Comparison of multispectral indexes extracted from hyperspectral images for the assessment of fruit ripening

The present research is focused on the application of artificial vision to assess the ripening of red skinned soft-flesh peach (‘Richlady’). Artificial vision allows a spatially detailed determination of the ripening stage of the fruit. The considered optical indexes (Ind 1 and Ind 2, proposed in th...

Full description

Saved in:
Bibliographic Details
Published in:Journal of food engineering Vol. 104; no. 4; pp. 612 - 620
Main Authors: Lleó, L., Roger, J.M., Herrero-Langreo, A., Diezma-Iglesias, B., Barreiro, P.
Format: Journal Article
Language:English
Published: Oxford Elsevier Ltd 01-06-2011
[New York, NY]: Elsevier Science Pub. Co
Elsevier
Subjects:
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The present research is focused on the application of artificial vision to assess the ripening of red skinned soft-flesh peach (‘Richlady’). Artificial vision allows a spatially detailed determination of the ripening stage of the fruit. The considered optical indexes (Ind 1 and Ind 2, proposed in the present research, and Ind 3 and I AD, proposed by other authors) are based on the combination of wavelengths close to the chlorophyll absorption peak at 680 nm. Ind 1 corresponds approximately to the depth of the absorption peak, and Ind 2 corresponds to the relative absorption peak. An artificial image of each index was obtained by computing the corresponding reflectance images, which were acquired with a hyperspectral camera. All indexes were able to correct convexity (except for the just-harvested peaches and for Ind 1). Ind 2 is the preferred index; it showed the highest discriminating power between ripening stages and no influence of convexity. Ind 2 also allowed the differentiation of ripening regions within the fruits, and it showed the evolution of those regions during ripening.
Bibliography:http://dx.doi.org/10.1016/j.jfoodeng.2011.01.028
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0260-8774
1873-5770
DOI:10.1016/j.jfoodeng.2011.01.028