Digital functional phenomic descriptors featured from machine learning-driven image-based phenotyping improve the accuracy of classic descriptors: A case study on Arachis spp. and Phaseolus spp.
cg.authorship.types | CGIAR single centre | en_US |
cg.contributor.affiliation | International Center for Tropical Agriculture | en_US |
cg.contributor.donor | CGIAR Trust Fund | en_US |
cg.contributor.initiative | Genebanks | en_US |
cg.coverage.country | Colombia | en_US |
cg.coverage.iso3166-alpha2 | CO | en_US |
cg.coverage.region | Americas | en_US |
cg.coverage.region | Latin America and the Caribbean | en_US |
cg.coverage.region | South America | en_US |
cg.creator.identifier | Juan José Gonzalez Guzman: 0000-0002-7643-3430 | en_US |
cg.creator.identifier | Milan Oldřich Urban: 0000-0002-3684-856X | en_US |
cg.creator.identifier | Peter Wenzl: 0000-0003-4657-8468 | en_US |
cg.subject.actionArea | Genetic Innovation | en_US |
cg.subject.alliancebiovciat | BEANS | en_US |
cg.subject.alliancebiovciat | DOCUMENTATION | en_US |
cg.subject.alliancebiovciat | GENETIC RESOURCES | en_US |
cg.subject.alliancebiovciat | PLANT GENETIC RESOURCES | en_US |
cg.subject.alliancebiovciat | TROPICAL FORAGES | en_US |
cg.subject.impactArea | Environmental health and biodiversity | en_US |
cg.subject.impactArea | Nutrition, health and food security | en_US |
cg.subject.sdg | SDG 2 - Zero hunger | en_US |
dc.contributor.author | Conejo Rodriguez, F. | en_US |
dc.contributor.author | Gonzalez Guzman, J. | en_US |
dc.contributor.author | Ramirez, Gil J. | en_US |
dc.contributor.author | Urban, Milan Oldřich | en_US |
dc.contributor.author | Wenzl, Peter | en_US |
dc.date.accessioned | 2023-12-26T13:59:57Z | en_US |
dc.date.available | 2023-12-26T13:59:57Z | en_US |
dc.identifier.uri | https://hdl.handle.net/10568/135933 | en_US |
dc.title | Digital functional phenomic descriptors featured from machine learning-driven image-based phenotyping improve the accuracy of classic descriptors: A case study on Arachis spp. and Phaseolus spp. | en_US |
dcterms.accessRights | Open Access | en_US |
dcterms.bibliographicCitation | Conejo Rodriguez, F.; Gonzalez Guzman, J.; Ramirez, G.J.; Urban, M.; Wenzl, P. (2023) Digital functional phenomic descriptors featured from machine learning-driven image-based phenotyping improve the accuracy of classic descriptors: A case study on Arachis spp. and Phaseolus spp. 17 sl. | en_US |
dcterms.extent | 17 sl. | en_US |
dcterms.issued | 2023-08-01 | en_US |
dcterms.language | en | en_US |
dcterms.license | CC-BY-4.0 | en_US |
dcterms.subject | evaluation | en_US |
dcterms.subject | gene banks | en_US |
dcterms.subject | machine learning | en_US |
dcterms.subject | agronomic characters | en_US |
dcterms.subject | phenotyping | en_US |
dcterms.subject | imagery | en_US |
dcterms.subject | classification | en_US |
dcterms.subject | functional diversity | en_US |
dcterms.type | Presentation | en_US |
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