Abstract：
OBJECTIVE: 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, as 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 (3D) image analysis.
METHODS: We used 109 F12 recombinant inbred lines (RILs) 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 height) by stopping irrigation 14 days after sowing (DAS). Time-series RSA at 14, 21, and 28 DAS was visualized by X-ray computed tomography, and subsequently compared between drought and well-watered conditions. Following this analysis, we further investigated drought-avoidant RSA by testing 20 randomly selected RILs under drought conditions.
RESULTS: We inferred the root location that most influences shoot growth using a hierarchical Bayes approach: the root segment depth, which positively impacted shoot growth, ranged between 1.7-3.4 cm under drought conditions and between 0.0-1.7 cm under well-watered conditions. Drought-avoidant RILs had a higher root density in the lower layers of the topsoil compared to the others.
CONCLUSIONS: Fine classification of soil layers using 3D 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.
METHODS: We used 109 F12 recombinant inbred lines (RILs) 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 height) by stopping irrigation 14 days after sowing (DAS). Time-series RSA at 14, 21, and 28 DAS was visualized by X-ray computed tomography, and subsequently compared between drought and well-watered conditions. Following this analysis, we further investigated drought-avoidant RSA by testing 20 randomly selected RILs under drought conditions.
RESULTS: We inferred the root location that most influences shoot growth using a hierarchical Bayes approach: the root segment depth, which positively impacted shoot growth, ranged between 1.7-3.4 cm under drought conditions and between 0.0-1.7 cm under well-watered conditions. Drought-avoidant RILs had a higher root density in the lower layers of the topsoil compared to the others.
CONCLUSIONS: Fine classification of soil layers using 3D 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.
摘要：
目的：根系结构（RSA）在植物适应干旱中起着关键作用，因为在最终干旱下，深生根比浅生根能更好地吸收水分。在植物早期发育过程中了解RSA对于提高作物产量至关重要。早期干旱会影响随后的芽生长。在这里，我们证明，在干旱条件下，在水稻（Oryzasativa）发育的早期阶段，表层土壤中的根系分布显着影响芽的生长。通过三维(3D)图像分析评估。
方法：我们使用了109个F12重组自交系（RILs），这些系是从浅根低地水稻和深根旱地水稻的杂交中获得的，代表具有不同RSA的人口。我们在播种（DAS）后14天停止灌溉，在花盆（25厘米高）中种植的水稻的早期发育过程中施加了中度干旱。通过X射线计算机断层扫描对14、21和28DAS的时间序列RSA进行可视化，随后在干旱和灌溉条件之间进行了比较。根据这一分析,我们通过在干旱条件下测试20个随机选择的RIL，进一步研究了避免干旱的RSA。
结果：我们使用分层贝叶斯方法推断了最影响枝条生长的根位置：根段深度，这对枝条的生长产生了积极的影响，在干旱条件下的范围在1.7-3.4厘米之间，在浇水条件下的范围在0.0-1.7厘米之间。与其他土壤相比，避免干旱的RIL在表层土壤的下层具有更高的根密度。
结论：使用3D图像分析对土壤层进行精细分类表明，表土下层的根系密度增加，而不是在底土中，有利于水稻早期生长阶段的抗旱。
方法：我们使用了109个F12重组自交系（RILs），这些系是从浅根低地水稻和深根旱地水稻的杂交中获得的，代表具有不同RSA的人口。我们在播种（DAS）后14天停止灌溉，在花盆（25厘米高）中种植的水稻的早期发育过程中施加了中度干旱。通过X射线计算机断层扫描对14、21和28DAS的时间序列RSA进行可视化，随后在干旱和灌溉条件之间进行了比较。根据这一分析,我们通过在干旱条件下测试20个随机选择的RIL，进一步研究了避免干旱的RSA。
结果：我们使用分层贝叶斯方法推断了最影响枝条生长的根位置：根段深度，这对枝条的生长产生了积极的影响，在干旱条件下的范围在1.7-3.4厘米之间，在浇水条件下的范围在0.0-1.7厘米之间。与其他土壤相比，避免干旱的RIL在表层土壤的下层具有更高的根密度。
结论：使用3D图像分析对土壤层进行精细分类表明，表土下层的根系密度增加，而不是在底土中，有利于水稻早期生长阶段的抗旱。
