Monitorización del contenido de fósforo del olivo mediante robot terrestre

  1. Noguera, Miguel 1
  2. Millan, Borja 2
  3. Moro, Rocio
  4. Andújar, José Manuel 1
  1. 1 Centro de Investigación en Tecnología, Energía y Sostenibilidad, Universidad de Huelva
  2. 2 Departamento de Ingeniería Eléctrica, Electrónica, Informática y de Sistemas, Universidad de Oviedo
Journal:
Jornadas de Automática
  1. Cruz Martín, Ana María (coord.)
  2. Arévalo Espejo, V. (coord.)
  3. Fernández Lozano, Juan Jesús (coord.)

ISSN: 3045-4093

Year of publication: 2024

Issue: 45

Type: Article

DOI: 10.17979/JA-CEA.2024.45.10918 DIALNET GOOGLE SCHOLAR lock_openOpen access editor

Sustainable development goals

Abstract

The olive grove is a crop of great importance for the agronomic sector in the countries of the Mediterranean basin. In the last decades, the olive sector has undergone modernisation in order to increase the profitability and productivity of its crop systems. In this context, management approaches based on precision agriculture are showing promising potential. In this sense, the present work shows a methodology for the characterisation of leaf P content in super-intensive olive orchards. The proposed method is based o nartificial neural networks fed with spectral information extracted from images acquired by a terrestrial robot with autonomous navigation capabilities. To evaluate the proposed methodology, an experimental approach was defined based on exposing a plot of super-intensive olive trees to differential fertigation treatments to generate variability in leaf P content. The correlation index between the reference values obtained by chemical analysis and the response of the developed model (R2 = 0.72) suggests the suitability of the proposed methodology.

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