Abstract
Guava leaves were classified and the free radical scavenging activity (FRSA) evaluated according to different harvest times by using the 1H-NMR-based metabolomic technique. A principal component analysis (PCA) of 1H-NMR data from the guava leaves provided clear clusters according to the harvesting time. A partial least squares (PLS) analysis indicated a correlation between the metabolic profile and FRSA. FRSA levels of the guava leaves harvested during May and August were high, and those leaves contained higher amounts of 3-hydroxybutyric acid, acetic acid, glutamic acid, asparagine, citric acid, malonic acid, trans-aconitic acid, ascorbic acid, maleic acid, cis-aconitic acid, epicatechin, protocatechuic acid, and xanthine than the leaves harvested during October and December. Epicatechin and protocatechuic acid among those compounds seem to have enhanced FRSA of the guava leaf samples harvested in May and August. A PLS regression model was established to predict guava leaf FRSA at different harvesting times by using a 1H-NMR data set. The predictability of the PLS model was then tested by internal and external validation. The results of this study indicate that 1H-NMR-based metabolomic data could usefully characterize guava leaves according to their time of harvesting.
Original language | English |
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Pages (from-to) | 1090-1097 |
Number of pages | 8 |
Journal | Bioscience, Biotechnology and Biochemistry |
Volume | 75 |
Issue number | 6 |
DOIs | |
State | Published - 2011 |
Bibliographical note
Funding Information:This work was supported by grants from the National Research Foundation of Korea (no. R01-2007-000-20492-0), Priority Research Centers Program (2010-0029630), and Basic Science Research Program (2010-0558) funded by the Korean government (MEST).
Keywords
- Discrimination
- Guava (Psidium guajava L.)
- H-NMR
- Metabolomic data