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

Devia Carlos A., Rojas bustos Juan Pablo, Petro Eliel, Martinez Carol, Mondragon Ivan F., Patino Diego, Rebolledo Cid Maria Camila, Colorado Julian D.. 2019. High-throughput biomass estimation in rice crops using UAV multispectral imagery. Journal of Intelligent and Robotic Systems, 96 (3-4) : 573-589.

Article de revue ; Article de recherche ; Article de revue à facteur d'impact
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Quartile : Q2, Sujet : COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE / Quartile : Q3, Sujet : ROBOTICS

Liste HCERES des revues (en SHS) : oui

Thème(s) HCERES des revues (en SHS) : Psychologie-éthologie-ergonomie

Résumé : 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.

Mots-clés Agrovoc : agriculture de précision, Oryza sativa, riz inondé, riz pluvial, biomasse, indice de végétation, imagerie multispectrale, drone

Mots-clés géographiques Agrovoc : Colombie

Mots-clés libres : UAV-based precision agriculture, Multispectral Imagery, Biomass, Rice, Vegetation indices

Classification Agris : U30 - Méthodes de recherche
F01 - Culture des plantes

Champ stratégique Cirad : CTS 2 (2019-) - Transitions agroécologiques

Auteurs et affiliations

  • Devia Carlos A., Pontificia Universidad Javeriana (COL)
  • Rojas bustos Juan Pablo, CIRAD-BIOS-UMR AGAP (FRA)
  • Petro Eliel, CIAT (COL)
  • Martinez Carol, Pontificia Universidad Javeriana (COL)
  • Mondragon Ivan F., Pontificia Universidad Javeriana (COL)
  • Patino Diego, Pontificia Universidad Javeriana (COL)
  • Rebolledo Cid Maria Camila, CIRAD-BIOS-UMR AGAP (FRA)
  • Colorado Julian D., Pontificia Universidad Javeriana (COL) - auteur correspondant

Source : Cirad-Agritrop (https://agritrop.cirad.fr/592197/)

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