几何和体积简述:利用三维 X 射线计算机断层扫描分析核桃形态

Erik J. Amézquita, Michelle Y. Quigley, Patrick J. Brown, Elizabeth Munch, D. Chitwood
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摘要

波斯核桃(Juglans regia L.)是产量和消费量第二大的木本坚果,仅 2022-2023 年收获周期的产量就超过 260 万公吨。美国是第二大生产国,占全球总供应量的 25%。尽管如此,生产商面临着在更加不确定的气候条件下不断增长的需求,这就要求对核仁含量更高、外壳更易打开的核桃新品种进行有效和高效的选育。过去和现在的工作都是使用手持卡尺和肉眼评估来选择这些性状。然而,还有很多形态特征是肉眼可以看到但却无法测量的,例如核仁内部空气的体积或凸度。在此,我们基于 X 射线计算机断层扫描三维重建研究核桃果实的形状。我们计算了 149 个品种 1264 个核桃的 49 种不同形态表型。这些表型由育种兴趣性状(如核仁摘除难易度和核仁与核仁重量比)进行补充。通过异速生长关系(一种组织相对于另一种组织的相对生长),我们确定了发育过程中可能存在的生物物理制约因素。我们探讨了所有形态性状与商品性状之间的多重相关性,并确定了哪些形态性状可以解释商品性状的最大变异性。我们的研究表明,仅使用基于体积和厚度的性状,特别是内部空气含量,我们就能成功地对几种商业性状进行编码。
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Allometry and volumes in a nutshell: Analyzing walnut morphology using three‐dimensional X‐ray computed tomography
Persian walnuts (Juglans regia L.) are the second most produced and consumed tree nut, with over 2.6 million metric tons produced in the 2022–2023 harvest cycle alone. The United States is the second largest producer, accounting for 25% of the total global supply. Nonetheless, producers face an ever‐growing demand in a more uncertain climate landscape, which requires effective and efficient walnut selection and breeding of new cultivars with increased kernel content and easy‐to‐open shells. Past and current efforts select for these traits using hand‐held calipers and eye‐based evaluations. Yet there is plenty of morphology that meets the eye but goes unmeasured, such as the volume of inner air or the convexity of the kernel. Here, we study the shape of walnut fruits based on X‐ray computed tomography three‐dimensional reconstructions. We compute 49 different morphological phenotypes for 1264 individual nuts comprising 149 accessions. These phenotypes are complemented by traits of breeding interest such as ease of kernel removal and kernel‐to‐nut weight ratio. Through allometric relationships, relative growth of one tissue to another, we identify possible biophysical constraints at play during development. We explore multiple correlations between all morphological and commercial traits and identify which morphological traits can explain the most variability of commercial traits. We show that using only volume‐ and thickness‐based traits, especially inner air content, we can successfully encode several of the commercial traits.
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