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Predictability of price of tea from sensory assessments and biochemical information using data‐mining techniques
Author(s) -
Paul Sanjoy K
Publication year - 2008
Publication title -
journal of the science of food and agriculture
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.782
H-Index - 142
eISSN - 1097-0010
pISSN - 0022-5142
DOI - 10.1002/jsfa.3223
Subject(s) - predictability , valuation (finance) , quality (philosophy) , econometrics , sensory system , computer science , statistics , business , mathematics , psychology , cognitive psychology , philosophy , finance , epistemology
BACKGROUND: The valuation of tea depends on the sensory assessments made by the Brokers and Buyers (Tea Tasters) to a large extent, though the market conditions and the requirements of a particular Buyer play an important role in determining the basic prices of teas. Again, there are several biochemical quality parameters in tea on which the quality of a particular tea depends. It is not straightforward to establish the reflection of biochemical quality characteristics in tea on the Taster's sensory assessments and price because of the complex dynamics within chemical properties and the inherent subjectivity of quality evaluation through the Taster's scores. It is, however, important to judge the market valuation of teas from quality assessments and biochemical properties. This paper describes the advantages of using statistical data‐mining techniques to explore the association of biochemical quality parameters in teas with the Taster's sensory assessments, and the application of a nonparametric statistical technique, multivariate adaptive regression splines (MARSplines), to establish the predictability of the realised prices of teas from sensory assessments. RESULTS: The price of tea is significantly associated with various quality attributes and some of the biochemical parameters. The MARSplines technique successfully demonstrated the predictability of price through Tasters' sensory assessments and also raised the issue of inherent subjectivity of the Tasters' assessments. CONCLUSION: It is important to explore appropriate statistical techniques to assess the subjectivity in Tasters' assessments, and a better‐designed study needs to be conducted to understand the complex biochemical reflections on the price of tea. Copyright © 2008 Society of Chemical Industry