Total polyphenol content and antioxidant capacity were estimated in various food and nutraceutical samples, including cranberries, raspberries, artichokes, grapevines, green tea, coffee, turmeric, and other medicinal plant extracts. Samples were analyzed by using two antioxidant assays-ferric reducing antioxidant power (FRAP) and Folin-Ciocalteu (FC)-and a reversed-phase high-performance liquid chromatography (HPLC), with a focus on providing compositional fingerprints dealing with polyphenolic compounds. A preliminary data exploration via principal component analysis (PCA) revealed that HPLC fingerprints were suitable chemical descriptors to classify the analyzed samples according to their nature. Moreover, chromatographic data were correlated with antioxidant data using partial least squares (PLS) regression. Regression models have shown good prediction capacities in estimating the antioxidant activity from chromatographic data, with determination coefficients (R2) of 0.971 and 0.983 for FRAP and FC assays, respectively.
Keywords: Folin–Ciocalteu; antioxidant capacity; ferric reducing antioxidant power; high-performance liquid chromatography; partial least squares; polyphenols; principal component analysis.