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László Sipos, Zoltán Kovács, Dániel Szöllősi, Zoltán Kókai, István Dalmadi and András Fekete Comparison of novel sensory panel performance evaluation techniques with e-nose analysis integration Journal of Chemometrics 25

Version of Record online: 30 MAR 2011 | DOI: 10.1002/cem.1391

A complex approach was used to evaluate the performance of a sensory panel with two novel techniques: GCAP (Gravity Center Area/Perimeter) and CRRN (Compare Ranks with Random Numbers). Profile analysis was performed on Sri Lanka black tea batches from different plantations; for the prediction of sensory data from electronic nose results partial least square regression and support vector machine regression were used. Prediction by support vector machine gave close correlation between the results of electronic nose measurement and odor attributes.

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