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.

From
The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT)
Published on
27.12.23
Challenges
Climate adaptation & mitigation, Environmental health & biodiversity

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.

Conejo Rodriguez, F.; Gonzalez Guzman, J.; Ramirez, G.J.; Urban, M.; Wenzl, P.

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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.