Differentiation of black tea infusions according to origin, processing and botanical varieties using multivariate statistical analysis of LC-MS data. (July 2018)

• Record Type: Journal Article
• Authors: Shevchuk, Anastasiia; Jayasinghe, Lalith; Kuhnert, Nikolai
• Is Part Of: Food research international. Volume 109(2018)
• Page Start: 387
• Page End: 402
• Publication Date: 2018-07
• Subjects: Multivariate analysis -- Black tea -- Polyphenols -- Thearubigins -- Discrimination -- Origin -- Fermentation -- HPLC-MS; Food -- Analysis -- Periodicals; Food industry and trade -- Periodicals; Food industry and trade -- Canada -- Periodicals; Food Technology -- Periodicals; Food -- Periodicals; Food-Processing Industry -- Periodicals; Aliments -- Industrie et commerce -- Périodiques; Aliments -- Industrie et commerce -- Canada -- Périodiques; Aliments -- Recherche -- Périodiques; Food industry and trade; Canada; Periodicals; Electronic journals; 664.005
• DOI: 10.1016/j.foodres.2018.03.059
• Languages: English
• ISSNs: 0963-9969

Abstract

Abstract: A data set of sixty samples of diverse black tea were collected and analysed using high-performance liquid chromatography-mass spectrometry (HPLC-MS) methods. Chemical variations of black tea infusions depending on origin, botanical variety, and processing were investigated employing various multivariate statistical techniques including principal component analysis (PCA), hierarchical cluster analysis (HCA), partial least squares discriminant analysis (PLS-DA) and analysis of variance (ANOVA). In particular, PLS-DA allowed identification of a variety of marker compounds responsible for differences among black teas of different origin, plant variety and processing methods used. Among most variable compounds are catechins, derivatives of quercetin, apigenin, quinic acid, and kaempferol. Rutin, epigallocatechin gallate (EGCG), quinic acid and theaflavin (TF) were contributing to most variances. Products of black tea fermentation (theaflavin, theasinensin, and theacitrin derivatives) contributed to PLS-DA associated to the processing of black tea. Graphical abstract: Highlights: Multivariant statistical analysis of LC-MS data allows discrimination of black teas. Products of black tea fermentation contribute significantly to the variation. Origin, botanical variety and processing affect black tea composition. More than 50 biomarkers responsible for variations were identified. The high chemical complexity of black tea requires dedicated statistical methods.