Background Micro-computed tomography (μCT) bring a new opportunity to accurately quantify micro phenotypic traits of maize stem, also provide comparable benchmark to evaluate its dynamic development at the different growth stages. The progressive accumulation of stem biomass brings manifest structure changes of maize stem and vascular bundles, which are closely related with maize varietal characteristics and growth stages. Thus, micro-phenotyping (μPhenotyping) of maize stems is not only valuable to evaluate bio-mechanics and water-transport performance of maize, but also yield growth-based traits for quantitative traits loci (QTL) and functional genes location in molecular breeding. Result In this study, maize stems of 20 maize cultivars and two growth stages were imaged using μCT scanning technology. According to the observable differences of maize stems from the elongation and tasseling stages, function zones of maize stem were firstly defined to describe the substance accumulation of maize stems. And then a set of image-based μPhenotyping pipelines were implemented to quantify maize stem and vascular bundles at the two stages. The coefficient of determination (R2) of counting vascular bundles was higher than 0.95. Based on the uniform contour representation, intensity-related, geometry-related and distribution-related traits of vascular bundles were respectively evaluated in function zones and structure layers. And growth-related traits of the slice, epidermis, periphery and inner zones were also used to describe the dynamic growth of maize stem. Statistical analysis demonstrated the presented method was suitable to the phenotyping analysis of maize stem for multiple growth stages. Conclusions The novel descriptors of function zones provide effective phenotypic references to quantify the differences between growth stages; and the detection and identification of vascular bundles based on function zones are more robust to determine the adaptive image analysis pipeline. Developing robust and effective image-based phenotyping method to assess the traits of stem and vascular bundles, is highly relevant for understanding the relationship between maize phenomics and genomics.

中文翻译：

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使用微型计算机断层扫描在伸长和抽雄阶段对玉米茎进行表型分析。


背景微计算机断层扫描（μCT）为准确量化玉米茎的微观表型性状带来了新的机会，也为评估其在不同生长阶段的动态发育提供了可比较的基准。茎生物量的逐步积累带来了玉米茎和维管束明显的结构变化，这与玉米品种特性和生育阶段密切相关。因此，玉米茎的微表型分析（μPhenotyping）不仅对于评估玉米的生物力学和水分运输性能有价值，而且对于分子育种中数量性状基因座（QTL）和功能基因定位的生长性状具有重要意义。结果本研究利用μCT扫描技术对20个玉米品种和两个生长阶段的玉米茎进行了成像。根据玉米茎秆在伸长和抽雄阶段可观察到的差异，首先定义了玉米茎秆的功能区，以描述玉米茎秆物质积累的情况。然后实施一组基于图像的μ表型分析流程来量化两个阶段的玉米茎和维管束。维管束计数判定系数(R2)大于0.95。基于统一的轮廓表示，分别在功能区和结构层中评估维管束的强度相关、几何相关和分布相关特征。切片、表皮、外围和内部区域的生长相关性状也被用来描述玉米茎的动态生长。统计分析表明该方法适用于玉米茎多个生长阶段的表型分析。 结论 功能区的新颖描述符为量化生长阶段之间的差异提供了有效的表型参考；基于功能区的维管束检测和识别更加鲁棒，以确定自适应图像分析流程。开发稳健有效的基于图像的表型方法来评估茎和维管束的性状，对于理解玉米表型​​组学和基因组学之间的关系高度相关。