Resumen

VIGABRIEL NAVARRO, Luz María; OSORIO LEYTON, Javier Mauricio; QUEZADA LAMBERTIN, Carlos Eduardo  y  BENAVIDES LOPEZ, Jean Paul. Estimating biomass of barley (Hordeum vulgare L.) using remotely sensed multispectral images. RIIARn [online]. 2024, vol.11, n.2, pp.18-29. ISSN 2409-1618.  https://doi.org/10.53287/iguo9951ru99j.

This study explores the potential of unmanned aerial vehicles (UAVs) and multispectral image analysis to estimate barley crop biomass in the Bolivian highlands. Using a drone equipped with a multispectral camera, images of barley crops were captured, and their biomass was estimated by calculating the NDVI vegetation index and applying a polynomial regression equation based on this index. The methodology proved to be efficient and precise, offering a non-invasive and cost-effective long-term alternative for agricultural research and decision-making compared to conventional methods. This approach, which combines remote sensing with advanced analytical models, demonstrates a strong correlation between NDVI and barley biomass, with a coefficient of determination (R2) of 0.94, highlighting the viability of this technology to enhance agricultural monitoring and optimize crop production in regions with climatic and resource limitations. This research opens up new opportunities to improve agricultural management and optimize crop production, providing farmers with a precise and efficient tool for informed decision-making.

Palabras clave : aerial biomass; unmanned aerial vehicles; remote sensing; vegetation index.

        · resumen en Español     · texto en Español     · Español ( pdf )