Characterization of Fermentative Behaviors of Lactic Acid Bacteria in Grape Wines through H-1 NMR- and GC-Based Metabolic Profiling
- Authors
- Lee, Jang-Eun; Hong, Young-Shick; Lee, Cherl-Ho
- Issue Date
- 10-6월-2009
- Publisher
- AMER CHEMICAL SOC
- Keywords
- Wine; NMR; GC; metabolomics; volatile compound; metabolites
- Citation
- JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY, v.57, no.11, pp.4810 - 4817
- Indexed
- SCIE
SCOPUS
- Journal Title
- JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
- Volume
- 57
- Number
- 11
- Start Page
- 4810
- End Page
- 4817
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/119830
- DOI
- 10.1021/jf900502a
- ISSN
- 0021-8561
- Abstract
- The effects of five commercial Oenococcus oeni strains (MCW, Enoferm alpha, Wyeast, Vinibacti111, and Vinibacti222) on fermentative behaviors, and variations of metabolites in Meoru (Vitis coigneties) wines during malolactic fermentation (MLF) were investigated by metabolomic analysis of H-1 NMR and GC data sets. In the development of MLF with various O. oeni strains, the fastest conversions of malic acid to lactic acid occurred in wines fermented with Enoferm a and Vinibacti111 strains. Seventeen primary metabolites and 65 secondary metabolites of volatile compounds in the wines were identified by H-1 NMR spectroscopy and GC-MS, respectively. In pattern recognition models of principal component analysis (PCA) and orthogonal projection to latent structures cliscriminant analysis (OPLS-DA), significant differentiations between wines with O. oeni strains were identified by the secondary metabolites rather than by the primary metabolites, showing the effects of O. oeni strains only on the secondary metabolites. Twelve volatile compounds, 2-phenylethanol, isoamyl alcohol, 2-butanol, ethyl octanoate, ethyl hexanoate, hexadecanoic acid, diethyl succinate, butyl butyrate, octanoic acid, 9-hexadecanoic acid, isobutyric acid, and 2-ethyl-1-hexanol, contributed to the differentiation of wines according to O. oeni strain, including spontaneous MLF This study demonstrates that O. oeni strains affect the secondary metabolites, which are easily identified through multivariate statistical analysis of GC-MS data set.
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Collections - College of Life Sciences and Biotechnology > Division of Food Bioscience and Technology > 1. Journal Articles
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