TY - JOUR
T1 - Characterization of three different classes of non-fermented teas using untargeted metabolomics
AU - Zhang, Qunfeng
AU - Wu, Si
AU - Li, Yan
AU - Liu, Meiya
AU - Ni, Kang
AU - Yi, Xiaoyun
AU - Shi, Yuanzhi
AU - Ma, Lifeng
AU - Willmitzer, Lothar
AU - Ruan, Jianyun
N1 - Publisher Copyright:
© 2018
PY - 2019/7/1
Y1 - 2019/7/1
N2 - Non-fermented teas, which are widely consumed in China, Japan, Korea, and elsewhere, have refreshing flavors and valuable health benefits. Various types of non-fermented teas look and taste similar and have no obvious differences in appearance, making their classification challenging. To date, there are very few reports about characterization and discrimination of different types of non-fermented teas. To characterize non-fermented teas and build a standard model for their classification based on their chemical composition, we employed multi-platform-based metabolomics to analyze primary and secondary metabolites in three main categories of non-fermented teas (green, yellow, and white), using 96 samples collected from China. Five hundred and ninety unique tea metabolites were identified and quantified in these three types of teas. Moreover, a partial least squares discriminant analysis (PLS-DA) model was established based on metabolomics data, in order to classify non-fermented teas into these three classes. Furthermore, our results speculate that the health benefits (e.g., antioxidant content) of these three types of non-fermented tea differ primarily because of variation in their metabolic components (e.g., ascorbate, vitexin).
AB - Non-fermented teas, which are widely consumed in China, Japan, Korea, and elsewhere, have refreshing flavors and valuable health benefits. Various types of non-fermented teas look and taste similar and have no obvious differences in appearance, making their classification challenging. To date, there are very few reports about characterization and discrimination of different types of non-fermented teas. To characterize non-fermented teas and build a standard model for their classification based on their chemical composition, we employed multi-platform-based metabolomics to analyze primary and secondary metabolites in three main categories of non-fermented teas (green, yellow, and white), using 96 samples collected from China. Five hundred and ninety unique tea metabolites were identified and quantified in these three types of teas. Moreover, a partial least squares discriminant analysis (PLS-DA) model was established based on metabolomics data, in order to classify non-fermented teas into these three classes. Furthermore, our results speculate that the health benefits (e.g., antioxidant content) of these three types of non-fermented tea differ primarily because of variation in their metabolic components (e.g., ascorbate, vitexin).
KW - Characterization
KW - Classification
KW - Metabolomics
KW - Non-fermented tea
UR - http://www.scopus.com/inward/record.url?scp=85059566924&partnerID=8YFLogxK
U2 - 10.1016/j.foodres.2018.12.042
DO - 10.1016/j.foodres.2018.12.042
M3 - Article
C2 - 31108798
AN - SCOPUS:85059566924
SN - 0963-9969
VL - 121
SP - 697
EP - 704
JO - Food Research International
JF - Food Research International
ER -