[en] Virgin olive oil quality assessment is critical for consumer protection and industry regulation. Fraudulent activities involving virgin olive oil are common worldwide. In Brazil, recent nationwide inspections have revealed recurrent cases of fraud, including the sale of adulterated or mislabeled olive oils. As a result, the Brazilian federal agency has suspended the commercialization of numerous brands and seized large quantities of products that failed to meet the official quality requirements. This study presents an automated analytical workflow for classifying Brazilian virgin olive oils based on their volatile organic compound (VOC) profiles. Headspace solid-phase microextraction (HS-SPME) and comprehensive two-dimensional gas chromatography-mass spectrometry (GC×GC-MS) were used to analyze 215 certified virgin olive oil samples, categorized as either defective (VOO, virgin and LVOO, lampante virgin) or non-defective (EVOO, extra virgin), and 21 undisclosed oils (UNKN). Chemometric modeling using partial least squares-discriminant analysis (PLS-DA) was applied to the resulting data, which comprised 108 recurring VOCs. The PLS-DA model successfully differentiated between the two quality classes (defective and non-defective) with a predictive accuracy of 91% based on the external validation set. Key chemical markers driving the classification were identified. Non-defective oils were characterized by higher levels of C5 and C6 aldehydes and alcohols from the lipoxygenase (LOX) pathway, such as (E)-2-hexenal, associated with positive green and fruity notes. Conversely, defective oils showed higher levels of compounds such as nonanal and acetic acid, linked to rancidity and other off-flavors. Finally, the model was used to predict the quality of 21 previously undisclosed samples. This instrumental approach demonstrates a powerful and reliable alternative for forensic analysis of olive oils, generating models that can be interpreted in sensory terms.
Disciplines :
Food science
Author, co-author :
Cunha Paiva, Andre; Instituto de Química (IQ), Universidade Estadual de Campinas, Rua Monteiro Lobato, 270, Campinas, SP, 13083-862, Brazil ; Instituto Nacional de Ciência e Tecnologia (INCTBio), Campinas, SP, Brazil
Passos de Resende, Glaucimar Alex ; Université de Liège - ULiège > Molecular Systems (MolSys) ; Instituto de Química (IQ), Universidade Estadual de Campinas, Rua Monteiro Lobato, 270, Campinas, SP, 13083-862, Brazil ; Instituto Nacional de Ciência e Tecnologia (INCTBio), Campinas, SP, Brazil
Barbosa, Luidy Darllan; Instituto de Química (IQ), Universidade Estadual de Campinas, Rua Monteiro Lobato, 270, Campinas, SP, 13083-862, Brazil
Dantas Freitas, Daniel Lucas; OpenScience, Campinas, SP, Brazil
Sabin, Guilherme Post; OpenScience, Campinas, SP, Brazil
Hantao, Leandro Wang ; Instituto de Química (IQ), Universidade Estadual de Campinas, Rua Monteiro Lobato, 270, Campinas, SP, 13083-862, Brazil. wang@unicamp.br ; Instituto Nacional de Ciência e Tecnologia (INCTBio), Campinas, SP, Brazil. wang@unicamp.br ; Núcleo Interdisciplinar de Planejamento Energético (NIPE), Campinas, SP, Brazil. wang@unicamp.br
Language :
English
Title :
Quality assessment of Brazilian olive oils by GC×GC-MS and chemometrics.
Publication date :
May 2026
Journal title :
Analytical and Bioanalytical Chemistry
ISSN :
1618-2642
eISSN :
1618-2650
Publisher :
Springer Science and Business Media Deutschland GmbH, Germany
CAPES - Coordenação de Aperfeicoamento de Pessoal de Nível Superior FAPESP - Fundação de Amparo à Pesquisa do Estado de São Paulo CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico
Funding text :
The Article Processing Charge (APC) for the publication of this research was funded by the Coordena\u00E7\u00E3o de Aperfei\u00E7oamento de Pessoal de N\u00EDvel Superior - Brasil (CAPES) (ROR identifier: 00x0ma614). This study received funding from the National Council for Scientific and Technological Development (CNPq) (Grants 302748/2018\u20130, 316202/2021\u20135, 408338/2024\u20135, and 306108/2025\u20139), the S\u00E3o Paulo Research Foundation (FAPESP) (Grant 2022/07406\u20131), and the Coordination for the Improvement of Higher Education Personnel (CAPES) (Finance Code 001). Additionally, the instruments used in this study were provided through funding from ANP/PETROBRAS (Grants 2019/00209\u20133 and 2019/00210\u20131).
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