Allometry and volumes in a nutshell: Analyzing walnut morphology using three‐dimensional X‐ray computed tomography
Allometry and volumes in a nutshell: Analyzing walnut morphology using three‐dimensional X‐ray computed tomography
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DOI：
10.1002/ppj2.20095
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发表时间：
2024-02
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通讯作者：
Erik J. Amézquita;Michelle Y. Quigley;Patrick J. Brown;Elizabeth Munch;D. Chitwood
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作者：
Erik J. Amézquita;Michelle Y. Quigley;Patrick J. Brown;Elizabeth Munch;D. Chitwood
波斯核桃(Juglans Regia L.)是产量和消费量第二大的树木坚果，仅2022-2023年收获周期就生产了超过260万吨坚果。美国是第二大生产国，占全球总供应量的25%。然而，在更加不确定的气候环境中，生产者面临着日益增长的需求，这就需要有效和高效地选择核桃，并培育出含仁量更高、壳更容易打开的新品种。过去和现在的努力使用手持卡尺和基于眼睛的评估来选择这些特征。然而，有许多形态符合眼睛，但没有测量，例如内部空气的体积或果仁的凸度。在这里，我们研究了基于X射线计算机断层扫描三维重建的核桃果实的形状。我们计算了包含149份材料的1264个坚果的49种不同的形态表型。这些表型与育种感兴趣的性状相辅相成，如易去仁率和仁果重量比。通过异速生长关系，即一个组织相对于另一个组织的相对生长，我们确定了在发育过程中可能起作用的生物物理限制因素。我们探索了所有形态性状和商业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业性状的最大变异性。我们表明，仅使用基于体积和厚度的特征，特别是内部空气含量，我们可以成功地编码几个商业特征。
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.