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1H NMR Spectroscopy to Characterize Italian Extra Virgin Olive Oil Blends, Using Statistical Models and Databases Based on Monocultivar Reference Oils
- Source :
- Foods, Vol 9, Iss 1797, p 1797 (2020), Foods, Volume 9, Issue 12
- Publication Year :
- 2020
- Publisher :
- MDPI AG, 2020.
-
Abstract
- During the last few years, the global demand for extra virgin olive oil (EVOO) is increased. Olive oil represents a significant percentage of world fat consumption determining an important development of its market. In this context, the problems related to counterfeiting and product fraud is becoming extremely relevant. Thus, the quality and authenticity control of EVOOs is nowadays mandatory. In this study we focused on the use of 1H NMR technique associated with multivariate statistical analysis to characterize Italian EVOOs commercial blends. In particular, a specific database including 126 monocultivar EVOOs reference samples, was used to characterize a total of 241 Italian EVOOs blends over four consecutive harvesting years. Moreover, the effect of the minor components (phenolic compounds) on the qualitative characterization of blended EVOOs was also evaluated. The correlation analysis of classification scores obtained using two pairwise orthogonal partial least square-discriminant analysis models (built with major and combined major&ndash<br />minor components NMR data) revealed that both could be profitably used to generally classify the studied Coratina containing blends.
- Subjects :
- 1h nmr spectroscopy
Health (social science)
1H-NMR spectroscopy
Context (language use)
Analysis models
Plant Science
computer.software_genre
lcsh:Chemical technology
Health Professions (miscellaneous)
Microbiology
Article
extra virgin olive oil
Chemometrics
lcsh:TP1-1185
Mathematics
Database
Statistical model
chemometrics
Nmr data
traceability
quality
Correlation analysis
computer
Food Science
Olive oil
Subjects
Details
- Language :
- English
- ISSN :
- 23048158
- Volume :
- 9
- Issue :
- 1797
- Database :
- OpenAIRE
- Journal :
- Foods
- Accession number :
- edsair.doi.dedup.....d8e4c42943e7a89e377df889d6209639