Monitoring of fresh-cut spinach leaves through multispectral vision and sensory evaluation

Lunadei, Loredana; Lleó García, Lourdes; Diezma Iglesias, Belen y Ruiz-Altisent, Margarita (2011). Monitoring of fresh-cut spinach leaves through multispectral vision and sensory evaluation. En: "2011 CIGR Section VI International Symposium", 18-20 Abril 2011, Nantes (France).

Descripción

Título: Monitoring of fresh-cut spinach leaves through multispectral vision and sensory evaluation
Autor/es:
  • Lunadei, Loredana
  • Lleó García, Lourdes
  • Diezma Iglesias, Belen
  • Ruiz-Altisent, Margarita
Tipo de Documento: Ponencia en Congreso o Jornada (Póster)
Título del Evento: 2011 CIGR Section VI International Symposium
Fechas del Evento: 18-20 Abril 2011
Lugar del Evento: Nantes (France)
Título del Libro: Towards a Sustainable Food Chain - Food Process, Bioprocessing and Food Quality Management
Fecha: Abril 2011
Materias:
Palabras Clave Informales: Leaf vegetable; multispectral image; ready-to-use; visual evaluation.
Escuela: E.T.S.I. Agrónomos (UPM) [antigua denominación]
Departamento: Ingeniería Rural [hasta 2014]
Grupo Investigación UPM: LPF-TAGRALIA
Licencias Creative Commons: Ninguna

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Resumen

The aim of this work was to compare an image algorithm to detect changes in quality related with changes in leaf pigments content in leafy spinach during storage with a visual evaluation using a 1-4 scale, where 1 corresponds to fresh samples without any spoilage and 4 to samples with severe deterioration, in order to obtain a sensory evaluation index (ISE) for each sample. The experiment was carried out on packed ready-to-use spinach stored at 4.5°C or 10ºC. Seventy-five leaves of spinach were analyzed at zero time and after 7, 14 and 21 days of storage at 4.5º C. Twenty-four e samples were measured at zero time and after 3, 6 and 9 days of storage at 10º C. Multispectral images were acquired in the red (R, 680±20 nm), infrared (IR, 800±20 nm) and blue (B, 450±20 nm) regions. Virtual images were calculated on the basis of spectral indexes usually employed for estimation of leaf pigment content. By considering the sensitive bands to chlorophyll, new virtual images were proposed. A non-supervised classification was applied to the obtained virtual images and the results were evaluated according to colorimetric measurements (CIE L*a*b* coordinates) and visual evaluation. Virtual images computed from R and B ranges gave the better results detecting changes in quality along period storage at 4.5º C. These virtual images were able to classify samples into two reference classes, including respectively the major part of the samples analyzed on zero time and on the 7th day and samples analyzed on the 14th and the 21th days.

Más información

ID de Registro: 9708
Identificador DC: http://oa.upm.es/9708/
Identificador OAI: oai:oa.upm.es:9708
Depositado por: Investigador contratado Loredana Lunadei
Depositado el: 16 Nov 2011 12:02
Ultima Modificación: 20 Abr 2016 18:01
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