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Monitoring oxidative quality of pork scratchings, peanuts, oatmeal and muesli by sensor array
Author(s) -
Jensen Pernille N,
Bertelsen Grete,
van den Berg Frans
Publication year - 2004
Publication title -
journal of the science of food and agriculture
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.782
H-Index - 142
eISSN - 1097-0010
pISSN - 0022-5142
DOI - 10.1002/jsfa.1946
Subject(s) - hexanal , electronic nose , sensor array , food science , chemistry , process engineering , computer science , chromatography , artificial intelligence , engineering , machine learning
A sensor array (electronic nose) was successfully applied for predicting the content of hexanal and other volatiles in different dry fat‐containing products, showing the potential of replacing time‐consuming traditional laboratory analysis by faster in‐process monitoring methods. Unfortunately, prediction of free radical content was not successful, making early prediction of oxidation by sensor array infeasible. Owing to the non‐specificity of the sensors, a generic model could not be generated even though a series of standards was shown to have a high correlation between hexanal concentration and individual or multiple sensor responses. PCA models of sensor array responses of eg pork scratchings revealed a clear separation of samples stored in the experimental factor light versus darkness. Copyright © 2004 Society of Chemical Industry