4.6 Article

An Electronic Nose as a Non-Destructive Analytical Tool to Identify the Geographical Origin of Portuguese Olive Oils from Two Adjacent Regions

期刊

SENSORS
卷 22, 期 24, 页码 -

出版社

MDPI
DOI: 10.3390/s22249651

关键词

EVOO quality; sensory analysis; oxidative stability; metal oxide semiconductor sensors; multivariate qualitative-quantitative analysis; resistance electrical signals; feature extraction parameters

资金

  1. Foundation for Science and Technology (FCT, Portugal) [UIDB/00690/2020, UIDP/00690/2020, LA/P/0007/2020]
  2. FCT (Portugal) [COA/BRB/0035/2019]
  3. FCT- Foundation for Science and Technology, P.I.

向作者/读者索取更多资源

The geographical traceability of extra virgin olive oils (EVOO) is crucial for oil chain actors and consumers. This study evaluated oils produced in two Portuguese regions and found differences in total phenol contents, oxidative stabilities, and flavor characteristics. By using an electronic nose and chemical analysis, the geographical origin of the oils and the contents of major volatile chemical classes could be successfully identified.
The geographical traceability of extra virgin olive oils (EVOO) is of paramount importance for oil chain actors and consumers. Oils produced in two adjacent Portuguese regions, Coa (36 oils) and Douro (31 oils), were evaluated and fulfilled the European legal thresholds for EVOO categorization. Compared to the Douro region, oils from Coa had higher total phenol contents (505 versus 279 mg GAE/kg) and greater oxidative stabilities (17.5 versus 10.6 h). The majority of Coa oils were fruity-green, bitter, and pungent oils. Conversely, Douro oils exhibited a more intense fruity-ripe and sweet sensation. Accordingly, different volatiles were detected, belonging to eight chemical families, from which aldehydes were the most abundant. Additionally, all oils were evaluated using a lab-made electronic nose, with metal oxide semiconductor sensors. The electrical fingerprints, together with principal component analysis, enabled the unsupervised recognition of the oils' geographical origin, and their successful supervised linear discrimination (sensitivity of 98.5% and specificity of 98.4%; internal validation). The E-nose also quantified the contents of the two main volatile chemical classes (alcohols and aldehydes) and of the total volatiles content, for the studied olive oils split by geographical origin, using multivariate linear regression models (0.981 <= R-2 <= 0.998 and 0.40 <= RMSE <= 2.79 mg/kg oil; internal validation). The E-nose-MOS was shown to be a fast, green, non-invasive and cost-effective tool for authenticating the geographical origin of the studied olive oils and to estimate the contents of the most abundant chemical classes of volatiles.

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