Compartir
Título
High-Resolution Drone-Acquired RGB Imagery to Estimate Spatial Grape Quality Variability
Autor
Facultad/Centro
Área de conocimiento
Título de la revista
Agronomy
Número de la revista
4
Cita Bibliográfica
García Fernández, M., Sanz Ablanedo E. & Rodríguez Pérez, J.R. (2021). High-Resolution Drone-Acquired RGB Imagery to Estimate Spatial Grape Quality Variability, Agronomy 11(4), 665. https://doi.org/10.3390/agronomy11040655
Editorial
MDPI
Fecha
2021-03-30
Resumen
[EN] Remotesensing techniques can help reduce time and resources spent collecting samples of crops and analyzing quality variables. The main objective of this work was to demonstrate that it is possible to obtain information on the distribution of must quality variables from conventional photographs. Georeferenced berry samples were collected and analyzed in the laboratory, and RGB images were taken using a low-cost drone from which an orthoimage was made. Transformation equations were calculated to obtain absolute reflectances for the different bands and to calculate 10 vegetation indices plus two new proposed indices. Correlations for the 12 indices with values for 15 must quality variables were calculated in terms of Pearson’s correlation coefficients. Significant correlations were obtained for 100-berries weight (0.77), malic acid (−0.67), alpha amino nitrogen (−0.59), phenolic maturation index (0.69), and the total polyphenol index (0.62), with 100-berries weight and the total polyphenol index obtaining the best results in the proposed RGB-based vegetation index 2 and RGB-based vegetation index 3. Our findings indicate that must variables important for the production of quality wines can be related to the RGB bands in conventional digital images, potentially improving and aiding management and increasing productivity.
Materia
Palabras clave
Peer review
SI
ID proyecto
- info:eu-repo/grantAgreement/Education Department of the Junta de Castilla y León//LE112G18
URI
DOI
Aparece en las colecciones
- Artículos [5167]
Ficheros en el ítem
Tamaño:
2.279
xmlui.dri2xhtml.METS-1.0.size-megabytes
Formato:
Adobe PDF