Application of principal component and hierarchical cluster analysis to classify different spices based on in vitro antioxidant activity and individual polyphenolic antioxidant compounds

Mohammad B. Hossain, Ankit Patras, Catherine Barry-Ryan, Ana B. Martin-Diana, Nigel P. Brunton

Research output: Contribution to journalArticlepeer-review

Abstract

This study investigated the variations in antioxidant profiles between spices using pattern recognition tools; classification was achieved based on the results of global antioxidant activity assays (2,2-diphenyl-1-picrylhydrazyl [DPPH], oxygen radical absorbance capacity [ORAC], ferric reducing antioxidant power [FRAP], microsomal lipid peroxidation [MLP] and 2,2′-azinobis(3-ethylbenzothiazoline-6-sulfonic acid) [ABTS]), levels of different polyphenolic compounds (gallic acid [GA], carnosol [CAR], carnosic acid [CRA], caffeic acid [CA], rosmarinic acid [RA], luteolin-7- O-glucoside [LOG], apigenin-7-O-glucoside [APOG] and total phenols [TP]) of spices namely rosemary, oregano, marjoram, sage, basil, thyme, fennel, celery, cumin and parsley, commonly consumed in Ireland were analyzed. Rosemary showed the highest antioxidant activity measured by the DPPH (11.02. g. Trolox/g. DW) assay, whereas oregano had the highest activity in the ORAC (28.31. g. Trolox/g. DW) test. By contrast, parsley showed the lowest antioxidant activity in both of the assays. Interrelationships of these assays and the spices were investigated by principal component analysis (PCA) and hierarchical cluster analysis (HCA). PCA revealed that the first two components represented 73% of the total variability in antioxidant activity and different antioxidant groups. HCA classified samples into four main groups on the basis of the measured parameters.

Original languageEnglish
Pages (from-to)179-189
Number of pages11
JournalJournal of Functional Foods
Volume3
Issue number3
DOIs
Publication statusPublished - Jul 2011

Keywords

  • Antioxidant activity
  • Hierarchical cluster analysis
  • Polyphenol
  • Principal component analysis
  • Spices

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