Differentiation of eight tea (Camellia sinensis) cultivars in China by elemental fingerprint of their leaves

BACKGROUND: Tea is an infusion made from dried leaves of tea (Camellia sinensis) and can be a good dietary source of essential trace metals for humans. Therefore, it is necessary to consider variations in element content of tea leaves among tea cultivars. Thus, elemental fingerprint techniques, base...

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Bibliographic Details
Published in:Journal of the science of food and agriculture 2009-11, Vol.89 (14), p.2350-2355
Main Authors: Chen, Yingxu, Yu, Mingge, Xu, Jie, Chen, Xincai, Shi, Jiyan
Format: Article
Language:English
Subjects:
accuracy
Biological and medical sciences
Camellia sinensis
chemical concentration
Chemical elements
Classification
Coffee, tea and other stimulative beverage industries
cultivar
cultivar identification
Cultivars
DNA fingerprinting
elemental fingerprint
elements
food analysis
food composition
Food industries
Food science
Fundamental and applied biological sciences. Psychology
ICP-AES
leaves
nutrient content
pattern recognition
product evaluation
Spectrum analysis
Tea
tea (beverage)
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Summary:BACKGROUND: Tea is an infusion made from dried leaves of tea (Camellia sinensis) and can be a good dietary source of essential trace metals for humans. Therefore, it is necessary to consider variations in element content of tea leaves among tea cultivars. Thus, elemental fingerprint techniques, based on elemental contents (Al, B, Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mn, Na, P, Pb, and Zn) determined by inductively coupled plasma atomic emission spectrometry (ICP-AES) and multivariate statistical analysis, have been used to differentiate eight tea cultivars.RESULTS: The ranges of element concentrations in leaves of the eight cultivars were in good agreement with those obtained in previous studies and the level of most elements in tea leaves was significantly different among cultivars. The classifications of eight tea cultivars were 100% accurate in total by principal component analysis (PCA), hierarchical cluster analysis (HCA), linear discriminant analysis (LDA), and back-propagation neural network (BPNN) analysis.CONCLUSION: Each cultivar presented a distinctive element fingerprint and the elements in tea leaves can be significant predictors in differentiating tea cultivars.
ISSN:0022-5142
1097-0010
DOI:10.1002/jsfa.3716