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CHEMOMETRICS

Classification of Tieguanyin Tea with an Electronic Tongue and Pattern Recognition

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Pages 2361-2369 | Received 22 Nov 2013, Accepted 16 Mar 2014, Published online: 08 Aug 2014

REFERENCES

  • Aditi , J. , M. Chanchal , K. Shrey , N. Darshika , and R. Vibha . 2013 . Tea and human health: The dark shadows . Toxicol. Lett. 220 : 82 – 87 .
  • Arrieta , Á. A. , M. L. Rodríguez-Méndez , J. A. De Saja , C. A. Blanco , and D. Nimubona . 2010 . Prediction of bitterness and alcoholic strength in beer using an electronic tongue . Food Chem. 123 : 642 – 646 .
  • Cao , H. 2013 . Polysaccharides from Chinese tea: Recent advance on bioactivity and function . Int. J. Biol. Macromol. 62 : 76 – 79 .
  • Chen , Q. , J. Zhao , and S. Vittayapadung . 2008 . Identification of the green tea grade level using electronic tongue and pattern recognition . Food Res. Int. 41 : 500 – 504 .
  • Dias , L. A. , A. M. Peres , A. C. Veloso , F. Reis , M. Vilas-Boas , and A. A. Machado . 2009 . An electronic tongue taste evaluation: Identification of goat milk adulteration with bovine milk . Sensor Actuat. B. 136 : 209 – 217 .
  • Erbek , F. S. , C. Özkan , and M. Taberner . 2004 . Comparison of maximum likelihood classification method with supervised artificial neural network algorithms for land use activities . Int. J. Remote Sens. 25 : 1733 – 1748 .
  • Escuder-Gilabert , L. , and M. Peris . 2010 . Review: highlights in recent applications of electronic tongues in food analysis . Anal. Chim. Acta. 665 : 15 – 25 .
  • Gutiérrez , M. , C. Domingo , J. Vila-Planas , A. Ipatov , F. Capdevila , S. Demming , S. Büttgenbach , A. Llobera , and C. Jiménez-Jorquera . 2011 . Hybrid electronic tongue for the characterization and quantification of grape variety in red wines . Sensor Actuat. B. 156 : 695 – 702 .
  • Hayashi , N. , R. Chen , H. Ikezaki , and T. Ujihara . 2008 . Evaluation of the umami taste intensity of green tea by a taste sensor . J. Agr. Food Chem. 56 : 7384 – 7387 .
  • He , W. , X. Hu , L. Zhao , X. Liao , Y. Zhang , M. Zhang , and J. Wu . 2009 . Evaluation of Chinese tea by the electronic tongue: correlation with sensory properties and classification according to geographical origin and grade level . Food Res. Int. 42 : 1462 – 1467 .
  • Hidayat , W. , A. Y. M. Shakaff , M. N. Ahmad , and A. H. Adom . 2010 . Classification of agarwood oil using an electronic nose . Sensors. 10 : 4675 – 4685 .
  • Ivarsson , P. , S. Holmin , N.-E. Höjer , C. Krantz-Rülcker , and F. Winquist . 2001 . Discrimination of tea by means of a voltammetric electronic tongue and different applied waveforms . Sensor Actuat. B. 76 : 449 – 454 .
  • Kovács , Z. , I. Dalmadi , L. Lukács , L. Sipos , K. Szántai‐Kőhegyi , Z. Kókai , and A. Fekete . 2010 . Geographical origin identification of pure Sri Lanka tea infusions with electronic nose, electronic tongue and sensory profile analysis . J. Chemometr. 24 : 121 – 130 .
  • Levenberg , K. 1944 . A method for the solution of certain problems in least squares . Q. Appl. Math. 2 : 164 – 168 .
  • Marquardt , D. W. 1963 . An algorithm for least-squares estimation of nonlinear parameters . J. Soc. Indust. Appl. Math. 11 : 431 – 441 .
  • Matsushita , K. , M. van der Velde , B. C. Astor , M. Woodward , A. S. Levey , P. E. de Jong , J. Coresh , and R. T. Gansevoort . 2010. Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: A collaborative meta-analysis. Lancet. 375: 2073–2081.
  • Moreno , L. , A. Merlos , N. Abramova , C. Jimenez , and A. Bratov . 2006 . Multi-sensor array used as an “electronic tongue” for mineral water analysis . Sensor Actuat. B. 116 : 130 – 134 .
  • Nakai , M. , Y. Fukui , S. Asami , Y. Toyoda-Ono , T. Iwashita , H. Shibata , T. Mitsunaga , F. Hashimoto , and Y. Kiso . 2005 . Inhibitory effects of oolong tea polyphenols on pancreatic lipase in vitro . J. Agr. Food Chem. 53 : 4593 – 4598 .
  • Oliveri , P. , V. Di Egidio , T. Woodcock , and G. Downey . 2011 . Application of class-modelling techniques to near infrared data for food authentication purposes . Food Chem. 125 : 1450 – 1456 .
  • Palit , M. , B. Tudu , P. K. Dutta , A. Dutta , A. Jana , J. K. Roy , N. Bhattacharyya , R. Bandyopadhyay , and A. Chatterjee . 2010 . Classification of black tea taste and correlation with tea taster's mark using voltammetric electronic tongue . IEEE T. Instrum. Meas. 59 : 2230 – 2239 .
  • Rudnitskaya , A. , I. Delgadillo , A. Legin , S. M. Rocha , A.-M. Costa , and T. Simões . 2007 . Prediction of the port wine age using an electronic tongue . Chemometr. Intell. Lab. 88 : 125 – 131 .
  • Rudnitskaya , A. , S. Rocha , A. Legin , V. Pereira , and J. C. Marques . 2010 . Evaluation of the feasibility of the electronic tongue as a rapid analytical tool for wine age prediction and quantification of the organic acids and phenolic compounds. The case-study of Madeira wine . Anal. Chim. Acta. 662 : 82 – 89 .
  • Sexton , R. S. , and J. N. Gupta . 2000 . Comparative evaluation of genetic algorithm and backpropagation for training neural networks . Inform. Sciences. 129 : 45 – 59 .
  • Sharma , P. , and M. Kaur . 2013 . Classification in pattern recognition: A review . Int. J. Adv. Res. Comput. Sci. Softw. Eng. 3 : 298 – 306 .
  • Sipos , L. , Z. Kovács , V. Sági-Kiss , T. Csiki , Z. Kókai , A. Fekete , and K. Héberger . 2012 . Discrimination of mineral waters by electronic tongue, sensory evaluation and chemical analysis . Food Chem. 136 : 2947 – 2953 .
  • Tan , C. , and Y. Ding . 2010 . The promotion of tea in South China: Re-inventing tradition in an old industry . Food Foodw. 18 : 121 – 144 .
  • Teye , E. , X. Huang , F. Han , and F. Botchway . 2014 . Discrimination of cocoa beans according to geographical origin by electronic tongue and multivariate algorithms . Food Anal. Method. 2 : 360 – 365 .
  • Wang , Y. , S. Shao , P. Xu , H. Chen , S.-Y. Lin-Shiau , Y.-T. Deng , and J.-K. Lin . 2012 . Fermentation process enhanced production and bioactivities of oolong tea polysaccharides . Food Res. Int. 46 : 158 – 166 .

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