DiasMorph: a dataset of morphological traits and images of Central European diaspores

Author:

Dayrell Roberta L. C.ORCID,Begemann Lina,Ott Tankred,Poschlod Peter

Abstract

A knowledge of the morphology of seeds and diaspores is an invaluable resource that has prompted the compilation of descriptions and/or images in a variety of media, including databases with standardized protocols for trait measurement. The pressing need for new solutions to solve environmental crises, together with advances in the application of machine learning and image analysis to solve ecological problems, call for an upgrade of the diaspore morphological datasets. Here, we present DiasMorph, a dataset of morphological traits and images of diaspores from 1,437 taxa in 513 genera, and 96 families from Central Europe, totalling 94,214 records. DiasMorph compiles information on quantitative morphological traits extracted from the images following a standardized and reproducible image analysis method, and include not only traditional morphometric measurements, but also colour, and shape features made available for the first time in a large dataset. The quantitative traits records correspond to measurements of individual diaspores, an input currently unavailable in traits databases that will allow for several approaches to be used for a complete exploration of the morphological traits of these species. We also included information on the presence and absence of appendages and structures in the diaspores of the evaluated taxa. By making these data available, we aim to encourage initiatives to advance on new tools for diaspore identification, further our understanding of morphological traits functions, and provide means for the continuous development of image analyses applications. Keywords: diaspore appendages, dispersal unit, image dataset, plant traits dataset, seed colour, seed morphology, seed shape, seed size, seed traits.

Publisher

Authorea, Inc.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Automated extraction of seed morphological traits from images;Methods in Ecology and Evolution;2023-05-14

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