This paper investigates the effectiveness of electronic nose with subsequent principal component analysis (PCA) treatment of data for differentiation of food samples of varied odour quality caused by lipid oxidation. Samples were evaluated for off-flavours with an electronic nose and a sensory analysis and for Totox value. Volatile compounds of fresh samples and samples subjected to storage test at 60°C were isolated with a static headspace technique. The results suggest that the electronic nose could help to supplement the sensory analysis. Models based on partial least-squares analysis were able to predict the oxidized flavour attribute of samples, with correlation coefficients ranging from 0.66 to 0.99. Based on elaborated methods and data treatment with PCA it was possible to distinguish between different food samples and monitor the formation of off-flavours associated with lipid oxidation.
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