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Detection of Adulterated Oregano Samples Using Untargeted Headspace-Gas Chromatography-Ion Mobility Spectrometry Analysis.
Rocamora-Rivera, Blas; Arroyo-Manzanares, Natalia; Viñas, Pilar.
Afiliación
  • Rocamora-Rivera B; Department of Analytical Chemistry, Faculty of Chemistry, University of Murcia, 30100 Murcia, Spain.
  • Arroyo-Manzanares N; Department of Analytical Chemistry, Faculty of Chemistry, University of Murcia, 30100 Murcia, Spain.
  • Viñas P; Department of Analytical Chemistry, Faculty of Chemistry, University of Murcia, 30100 Murcia, Spain.
Foods ; 13(4)2024 Feb 07.
Article en En | MEDLINE | ID: mdl-38397493
ABSTRACT
Oregano is often adulterated for economic reasons. This fraud mainly consists of adding other species with lower commercial value, such as olive leaves. To ensure the authenticity of oregano, an analytical method based on the analysis of the volatile organic compound (VOC) profile obtained by headspace gas chromatography coupled to ion mobility spectrometry (HS-GC-IMS) was developed and validated. Samples of ecological Mediterranean oregano adulterated with different percentages of two types of olive leaves (cornicabra and manzanilla) were studied using a non-targeted analysis. Moreover, a total of 30 VOCs were identified in the analyzed samples, and 24 compounds could be quantified using calibration curves based on Boltzmann's equation. A chemometric model based on orthogonal partial least squares discriminant analysis (OPLS-DA) was used to detect the adulterated oregano samples, obtaining a 100% validation success rate, and partial least squares (PLS) analysis was used to quantify the percentage of adulterant. Finally, the proposed methodology was applied to 15 commercial oregano samples, resulting in two of them being classified as adulterated with 31 and 43% of olive leaves, respectively.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Foods Año: 2024 Tipo del documento: Article País de afiliación: España

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Foods Año: 2024 Tipo del documento: Article País de afiliación: España