RT Journal Article
T1 Nutritional status assessment of olive crops by means of the analysis and modelling of multispectral images taken with UAVs
A1 Noguera Manzano, Miguel
A1 Aquino Martín, Arturo
A1 Ponce Real, Juan Manuel
A1 Cordeiro, Antonio
A1 Silvestre, José
A1 Arias Calderón, Rocío
A1 Marcelo, Maria da Encarnação
A1 Jordão, Pedro
A1 Andújar Márquez, José Manuel
AB This research was aimed at developing an efficient method for Nitrogen, Phosphorus, and Potassium (NPK) foliar content retrieval in olive trees by means of the analysis and modelling multispectral images taken by an unmanned aerial vehicle (UAV) under field conditions. To this end, an experiment was carried out in a super hight density olive orchard. The fertirrigation system of the experimental area was sectorized to obtain plots with different status of NPK. The orchard was overflown with a UAV equipped with a multispectral camera that photographed the entire experimental surface. A new image analysis approach was developed for integrating all the spectral images gathered during the flight in orthomosaics from which to automatically extract information from discrete points. Finally, several retrieval techniques (partial least squares regression, artificial neural network (ANN), support vector regression and Gaussian process regression) were evaluated for NPK leaf content retrieval by using the spectral data as input variables, and the results of chemical analyses as reference. Among all, the best results were obtained by ANN approach (N (R2 = 0.63), P (R2 = 0.89), K (R2 = 0.93)). These results showed the suitability of the proposed image processing approach and indicate ANN as the best recovery technique for the experimental conditions evaluated. However, the approach must be validated under other environmental conditions, olive varieties and plant vegetative stages before making fertilization recommendations.
PB Elsevier
SN 1537-5110
SN 1537-5129 (electrónico)
YR 2021
FD 2021-09
LK https://hdl.handle.net/10272/23050
UL https://hdl.handle.net/10272/23050
LA eng
NO Noguera, M., Aquino, A., Ponce, J. M., Cordeiro, A., Silvestre, J., Arias-Calderón, R., Marcelo, M. da E., Jordão, P., & Andújar, J. M. (2021). Nutritional status assessment of olive crops by means of the analysis and modelling of multispectral images taken with UAVs. In Biosystems Engineering (Vol. 211, pp. 1–18). Elsevier BV. https://doi.org/10.1016/j.biosystemseng.2021.08.035
NO The research and APC were funded by the Interreg Cooperation Program V-A SPAIN-PORTUGAL (POCTEP) 2014–2020 and co-financed with ERDF, grant number 0155_TECNOLIVO_6_E, within the scope of the TecnOlivo Project.
DS Repositorio Institucional de la Universidad de Huelva
RD 31 may 2026