Metabolic Profiling and Predicting the Free Radical Scavenging Activity of Guava (<i>Psidium guajava</i>L.) Leaves According to Harvest Time by<sup>1</sup>H-Nuclear Magnetic Resonance Spectroscopy
-
- KIM So-Hyun
- College of Pharmacy, Chung-Ang University
-
- CHO Somi K.
- Faculty of Biotechnology, College of Applied Life Sciences, Cheju National University
-
- HYUN Sun-Hee
- College of Pharmacy, Chung-Ang University
-
- PARK Hae-Eun
- College of Pharmacy, Chung-Ang University
-
- KIM Young-Suk
- Department of Food Science and Engineering, Ewha Woman’s University
-
- CHOI Hyung-Kyoon
- College of Pharmacy, Chung-Ang University
書誌事項
- タイトル別名
-
- Metabolic Profiling and Predicting the Free Radical Scavenging Activity of Guava (Psidium guajava L.) Leaves According to Harvest Time by 1H-Nuclear Magnetic Resonance Spectroscopy
この論文をさがす
説明
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.
収録刊行物
-
- Bioscience, Biotechnology, and Biochemistry
-
Bioscience, Biotechnology, and Biochemistry 75 (6), 1090-1097, 2011
公益社団法人 日本農芸化学会
- Tweet
詳細情報 詳細情報について
-
- CRID
- 1390001206478218880
-
- NII論文ID
- 10029327988
-
- NII書誌ID
- AA10824164
-
- ISSN
- 13476947
- 09168451
-
- NDL書誌ID
- 11131937
-
- 本文言語コード
- en
-
- データソース種別
-
- JaLC
- NDLサーチ
- Crossref
- CiNii Articles
-
- 抄録ライセンスフラグ
- 使用不可