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Current Analytical Chemistry

Editor-in-Chief

ISSN (Print): 1573-4110
ISSN (Online): 1875-6727

Research Article

HPLC Fingerprints for the Authentication of Cranberry-Based Products Based on Multivariate Calibration Approaches

Author(s): Lidia Puigventos, Oscar Nunez* and Javier Saurina

Volume 13, Issue 3, 2017

Page: [256 - 261] Pages: 6

DOI: 10.2174/1573411012666160216220526

Price: $65

Abstract

Background: Food products and pharmaceuticals prepared with American red cranberries are gaining importance in our society due to some healthy effects on humans. However, some concerns have arisen on the evaluation of authenticity of red cranberry extracts as well as on the detection of possible adulterations with less expensive fruits like grapes or blueberries, which do not contain the appropriate polyphenols for having the desired bioactivity. This fact reveals the importance of developing analytical methodologies for the characterization of natural extracts to deal with authentication issues regarding the fruit of origin.

Methods: HPLC-UV polyphenolic fingerprints of pure cranberry extracts and cranberry-based extracts adulterated with grape at different percentages were obtained and analyzed by chemometric methods (principal component analysis and partial least square regression).

Results: Preliminary studies of HPLC-UV polyphenolic fingerprints by principal component analysis showed that the sample extracts were clearly distributed depending on the extent of adulteration with grape. Data was then further treated by partial least square regression to determine the percentages of grape contamination. It was found that even mixture samples containing low percentages of grape could be distinguished from genuine cranberry extracts. Besides, results obtained were highly satisfactory, with overall quantification errors lower than 5%.

Conclusion: The proposed HPLC-UV method resulted in an excellent approach to carry out the authentication of cranberry-based products relying on polyphenolic fingerprints.

Keywords: Liquid chromatography, polyphenolic fingerprints, cranberry, authentication, chemometrics, partial least square regression.

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