Evolución y recuperación de pasturas para optimizar los rendimientos nutricionales de los semovientes interpretando los índices de vegetación normalizada usando levantamientos multiespectrales

Luis Daniel Gualdrón Guerrero; Oscar Eduardo Gualdrón Guerrero; Marisol Maestre Delgado

doi:10.24054/rcta.v2i42.2701

Authors

Luis Daniel Gualdrón Guerrero Universidad de Pamplona https://orcid.org/0000-0001-5024-1185
Oscar Eduardo Gualdrón Guerrero Universidad de Pamplona https://orcid.org/0000-0002-7854-6842
Marisol Maestre Delgado Universidad de Pamplona https://orcid.org/0000-0002-0548-2710

DOI:

https://doi.org/10.24054/rcta.v2i42.2701

Keywords:

NDVI, multispectral images, UAV, soil characterization

Abstract

Precision agriculture has experienced significant advances by taking advantage of technologies such as the use of drones and the capture of spectral images. The application of NDVI (Normalized Difference Vegetation Index) has become a key tool for the identification of vegetation cover, allowing for the accurate analysis of crop health and the estimation of the area occupied according to biomass density. The combination of these technologies facilitates the generation of daily vegetation growth rates, which is essential for projecting pasture recovery. In this work, NDVI was used to assess the health and anticipate the need for adjustments in pasture management and kikuyo grass requirements. Projections based on these data provide a valuable tool for decision making, ensuring that pasture recovery strategies are appropriate and effective as yields are optimized for livestock nutrition. This article focuses on monitoring the evolution of kikuyo pasture, specifically in a farm in the municipality of Pamplona, Norte de Santander, the time window for the development of the monitoring was determined in four months, in which a multispectral survey was carried out per month, and with the information obtained, daily growth rates and the projection of the days for the reestablishment of the grass were determined.

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