Abstract
Electronic tongue has already been used to estimate the quality of tea in terms of tea-tasters scores that are subjective and limited by human sensory organs. It is known that, chemical constituents play significant role to determine the quality of tea. Thus the perception of quality as understood from an electronic tongue can be improved if it can be trained to estimate the amount of major chemicals responsible for quality of tea. An alternate method of rapid quality evaluation of tea is proposed using a voltammetric electronic tongue to determine two major taste descriptors in black tea. The correlation model is developed between the electronic tongue signatures and theaflavins/thearubigins contents of tea using multi-layer perceptrons. The perception of taste is further improved using scaled conjugate gradient as a weight optimization algorithm.
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Ghosh, A., Tudu, B., Tamuly, P., Bhattacharyya, N., Bandyopadhyay, R. (2012). Improvement of Quality Perception for Black CTC Tea by Means of an Electronic Tongue. In: Kundu, M.K., Mitra, S., Mazumdar, D., Pal, S.K. (eds) Perception and Machine Intelligence. PerMIn 2012. Lecture Notes in Computer Science, vol 7143. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27387-2_24
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DOI: https://doi.org/10.1007/978-3-642-27387-2_24
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