Chlorogenic Acid Profiles and Antioxidant Potentials of 17 Sweet Potato Varieties Cultivated in Korea: Impact of Extraction Condition and Classification by Hierarchical Clustering Analysis

Journal Title: Journal of Food Chemistry and Nanotechnology - Year 2015, Vol 1, Issue 1

Abstract

A high resolution LC-ESI-QTOF-MS, LC-MS/MS, and HPLC-DAD analysis were conducted to isolate, identify and quantify the chlorogenic acids in 17 sweet potato varieties cultivated in Korea. The impacts of extracting solvent mixture system on the quantity and composition chlorogenic acids of the extracts were studied. It was found that extracting solvent mixture system greatly affected the quantity and quality of chlorogenic acids in the extracts of sweet potato. The optimum extracting solvent system was selected for extracting the chlorogenic acids from sweet potatoes. The profiles and quantities of chlorogenic acids in sweet potatoes were greatly different with variety, showing about 30-fold variation in quantity. Juhwangmi contained the highest quantity of chlorogenic acid (2393.65 μg/g dry weight), while Matnami contained the least quantity of chlorogenic acid (68.62 μg/g dry weight). High correlations (>0.97) were observed between chlorogenic acid contents and antioxidant potential data from DPPH, ABTS, FARP, and total phenolic assays. Sweet potatoes were statistically classified in 4 well defined groups in terms of their similarity in chlorogenic acid profile and quantity. This represents the first report on the profiles and quantity of chlorogenic acids as well as antioxidative potentials of several unreported sweet potato varieties.

Authors and Affiliations

Ji Su Park, Ja Won Woo, Gyu-Hwan Choi, Dong-Seong Choi, Mun Yhung Jung

Keywords

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  • EP ID EP222163
  • DOI 10.17756/jfcn.2015-001
  • Views 143
  • Downloads 0

How To Cite

Ji Su Park, Ja Won Woo, Gyu-Hwan Choi, Dong-Seong Choi, Mun Yhung Jung (2015). Chlorogenic Acid Profiles and Antioxidant Potentials of 17 Sweet Potato Varieties Cultivated in Korea: Impact of Extraction Condition and Classification by Hierarchical Clustering Analysis. Journal of Food Chemistry and Nanotechnology, 1(1), 3-12. https://europub.co.uk/articles/-A-222163