Geographical origin classification of olive oils by PTR-MS

N. Araghipour, J. Colineau, A.H. Koot, W. Akkermans, J.M.M. Rojas, J. Beauchamp, A. Wisthaler, T.D. Märk, G. Downey, C. Guillou, L. Mannina, S.M. van Ruth

Research output: Contribution to journalArticleAcademicpeer-review

83 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)374-383
JournalFood Chemistry
Volume108
Issue number1
DOIs
Publication statusPublished - 2008

Keywords

  • resolution gas-chromatography
  • mass-spectrometry
  • volatile compounds
  • quality
  • aroma
  • extraction
  • headspace

Fingerprint Dive into the research topics of 'Geographical origin classification of olive oils by PTR-MS'. Together they form a unique fingerprint.

Cite this