Estimación de la calidad y cantidad de pasto kikuyo (Cenchrus clandestinum (Hochst. ex Chiov.) Morrone) usando imágenes multiespectrales

The evaluation of grazing lands is essential to improve livestock productivity. Data from multispectral airborne sensors allow calculating vegetation indexes (VI) and relating them to physiological and biophysical characteristics of the pastures. The objective of this study was to evaluate the usefu...

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Autores:
Posada Asprilla, William
Medina Sierra, Marisol
Cerón Muñoz, Mario
Tipo de recurso:
Article of journal
Fecha de publicación:
2019
Institución:
Universidad de Ciencias Aplicadas y Ambientales U.D.C.A
Repositorio:
Repositorio Institucional UDCA
Idioma:
spa
OAI Identifier:
oai:repository.udca.edu.co:11158/2008
Acceso en línea:
https://revistas.udca.edu.co/index.php/ruadc/article/view/1195
https://doi.org/10.31910/rudca.v22.n1.2019.1195
Palabra clave:
Agricultura de precisión
Calidad nutricional
Ganadería de leche
Índices de vegetación
Proteína bruta
Sensores remotos
Cenchrus
Pennisetum clandestinum
Proteina bruta
Rights
openAccess
License
Derechos Reservados - Universidad de Ciencias Aplicadas y Ambientales
Description
Summary:The evaluation of grazing lands is essential to improve livestock productivity. Data from multispectral airborne sensors allow calculating vegetation indexes (VI) and relating them to physiological and biophysical characteristics of the pastures. The objective of this study was to evaluate the usefulness of VI to estimate the quantity and quality of Kikuyu grass in dairy farms of northern Antioquia, Colombia. We calculated 10 different VI using 168 samples of Kikuyu grass. The samples were weighted to estimate green biomass (BV) and analyzed by near infrared spectroscopy for the contents of crude protein (PB), neutral detergent fiber (FDN) and acid detergent fiber (ADF). Data were analyzed using principal components (CP) and smoothed generalized additive models. The variables that contributed most to the formation of the first principal component (CP1) were the Normalized Difference Vegetation Index (NDVI), the Simple Vegetation Index (RVI), the Normalized Difference Vegetation Green Index (GNDVI), the Green Chlorophyll Index (Clg) and the BV of Kikuyu grass. The mayor contributors to the second principal component (CP2) were the Normalized Red-Edge Vegetation Index (RNDVI), the Red-Edge Chlorophyll Index (Clrg), and the PB, NDF and FDA of Kikuyu. The NDVI explained the BV, and the RNDVI explained the PB. The FDN and FDA estimations in Kikuyu were not precise.