Journal Article

High-throughput biomass estimation in rice crops using UAV multispectral imagery

Colorado, Julian D, Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Mondragon, Ivan F, Patino, Diego, Petro, Eliel, Rojas Bustos, Juan Pablo, Devia, Carlos A, Martinez, Carol, International Center for Tropical Agriculture [Colombie] (CIAT) ; Consultative Group on International Agricultural Research [CGIAR] (CGIAR), Rebolledo Cid, Maria Camila, Pontificia Universidad Javeriana (PUJ)

2019

Overview

This paper presents a high-throughput method for Above Ground Estimation of Biomass (AGBE) in rice using multispectral near-infrared (NIR) imagery captured at different scales of the crop. By developing an integrated aerial crop monitoring solution using an Unmanned Aerial Vehicle (UAV), our approach calculates 7 vegetation indices that are combined in the form of multivariable regressions depending on the stage of rice growth: vegetative, reproductive or ripening. We model the relationship of these vegetation indices to estimate the biomass of a certain crop area. The methods are calibrated by using a minimum sampling area of 1 linear meter of the crop. Comprehensive experimental tests have been carried out over two different rice varieties under upland and lowland rice production systems. Results show that the proposed approach is able to estimate the biomass of large areas of the crop with an average correlation of 0.76 compared with the traditional manual destructive method. To our knowledge, this is the first work that uses a small sampling area of 1 linear meter to calibrate and validate NIR image-based estimations of biomass in rice crops.

• Publisher: Springer Verlag,CCSD,Springer Netherlands,Springer,Springer Nature B.V
• Subject: Agricultural industry / Agricultural sciences / Agronomy / Analysis / Artificial Intelligence / Biomass / Control / Crops / Drone aircraft / Electrical Engineering / Engineering / Equipment and supplies / Horticulture / Humanities and Social Sciences / Image processing / Infrared imagery / Life Sciences / Mechanical Engineering / Mechatronics / Methods and statistics / Near infrared radiation / Rice / Ripening / Robotics / Sampling / Sciences and technics of agriculture / Unmanned aerial vehicles / Vegetation / Vegetation index