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.
Sinelli N., Cerretani L., Di Egidio V., Bendini A., Casiraghi E. (2010). Application of near (NIR) infrared and mid (MIR) infrared spectroscopy as a rapid tool to classify extra virgin olive oil on the basis of fruity attribute intensity. FOOD RESEARCH INTERNATIONAL, 43, 369-375 [10.1016/j.foodres.2009.10.008].
Application of near (NIR) infrared and mid (MIR) infrared spectroscopy as a rapid tool to classify extra virgin olive oil on the basis of fruity attribute intensity
CERRETANI, LORENZO;BENDINI, ALESSANDRA;
2010
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
