ArticleData in brief2020
High throughput phenotyping dataset related to seed and seedling traits of sugar beet genotypes.
Article in Data in brief, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 11 citations in OpenAlex.
- Understanding seed germination responses to low-dose X-rays: the role of seed quality, variety, and density.Plant methods · 2025Article
- Toward robust and high-throughput detection of seed defects in X-ray images via deep learning.Plant methods · 2024Article
- Cereal grain 3D point cloud analysis method for shape extraction and filled/unfilled grain identification based on structured light imaging.Scientific reports · 2022Article
- Resources for image-based high-throughput phenotyping in crops and data sharing challenges.Plant physiology · 2021Article
- Genome wide association study of agronomic and seed traits in a world collection of proso millet (Panicum miliaceum L.).BMC plant biology · 2021Article
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Authors and funding
16 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Several seed and seedling traits are measured to evaluate germination and emergence potential in relation with environmental conditions. More generally, these traits are also measured in the field of ecology as simple traits that can be correlated to other adaptative traits more difficult to measure on adult plants, as for example traits of the rooting system. Methods were developed for deep high throughput phenotyping of hundreds of genotypes from dry seed to the end of heterotrophic growth. The present dataset comes from a project on genotyping and phenotyping of populations of genotypes, with different geographic and genetic origins so as to increase genotypic diversity of sugar beet in terms of germination and early growth traits, evaluated at low temperatures. Data were collected in relation to the creation of the first sugar beet crop ontology. This dataset corresponds to the first automated phenotyping of a population of 198 genotypes and 4 commercial control varieties and is hosted on INRAE public depository under the reference number doi.org/10.15,454/AKNF4Q. The equipment and methods presented here are available on a phenotyping platform opened to collaborative research and adaptable for specific services for characterizing thousands of genotypes on different crops or other species. The phenotyping values can also be linked to genomic information to study the genetic determinism of the trait values.
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