Quantitative Detection of Virgin Olive Oil Adulteration With Olive-Derived Oils by Near- and Mid-Infrared Spectroscopy

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Ayvaz H., Öğütcü M., Doğan M. A., Aydın U.

EUROPEAN JOURNAL OF LIPID SCIENCE AND TECHNOLOGY, cilt.12870157, 2026 (SCI-Expanded, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 12870157
  • Basım Tarihi: 2026
  • Dergi Adı: EUROPEAN JOURNAL OF LIPID SCIENCE AND TECHNOLOGY
  • Derginin Tarandığı İndeksler: Applied Science & Technology Source, Academic Search Ultimate (EBSCO), Biomedical Reference Collection: Corporate Edition (EBSCO), Scopus, Materials Science & Engineering Collection (ProQuest), Pharma Collection (ProQuest), Technology Collection (ProQuest), Science Citation Index Expanded (SCI-EXPANDED), BIOSIS, Chemical Abstracts Core
  • Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
  • Çanakkale Onsekiz Mart Üniversitesi Adresli: Evet

Özet

The main purpose of this study was to quantify adulteration of virgin olive oil (VOO) with lower priced olive-derived oils, namely,
olive pomace oil (OPO) and refined olive oil–virgin olive oil blends (ROO), using infrared (IR) spectroscopy combined with
chemometrics. Five samples from each group (VOO, OPO, and ROO) were purchased and analyzed for common physicochemical
parameters, including free fatty acids, peroxide value, conjugated dienes/trienes, chlorophylls, and carotenoids. Significant
differences were observed among VOO, OPO, and ROO across quality attributes: VOO and OPO differed in all properties, VOO
and ROO in all except K232 values, and ROO and OPO only in conjugated dienes and carotenoids. To evaluate adulteration, equally
pooled oils from each group were blended, yielding 120 OPO–VOO and 120 ROO–VOO mixtures with adulterant levels from
0.05% to 100% (w/w). Spectra were collected using benchtop FT-MIR, benchtop FT-NIR, and handheld NIR spectrometers. All
developed partial least squares regression models showed high predictive performance for quantifying OPO and ROO in VOO. For
OPO quantification, benchtop FT-NIR with a 6-mm transflectance accessory gave the best results (residual predictive deviation
[RPD] = 28.0), followed by FT-MIR with ATR (RPD = 13.8). For ROO prediction, FT-MIR performed slightly better (RPD = 21.8)
than FT-NIR (RPD = 20.4). Pathlength effects in NIR applications (1 vs. 6 mm) strongly influenced model performance, with 6 mm
yielding superior outcomes. Handheld NIR, although less accurate (RPD = 5.69–8.59), still provided reliable estimates, offering
rapid and on-site screening for fraud prevention in the olive oil sector.