Adaptation of agriculture to climate change and its associated ecological pressures will require new crops, novel trait combinations, and previously unknown phenotypic attributes to deploy in climate resilient cropping systems. Genebanks, a primary source of exotic germplasm for novel crops and breeding materials, need comprehensive methods to detect novel and unknown phenotypes without a priori information about the species or trait under consideration. We demonstrate how persistent homology (PH) and elliptical fourier descriptors (EFD), two morphometric techniques easily applied to image-based data, can serve this purpose by cataloging leaf morphology in the USDA NPGS kura clover collection and demarcating a leaf morphospace for the species. Additionally, we identify a set of representative accessions spanning the leaf morphospace and propose they serve as a kura clover core collection. The core collection will be a framework for monitoring the effects of climate change on kura clover in situ diversity and determining the role of ex situ accessions in modern agriculture.

中文翻译：

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促进利用外来种质改善粮食安全和气候变化适应力的形态测量方法：以库拉三叶草为例

农业对气候变化及其相关生态压力的适应将需要新作物、新的性状组合和以前未知的表型属性，以部署在气候适应性种植系统中。基因库是新作物和育种材料外来种质的主要来源，需要综合方法来检测新的和未知的表型，而无需考虑物种或性状的先验信息。我们展示了持久同源性 (PH) 和椭圆傅立叶描述符 (EFD) 这两种易于应用于基于图像的数据的形态测量技术如何通过对美国农业部 NPGS 库拉三叶草系列中的叶子形态进行编目并划分该物种的叶子形态空间来达到此目的. 此外，我们确定了一组跨越叶形态空间的代表性种质，并建议它们作为 kura 三叶草核心系列。核心收藏将是一个框架，用于监测气候变化对库拉三叶草原生境多样性的影响，并确定非原生境种质在现代农业中的作用。