Analytical MethodsUsing UV–Vis spectroscopy for simultaneous geographical and varietal classification of tea infusions simulating a home-made tea cup
Graphical abstract
Introduction
Since ancient times, tea has been used by the Asiatic cultures not only as an herbal medicine, but also for its characteristic flavour and aroma. The great present-day popularity of teas as beverages is mainly due to the presence of polyphenols and caffeine, which respectively determine up to 30% and up to 4% of the dry weight (Kumar, Murugesan, Kottur, & Gyamfl, 2012). Polyphenols have been shown to present various benefits for human health, nutrition, and physiology (Khan and Mukhtar, 2007, Sharma, 2014), while caffeine is principally attractive due to its stimulatory effects, which are frequently used by the pharmacological industry (Spiller, 1997, Wang et al., 2008). The additional health benefits of teas are also frequently described in the literature (Sharangi, 2009, Chow and Hakim, 2011, Pinto, 2013).
Tea is the second most consumed non-alcoholic beverage in the world (after water), and is prepared by brewing the dried leaves of Camellia sinensis in water. The types of tea (white, yellow, green, oolong, black, and Pu-ehr) basically differ with regards to the extent of fermentation. Green (unfermented) and black (fully fermented) teas are the two most popular categories, together accounting for around 98% of both world production and consumption (Diniz et al., 2012, Pinto, 2013). The plant is highly cultivated in Asia, Africa, and South America. In South America, Argentina and Brazil are the main tea producers, respectively harvesting 90.7 and 7.7 thousand tons in 2012 (Food & intergovernmental group on tea. Current situation, 2012). In the 1920’s Japanese immigrants to Brazil initiated cultivation using tea seeds from Sri Lanka and India. Despite a relatively small tea industry in Brazil, the tea producers here have achieved some increase in market share due to their efforts to improve the quality of Brazilian teas. In Argentina, tea was first introduced in 1920 (with Russian seeds) and it is currently the world 9th largest tea producer.
In worldwide tea trading, consumer interest and a country’s reputation (clearly indicating geographic origin), has increasingly become synonymous with higher than average prices (Ye, 2012). As an example the famous “Lion” logo of “Ceylon” or “Sri Lankan” teas (administered by the Sri Lankan Tea Board) is still regarded worldwide as a sign of quality and taste.
Various analytical methods to verify the geographic origins of teas have been proposed in the literature with the purpose of providing some sort of security to both tea traders and consumers, and to prevent fraudulent labelling (Ye, 2012). However, most of these techniques require laborious sample preparation, and induce significant operational expenditures. We therefore propose a tea classification strategy that provides precise and reliable results, and can be implemented in a routine laboratory. Ultraviolet–Visible (UV–Vis) spectroscopy is one of the most common techniques used in routine analysis, and has already been used to differentiate between black, green, and Pu-erh tea varieties (Pallacios-Morillo, Alcázar, de Pablos, and Jurado (2013)). However in this method, methanol was used as the extractor solvent creating very broad spectra with highly correlated variables. This requires more sophisticated non-linear classifiers such as Artificial Neural Networks (ANNs), and Support Vector Machines (SVMs). Methanol also presents toxicity to humans as well as to the environment (Clary, 2013). Geographical classification of teas using UV–Vis spectroscopy has not been reported in the literature. Simultaneous classification of both geographic origin and variety for teas has been proposed using digital images (Diniz et al., 2012), and near-infrared spectroscopy (NIRS) (Diniz, Gomes, Pistonesi, Band, & Araújo, 2014). However, these methodologies were carried out directly on the tea as contained in commercialized bags, whereas the infusion represents the final product as ingested by the consumer. Tea quality moreover is traditionally evaluated by skilful tasters based on the infusion’s appearance, taste, and aroma, which is evidently partial and cannot assess a tea’s geographic origin (Diniz et al., 2014).
In this work we propose a method to verify the differentiating characteristics of simple tea infusions prepared in boiling water alone (simulating a home-made tea cup). This form represents the final product as ingested by the consumer. For this purpose, UV–Vis spectroscopy, and variable selection using the Successive Projections Algorithm associated with Linear Discriminant Analysis (SPA-LDA) (Soares, Gomes, Galvão Filho, Araújo, & Galvão, 2013) was used for simultaneous classification of teas according to their variety (black or green tea), and their geographic origin (Argentina, Brazil, or Sri Lanka). For comparison, other supervised pattern recognition techniques such as K-nearest neighbours (KNN), Classification, Regression Tree (CART), Soft Independent Modelling by Class Analogy (SIMCA), Partial Least Squares Discriminant Analysis (PLS-DA), and Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA) were used. It is worth noting that SPA-LDA has been successfully applied to classify other foods such as edible vegetable oils using square wave voltammetry (Gambarra-Neto et al., 2009), coffees using UV–Vis spectroscopy (Souto et al., 2010), beers using NIR spectroscopy (Ghasemi-Varnamkhasti et al., 2012), and honeys using digital images (Domínguez, Diniz, Di Nezio, Araújo, & Centurión, 2014).
Section snippets
Samples
One hundred tea samples were purchased from local supermarkets in the cities of João Pessoa (Brazil), and Bahía Blanca (Argentina): 20 Brazilian black teas, 20 Brazilian green teas, 20 Argentinean black teas, 20 Sri Lankan black teas, and 20 Argentinean green teas. A sample quartering step was performed as described by Diniz et al. (2014). The contents of the 100 tea bags from each batch were quartered, and then reduced to a final sample containing 25 g, they were subsequently stored in sealed
Exploratory analysis of the data
Fig. 1a shows the absorbance spectra of the simple tea infusions in the range of 190–800 nm. The spectra present a profile similar to that of data published by Pallacios-Morillo et al. (2013), although their spectra were much broader and highly correlated. This is because the solvent (in this case, methanol) affects the position of the spectral band, and the maximum absorbance, i.e. the values of λmax, molar absorptivity ε, and the shape of the spectrum. As can be seen in Fig. 1a, the most
Conclusions
A simultaneous classification of both geographic origin and variety of teas using UV–Vis spectroscopy and pattern recognition techniques was proposed. In order to verify their differentiating characteristics, simple tea infusions prepared in boiling water alone (simulating a home-made tea cup) were analysed, this instead of extraction with methanol, as done by Pallacios-Morillo et al. (2013). Apart from its toxicity, the use of methanol as a solvent extractor makes the spectra much broader with
Acknowledgements
The authors gratefully acknowledge the Universidad Nacional del Sur, CIC (Comisión de Investigaciones Científicas de la Provincia de Buenos Aires), and CONICET (Consejo Nacional de Investigaciones Científicas y Técnicas) for their financial support. The authors also gratefully acknowledge the Capes and CNPq Brazilian scholarships and research fellowships.
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