Jams fruit products characterized by acid pH, which under high temperatures, can be affected by reactions of oxidation of ascorbic acid and caramelization of sugars. Extra quality jams seem to be more sensitive to this phenomenon because fructose caramelizes at lower temperatures than sucrose. The most important effect of overheating is the browning, and it is possible to monitor it by image analysis, and especially by the b* colour coordinate. The large variability observed in the grey level of histograms of the b* image, probably due to the heterogeneous particle composition of jam, may be avoided by k-means clustering applied about jam images. This allows to segregate fruit fragments from homogeneous jam areas, using only these ones to extract the colour coordinates to characterise that image. These results show that it is possible to implement a vision system to supervise colour changes in the productive process of jams. Additionally, differences in the optical density of overheated samples in comparison to control samples have been reported. It is possible to detect overheated samples using mean grey level in the area affected by the red LED light.

Instrumental parameters describing the quality of peach and apricot "extra jams", as influenced by excess heating

RICAUDA AIMONINO, Davide;
2008-01-01

Abstract

Jams fruit products characterized by acid pH, which under high temperatures, can be affected by reactions of oxidation of ascorbic acid and caramelization of sugars. Extra quality jams seem to be more sensitive to this phenomenon because fructose caramelizes at lower temperatures than sucrose. The most important effect of overheating is the browning, and it is possible to monitor it by image analysis, and especially by the b* colour coordinate. The large variability observed in the grey level of histograms of the b* image, probably due to the heterogeneous particle composition of jam, may be avoided by k-means clustering applied about jam images. This allows to segregate fruit fragments from homogeneous jam areas, using only these ones to extract the colour coordinates to characterise that image. These results show that it is possible to implement a vision system to supervise colour changes in the productive process of jams. Additionally, differences in the optical density of overheated samples in comparison to control samples have been reported. It is possible to detect overheated samples using mean grey level in the area affected by the red LED light.
2008
Ageng2008 Conference "Agricultural & Biosystems Engineering for a Sustainable World"
Hernissos - Crete - Greece
23-25 June 2008
Agricultural & Biosystems Engineering for a Sustainable World
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On CD, paper OP-2105
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http://www.ageng2008.com
Belen Diezma-Iglesias; Davide Ricauda Aimonino; E Correa; Margarita Ruiz-Altisent
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/123680
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