSA at 14, 21 and 28 days after sowing was visualized by X-ray computed tomography and, subsequently, compared between drought and well-watered conditions. After this analysis, we investigated drought-avoidant RSA further by testing 20 randomly selected recombinant inbred lines in drought conditions. Key results We inferred the root location that most influences shoot growth using a hierarchical Bayes approach: the root segment depth that impacted shoot growth positively ranged between 1.7 and 3.4 cm in drought conditions and between 0.0 and 1.7 cm in well-watered conditions. Drought-avoidant recombinant inbred lines had a higher root density in the lower layers of the topsoil compared with the others. Conclusions Fine classification of soil layers using three-dimensional image analysis revealed that increasing root density in the lower layers of the topsoil, rather than in the subsoil, is advantageous for drought avoidance during the early growth stage of rice.

Plant phenotyping relevance

X線CTと三次元画像解析による時系列の根系構造・根密度の取得と細分類が研究の中心であり、植物形質を抽出する方法の実質的な適用に該当する。

Code and data availability

The paper's phenotype datasets (root intensity per soil layer, SNP marker genotypes, shoot measurements) are not deposited in any public repository; the Data Availability Statement requires contacting the corresponding author. The supplementary zip is hosted on PMC, but no allowed URL can be assigned to it, and the R/J

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