Skip to content
2000
Volume 17, Issue 7
  • ISSN: 1573-4110
  • E-ISSN: 1875-6727

Abstract

Background: This work describes a fast, simple, sensitive, and low-cost method for the identification of resveratrol in different brands and varieties of red wines. Methods: It was developed based on a comparison of the UV-VIS spectra of the samples and samples enriched with different concentrations of the trans-resveratrol standard. The spectra were analyzed by chemometric principal component analysis (PCA) and multivariate calibration. Results: The PCA data indicated that only 4 main components made possible group samples based on the grape variety characteristics and/or production region. Conclusion: From the construction of partial least squares (PLS) and multiple linear regression (RLM) models, it was possible to predict the sample trans-resveratrol content with that sample showing similarities between the groups observed in the PCA and the samples used in the model constructions. The predicted trans-resveratrol present in these samples ranged from 0.29 to 23.3 mg L-1. This multivariate method suggested a good predictive capacity of determination of resveratrol concentrations in commercial red wines.

Loading

Article metrics loading...

/content/journals/cac/10.2174/1573411017666201229142412
2021-09-01
2025-07-11
Loading full text...

Full text loading...

/content/journals/cac/10.2174/1573411017666201229142412
Loading

  • Article Type:
    Research Article
Keyword(s): Multivariate methods; PCA; PLS; red wine; trans-resveratrol; UV-Vis
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test