Abstract：
CONCLUSIONS: A novel image-based screening method for precisely identifying genotypic variations in rapeseed RSA under waterlogging stress was developed. Five key root traits were confirmed as good indicators of waterlogging and might be employed in breeding, particularly when using the MFVW approach. Waterlogging is a vital environmental factor that has detrimental effects on the growth and development of rapeseed (Brassica napus L.). Plant roots suffer from hypoxia under waterlogging, which ultimately confers yield penalty. Therefore, it is crucially important to understand the genetic variation of root system architecture (RSA) in response to waterlogging stress to guide the selection of new tolerant cultivars with favorable roots. This research was conducted to investigate RSA traits using image-based screening techniques to better understand how RSA changes over time during waterlogging at the seedling stage. First, we performed a t-test by comparing the relative root trait value between four tolerant and four sensitive accessions. The most important root characteristics associated with waterlogging tolerance at 12 h are total root length (TRL), total root surface area (TRSA), total root volume (TRV), total number of tips (TNT), and total number of forks (TNF). The root structures of 448 rapeseed accessions with or without waterlogging showed notable genetic diversity, and all traits were generally restrained under waterlogging conditions, except for the total root average diameter. Additionally, according to the evaluation and integration analysis of 448 accessions, we identified that five traits, TRL, TRSA, TRV, TNT, and TNF, were the most reliable traits for screening waterlogging-tolerant accessions. Using analysis of the membership function value (MFVW) and D-value of the five selected traits, 25 extremely waterlogging-tolerant materials were screened out. Waterlogging significantly reduced RSA, inhibiting root growth compared to the control. Additionally, waterlogging increased lipid peroxidation, accompanied by a decrease in the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT). This study effectively improves our understanding of the response of RSA to waterlogging. The image-based screening method developed in this study provides a new scientific guidance for quickly examining the basic RSA changes and precisely predicting waterlogging-tolerant rapeseed germplasms, thus expanding the genetic diversity of waterlogging-tolerant rapeseed germplasm available for breeding.
摘要：
结论：开发了一种新的基于图像的筛选方法，用于在淹水胁迫下精确识别油菜RSA的基因型变异。五个关键根系性状被确认为良好的淹水指标，可用于育种。特别是在使用MFVW方法时。淹水是影响油菜生长发育的重要环境因素。植物根系在淹水下遭受缺氧，这最终赋予了屈服惩罚。因此,了解根系结构（RSA）的遗传变异以响应淹水胁迫，以指导选择具有良好根的新耐性品种至关重要。进行这项研究是为了使用基于图像的筛选技术研究RSA性状，以更好地了解RSA在幼苗期的淹水过程中如何随时间变化。首先,我们通过比较四个耐性和四个敏感种质之间的相对根性状值进行了t检验。与12小时耐涝性相关的最重要的根系特征是总根长（TRL），总根表面积（TRSA），总根体积（TRV），提示总数（TNT），和叉子总数（TNF）。448个油菜品种的根系结构表现出明显的遗传多样性，所有性状在涝渍条件下一般都受到抑制，除了总根平均直径。此外,根据对448个种质资源的评估和整合分析，我们确定了五个特征，TRL,TRSA,TRV,TNT,和TNF，是筛选耐涝种质的最可靠性状。利用对五个选定性状的隶属函数值(MFVW)和D值的分析,筛选出25个耐涝材料。内涝显著降低了RSA，与对照相比，抑制根生长。此外,淹水增加脂质过氧化，伴随着超氧化物歧化酶（SOD）活性的降低，过氧化物酶(POD),和过氧化氢酶(CAT)。这项研究有效地提高了我们对RSA对内涝反应的理解。本研究开发的基于图像的筛选方法为快速检测RSA的基本变化和准确预测耐涝油菜种质提供了新的科学指导。从而扩大了耐涝油菜种质的遗传多样性，可用于育种。
