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

Abstract

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.