Memorias de investigación
Artículos en revistas:
Multispectral Vision for Monitoring Peach Ripeness
Año:2011

Áreas de investigación
  • Agricultura,
  • Ingenierías

Datos
Descripción
The main objective of this research was to develop an automatic procedure able to classify Rich Lady commercial peaches according to their ripeness stage through multispectral imaging techniques. A classification procedure was applied to the ratio images calculated as red (R, 680 nm) divided by infrared (IR, 800 nm), that is, R/IR images. Four imagebased ripeness reference classes (A: unripe to D: overripe) were generated from 380 fruit images (season 1: 2006) by a nonsupervised classification method and evaluated according to reference measurements of the ripeness of the same samples: Magness-Taylor penetrometry firmness, low-mass impact firmness, reflectance at 680 nm (R680, and soluble solids content. The assignment of unknown sample images from those season 1 images (internal validation, n = 380) and of 240 images from the 2nd season (season 2: 2007) to the ripeness reference classes (external validation) was carried out by computing the minimum Euclidean distance (classification distance, Cd) between each unknown image histogram and the average histogram of each ripeness reference class. For both validation phases, firmness values decreased and R680 increased for increasing alphabetical order of image-based class letter, reflecting the ripening process. Moreover, 70% (season 1) and 80% (season 2) of the samples below bruise susceptibility firmness were classified into class D.
Internacional
Si
JCR del ISI
Si
Título de la revista
Journal of Food Science
ISSN
1750-3841
Factor de impacto JCR
1,6
Información de impacto
Volumen
76
DOI
10.1111/j.1750-3841.2010.02000.x
Número de revista
2
Desde la página
178
Hasta la página
187
Mes
SIN MES
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Participantes

Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: LPF-TAGRALIA: Técnicas Avanzadas en Agroalimentación