In-Field Forage Biomass and Quality Prediction Using Image and VIS-NIR Proximal Sensing with Machine Learning and Covariance-Based Strategies for Livestock Management in Silvopastoral Systems

Controlling forage quality and grazing are crucial for sustainable livestock production, health, productivity, and animal performance. However, the limited availability of reliable handheld sensors for timely pasture quality prediction hinders farmers’ ability to make informed decisions. This stud...

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Detalles Bibliográficos

Autores principales:	Serpa Imbett, Claudia M., Gómez Palencia, Erika L., Medina Herrera, Diego A., Mejía Luquez, Jorge A., Martínez, Remberto R., Burgos Paz, William O., Aguayo Ulloa, Lorena A.
Formato:	article
Lenguaje:	Inglés
Publicado:	Multidisciplinary Digital Publishing Institute (MDPI) 2025
Materias:	Hyperspectral sensing Optical spectrum Handheld proximal sensors Image processing Mahalanobis distance Ganadería - L01 Biomasa Forraje Sistema silvopascícola Alimentación de los animales Ganadería y especies menores http://aims.fao.org/aos/agrovoc/c_926 http://aims.fao.org/aos/agrovoc/c_36108 http://aims.fao.org/aos/agrovoc/c_16097 http://aims.fao.org/aos/agrovoc/c_429
Acceso en línea:	https://www.mdpi.com/2624-7402/7/4/111 https://hdl.handle.net/20.500.12324/41271 https://doi.org/10.3390/agriengineering7040111