Use of machine learning approaches for quantification of red spider mite (Acari: Tetranychidae) damage in Urochloa sp.
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Title |
Use of machine learning approaches for quantification of red spider mite (Acari: Tetranychidae) damage in Urochloa sp.
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Creator |
Espitia-Buitrago, Paula
Cotes-Torres, José M. Mating'i Kimani, Adrian Chidawanyika, Frank Hernández, Luis M. Cardoso, Juan Jauregui, Rosa |
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Subject |
machine learning
Tetranychidae plant pests pest resistance Urochloa genotypes |
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Date |
2023-10-23
2023-11-07T15:24:42Z 2023-11-07T15:24:42Z |
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Type |
Poster
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Identifier |
Espitia-Buitrago P.; Cotes-Torres J.M.; Mating'i A.; Chidawanyika F.; Hernández L.M.; Cardoso J.; Jauregui R. (2023) Use of machine learning approaches for quantification of red spider mite (Acari: Tetranychidae) damage in Urochloa sp. Poster prepared for African Plant Breeders Association 2023 Conference - Leveraging Genetic Innovation for Resilient African Food Systems in the wake of Global Shocks. Benguerir, Morocco, 23-26 October 2023. Cali (Colombia): International Center for Tropical Agriculture. 1 p.
https://hdl.handle.net/10568/132802 |
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Language |
en
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Relation |
African Plant Breeders Association 2023 Conference
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Rights |
CC-BY-4.0
Open Access |
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Format |
1 p.
application/pdf |
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Publisher |
International Center for Tropical Agriculture
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