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Morphometrics of Starch Granules from Sub-Saharan Plants and the Identification of Ancient Starch

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DataCite Commons2026-04-16 更新2024-07-13 收录
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https://www.frdr-dfdr.ca/repo/dataset/cf1f2720-eb8b-04ee-6a4d-941cb0cbe67a
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The assumption that taxonomy can be ascertained by starch granule shape and size has persisted unchallenged since the late nineteenth and early twentieth century biochemistry. More recent work has established that granule morphological affinity is scattered throughout phylogenetic branches, morphotype proportions vary within the genus, granules from closely related genera can differ dramatically in shape, and size variations do not reflect phylogenetic relationships. This situation is confounded by polymorphism at the species and tissue level, resulting in redundancy and multiplicity. This paper classifies morphological features of starch granules from 77 species, 31 families, and 22 orders across three African ecoregions. This is the largest starch reference collection published to date, rendering the dataset uniquely well suited to explore i) the diagnostic power of unique morphometric classifiers and their frequency, ii) morphotypes that cut across taxonomic boundaries, and iii) issues surrounding the minimum counts needed to accurately reflect granule polymorphism, variability, and identification. In a collection of 23,100 granules, taxonomic identification occurred very rarely. In the instances it did, it was at the species level, with no occurrences of a single morphotype or complement identifying all species within a family or genus. Some families cannot be uniquely identified, and morphometric types are shared despite taxonomic distance for three quarters of the taxa. However, this reference collection boasts 98 unique identifiers located in the Arecaceae, Convolvulaceae, Cyperaceae, Dioscoreaceae, Fabaceae, Musaceae, Pedaliaceae, Poaceae, and Zamiaceae. Therefore, the identification of starch granules is possible in some cases only.
提供机构:
Federated Research Data Repository / dépôt fédéré de données de recherche
创建时间:
2018-01-18
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