Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2022 Mar 22;11(7):910.
doi: 10.3390/foods11070910.

Use of Multivariate Statistics in the Processing of Data on Wine Volatile Compounds Obtained by HS-SPME-GC-MS

Maria Tufariello  1 , Sandra Pati  2 , Lorenzo Palombi  3 , Francesco Grieco  1 , Ilario Losito  4
Affiliations
Review

Use of Multivariate Statistics in the Processing of Data on Wine Volatile Compounds Obtained by HS-SPME-GC-MS

Maria Tufariello et al. Foods. .

Abstract

This review takes a snapshot of the main multivariate statistical techniques and methods used to process data on the concentrations of wine volatile molecules extracted by means of solid phase micro-extraction and analyzed using GC-MS. Hypothesis test, exploratory analysis, regression models, and unsupervised and supervised pattern recognition methods are illustrated and discussed. Several applications in the wine volatolomic sector are described to highlight different interactions among the various matrix components and volatiles. In addition, the use of Artificial Intelligence-based methods is discussed as an innovative class of methods for validating wine varietal authenticity and geographical traceability.

Keywords: HS-SPME-GC-MS; artificial intelligence; multivariate statistical analysis; volatile compounds; wine.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Number of published articles between 1998 and 2022 related to HS-SPME/wine/volatile.
Figure 2
Figure 2
Schematic diagram of different objectives and multivariate statistical analysis techniques used for HS-SPME/GC-MS data.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Ribéreau-Gayon P., Dubourdie D., Donèche B., Lovaud A. Handbook of Enolgy. John Wiley Sons, Ltd.; Hoboken, NJ, USA: 2006.
    1. Alanon M.E., Perez-Coello M.S., Marina M.L. Wine science in the metabolomics era. TRAC-Trend Anal. Chem. 2015;74:1–20. doi: 10.1016/j.trac.2015.05.006. - DOI
    1. Diez-Simon C., Mumm R., Hall R.D. Mass spectrometry-based metabolomics of volatiles as a new tool for understanding aroma and flavour chemistry in processed food products. Metabolomics. 2019;15:41. doi: 10.1007/s11306-019-1493-6. - DOI - PMC - PubMed
    1. Cozzolino D., Cynkar W.U., Shah N., Dambergs R.G., Smith P.A. A brief introduction to multivariate methods in grape and wine analysis. Int. J. Wine Res. 2009;1:123–130. doi: 10.2147/IJWR.S4585. - DOI
    1. Bordiga M., Rinaldi M., Locatelli M., Piana G., Travaglia F. Characterization of Muscat wines aroma evolution using comprehensive gas chromatography followed by a post-analytic approach to 2D contour plots comparison. Food Chem. 2013;140:57–67. doi: 10.1016/j.foodchem.2013.02.051. - DOI - PubMed

LinkOut - more resources