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

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

Description

Title: Monitoring of fresh-cut spinach leaves through multispectral vision and sensory evaluation
Author/s:
  • Lunadei, Loredana
  • Lleó García, Lourdes
  • Diezma Iglesias, Belen
  • Ruiz-Altisent, Margarita
Item Type: Presentation at Congress or Conference (Poster)
Event Title: 2011 CIGR Section VI International Symposium
Event Dates: 18-20 Abril 2011
Event Location: Nantes (France)
Title of Book: Towards a Sustainable Food Chain - Food Process, Bioprocessing and Food Quality Management
Date: April 2011
Subjects:
Freetext Keywords: Leaf vegetable; multispectral image; ready-to-use; visual evaluation.
Faculty: E.T.S.I. Agrónomos (UPM) [antigua denominación]
Department: Ingeniería Rural [hasta 2014]
UPM's Research Group: LPF-TAGRALIA
Creative Commons Licenses: None

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Abstract

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.

More information

Item ID: 9708
DC Identifier: http://oa.upm.es/9708/
OAI Identifier: oai:oa.upm.es:9708
Deposited by: Investigador contratado Loredana Lunadei
Deposited on: 16 Nov 2011 12:02
Last Modified: 20 Apr 2016 18:01
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