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|Title:||Geographical Origin Classification of Olive Oils by PTR-MS|
|Authors:||ARAGHIPOUR Nooshin; COLINEAU Jennifer; KOOT Alex; AKKERMANS Wies; MORENO ROJAS JOSE'; BEAUCHAMP Jonathan; WISTHALER Armin; MARK Tilmann D.; DOWNEY Gerard; GUILLOU CLAUDE; MANNINA Luisa; VAN RUTH Saskia|
|Citation:||FOOD CHEMISTRY vol. 108 p. 374-383|
|Publisher:||ELSEVIER SCI LTD|
|Type:||Articles in periodicals and books|
|Abstract:||The volatile compositions of 192 olive oil samples from five different European countries were investigated by PTR-MS sample headspace analysis. The mass spectra of all samples showed many masses with high abundances, indicating the complex VOC composition of olive oil. Three different PLS-DA models were fitted to the data to classify samples into country, region and district of origin, respectively. Correct classification rates were assessed by cross-validation. The first fitted model produced an 86% success rate in classifying the samples into their country of origin. The second model, which was fitted to the Italian oils only, also demonstrated satisfactory results, with 74% of samples successfully classified into region of origin. The third model, classifying the Italian samples into district of origin, yielded a success rate of only 52%. This lower success rate might be due to either the small class set, or to genuine similarities between olive oil VOC compositions on this tight scale.|
|JRC Institute:||Institute for Health and Consumer Protection|
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