Article ID Journal Published Year Pages File Type
4562302 Food Research International 2010 7 Pages PDF
Abstract

A sensory analysis of 112 virgin olive oils was performed by a fully trained taste panel. The samples were divided in “defective” and “not defective” on the basis of their olfactory attributes. Then, the “not defective” samples were classified into “low”, “medium” and “high” according to the fruity aroma intensity perceived by assessors. All samples were also analysed by FT-NIR and FT-IR spectroscopy and processed by classification methods (LDA and SIMCA). The results showed that NIR and MIR spectroscopy coupled with statistical methods are an interesting technique compared with traditional sensory assessment in classifying olive oil samples on the basis of the fruity attribute. The prediction rate varied between 71.6% and 100%, as average value. The spectroscopic methods, combined with chemometric strategies, could represent a reliable, cheap and fast classification tool, able to draw a complete fingerprint of a food product, describing its intrinsic quality attributes, that include its sensory attributes.

Related Topics
Life Sciences Agricultural and Biological Sciences Food Science
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