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Research Articles

Classification of geographical origin of Sri Lankan black tea using discriminant function analysis

Authors:

T. U. S. Peiris ,

Wayamba University of Sri Lanka, Makandura, Gonawila, LK
About T. U. S.
Biostatistics Unit, Faculty of Livestock Fisheries and Nutrition
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C. K. Walgampaya,

University of Peradeniya, LK
About C. K.
Department of Engineering Mathematics, Faculty of Engineering
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R. O. Thattil,

University of Peradeniya, LK
About R. O.
Department of Crop Science, Faculty of Agriculture
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I. S. B. Abeysinghe

Tea Research Institute of Sri Lanka, Talawakelle, LK
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Abstract

Designated food products are considered the best on the basis of their authenticity. These products have a much higher market price and therefore, subjected to frauds. Developing a scientific mechanism to ensure authenticity is a timely requirement. The objective of this study was to establish a base to classify geographical origins of Sri Lankan black tea using chemical compounds of tea coupled with discriminant function analysis. Thirteen different geographical origins which have a distinct character unique to the region were considered and eleven chemical parameters were analysed in the study. The highest rate of correctly classified cases was observed in Nuwara Eliya tea followed by Mid Country, Uva Medium, Matara/Akuressa and Maskeliya. Total colour was sufficient to discriminate Nuwaraeliya tea. Thearubugins was the most important chemical compound to discriminate between high grown, low grown and mid grown tea. This study gives an insight on the potential to classify Sri Lankan black tea using the profile of chemical constituents and to ensure the authenticity of Ceylon speciality tea in order to upkeep the market share.
How to Cite: Peiris, T.U.S., Walgampaya, C.K., Thattil, R.O. and Abeysinghe, I.S.B., 2017. Classification of geographical origin of Sri Lankan black tea using discriminant function analysis. Tropical Agricultural Research, 29(1), pp.12–24. DOI: http://doi.org/10.4038/tar.v29i1.8293
Published on 31 Dec 2017.
Peer Reviewed

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