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Volumn 25, Issue 7, 2011, Pages 382-388

Predictive power of LDA to discriminate abnormal wine fermentations

Author keywords

LDA; Nonlinear curve fitting; Prediction; Stepwise; Wine fermentation

Indexed keywords

CURVE FITTING; DISCRIMINANT ANALYSIS; WINE;

EID: 79960375489     PISSN: 08869383     EISSN: 1099128X     Source Type: Journal    
DOI: 10.1002/cem.1362     Document Type: Article
Times cited : (4)

References (34)
  • 1
    • 60849111375 scopus 로고    scopus 로고
    • Simulation and optimization software for alcoholic fermentation in winemaking conditions
    • Goelzer A, Chamomordic B, Colombié S, Fromion V, Sablayrolles JM. Simulation and optimization software for alcoholic fermentation in winemaking conditions. Food Control 2009; 20: 635-642.
    • (2009) Food Control , vol.20 , pp. 635-642
    • Goelzer, A.1    Chamomordic, B.2    Colombié, S.3    Fromion, V.4    Sablayrolles, J.M.5
  • 2
    • 0031883127 scopus 로고    scopus 로고
    • Biochemical aspects of stuck and sluggish fermentation in grape must
    • Alexandre H, Charpentier C. Biochemical aspects of stuck and sluggish fermentation in grape must. J. Ind. Microbiol. Biotechnol. 1998; 20: 20-27.
    • (1998) J. Ind. Microbiol. Biotechnol. , vol.20 , pp. 20-27
    • Alexandre, H.1    Charpentier, C.2
  • 3
    • 0035107918 scopus 로고    scopus 로고
    • Stuck and slow fermentations in enology: statical study of causes and effectiveness of combined additions of oxygen and diammonium phosphate
    • Blateyron L, Sablayrolles JM. Stuck and slow fermentations in enology: statical study of causes and effectiveness of combined additions of oxygen and diammonium phosphate. J. Biosci. Bioeng. 2001; 91(2): 184-189.
    • (2001) J. Biosci. Bioeng. , vol.91 , Issue.2 , pp. 184-189
    • Blateyron, L.1    Sablayrolles, J.M.2
  • 4
    • 85159502667 scopus 로고    scopus 로고
    • Home Winemaking website
    • Home Winemaking website:.
  • 6
    • 33645344085 scopus 로고    scopus 로고
    • Industrial experiences with multivariate statistical analysis of batch process data
    • Chiang L, Leardi R, Pell R, Seasholtz M. Industrial experiences with multivariate statistical analysis of batch process data. Chemom. Intell. Lab. Syst. 2006; 81: 109-119.
    • (2006) Chemom. Intell. Lab. Syst. , vol.81 , pp. 109-119
    • Chiang, L.1    Leardi, R.2    Pell, R.3    Seasholtz, M.4
  • 8
    • 34250815100 scopus 로고    scopus 로고
    • Study of the application of multiway multivariate techniques to model data from an industrial fermentation process
    • Ferreira A, Lopes J, Menezes J. Study of the application of multiway multivariate techniques to model data from an industrial fermentation process. Anal. Chim. Acta 2007; 595: 120-127.
    • (2007) Anal. Chim. Acta , vol.595 , pp. 120-127
    • Ferreira, A.1    Lopes, J.2    Menezes, J.3
  • 9
    • 0242390969 scopus 로고    scopus 로고
    • On-line batch process monitoring using a consecutively updated multiway principal component analysis model
    • Lee J-M, Yoo C, Lee I-B. On-line batch process monitoring using a consecutively updated multiway principal component analysis model. Comput. Chem. Eng. 2003; 27: 1903-1912.
    • (2003) Comput. Chem. Eng. , vol.27 , pp. 1903-1912
    • Lee, J.-M.1    Yoo, C.2    Lee, I.-B.3
  • 10
    • 60249088159 scopus 로고    scopus 로고
    • Multivariate statistical real-time monitoring of an industrial fed-batch process for the production of specialty chemicals
    • Faggian A, Facco P, Doplicher F, Bezzo F, Barolo M. Multivariate statistical real-time monitoring of an industrial fed-batch process for the production of specialty chemicals. Chem. Eng. Res. Des. 2009; 87(3): 325-334.
    • (2009) Chem. Eng. Res. Des. , vol.87 , Issue.3 , pp. 325-334
    • Faggian, A.1    Facco, P.2    Doplicher, F.3    Bezzo, F.4    Barolo, M.5
  • 11
    • 0036401887 scopus 로고    scopus 로고
    • Classification of fermentation performance by multivariate analysis based on Mean Hypothesis Testing
    • Huang J, Nanami H, Kanda A, Shimizu H, Shioya S. Classification of fermentation performance by multivariate analysis based on Mean Hypothesis Testing. J. Biosci. Bioeng. 2002; 94(3): 251-257.
    • (2002) J. Biosci. Bioeng. , vol.94 , Issue.3 , pp. 251-257
    • Huang, J.1    Nanami, H.2    Kanda, A.3    Shimizu, H.4    Shioya, S.5
  • 12
    • 34347379313 scopus 로고    scopus 로고
    • Using data mining techniques to predict industrial wine problem fermentations
    • Urtubia A, Pérez-Correa J, Soto A, Pszczólkowski P. Using data mining techniques to predict industrial wine problem fermentations. Food Control 2007; 18: 1512-1517.
    • (2007) Food Control , vol.18 , pp. 1512-1517
    • Urtubia, A.1    Pérez-Correa, J.2    Soto, A.3    Pszczólkowski, P.4
  • 13
    • 79960370254 scopus 로고    scopus 로고
    • Application of MPCA and MPLS on industrial batch bioprocesses. Presented in 14th International Biotechnology Symposium, Rimini, Italy, 14-18 September 2010
    • Urtubia A, Emparan M, Almonacid S, Pinto M, Valdenegro M. Application of MPCA and MPLS on industrial batch bioprocesses. Presented in 14th International Biotechnology Symposium, Rimini, Italy, 14-18 September 2010. J. Biotechnol. 2010.
    • (2010) J. Biotechnol.
    • Urtubia, A.1    Emparan, M.2    Almonacid, S.3    Pinto, M.4    Valdenegro, M.5
  • 14
    • 85159508485 scopus 로고    scopus 로고
    • Multivariate statistic and pattern recognition to detect abnormal fermentations in wine process
    • Urtubia A, Emparan M, Román C, Hernández G, Roger JM. Multivariate statistic and pattern recognition to detect abnormal fermentations in wine process. J. Biotechnol. 2010.
    • (2010) J. Biotechnol.
    • Urtubia, A.1    Emparan, M.2    Román, C.3    Hernández, G.4    Roger, J.M.5
  • 15
    • 0037405964 scopus 로고    scopus 로고
    • Extensions of LDA by PCA mixture model and class-wise features
    • Kim H-C, Kim D, Ban SY. Extensions of LDA by PCA mixture model and class-wise features. Pattern Recognit. 2003; 36: 1095-1105.
    • (2003) Pattern Recognit. , vol.36 , pp. 1095-1105
    • Kim, H.-C.1    Kim, D.2    Ban, S.Y.3
  • 16
    • 0000764772 scopus 로고
    • The use of multiple measurements in taxinomic problems
    • Fisher R. The use of multiple measurements in taxinomic problems. Ann. Eugen. 1936; 7: 179-188.
    • (1936) Ann. Eugen. , vol.7 , pp. 179-188
    • Fisher, R.1
  • 17
    • 33845421286 scopus 로고    scopus 로고
    • Chemometrics and visible-near infrared spectroscopic monitoring of red wine fermentation in a pilot scale
    • Cozzolino D, Parker M, Dambergs R, Herderich M, Gishen M. Chemometrics and visible-near infrared spectroscopic monitoring of red wine fermentation in a pilot scale. Biotechnol. Bioeng. 2006; 95(6): 1101-1107.
    • (2006) Biotechnol. Bioeng. , vol.95 , Issue.6 , pp. 1101-1107
    • Cozzolino, D.1    Parker, M.2    Dambergs, R.3    Herderich, M.4    Gishen, M.5
  • 18
    • 35449001649 scopus 로고    scopus 로고
    • A comparison of generalized linear discriminant analysis algorithms
    • Park C, Park H. A comparison of generalized linear discriminant analysis algorithms. Pattern Recognit. 2008; 41: 1083-1097.
    • (2008) Pattern Recognit. , vol.41 , pp. 1083-1097
    • Park, C.1    Park, H.2
  • 19
    • 0029888347 scopus 로고    scopus 로고
    • Discriminant analysis of high-dimensional data: a comparison of principal component analysis and partial least squares data reduction methods
    • Kemsley E. Discriminant analysis of high-dimensional data: a comparison of principal component analysis and partial least squares data reduction methods. Chemom. Intell. Lab. Syst. 1996; 33(1): 47-61.
    • (1996) Chemom. Intell. Lab. Syst. , vol.33 , Issue.1 , pp. 47-61
    • Kemsley, E.1
  • 20
    • 0037350844 scopus 로고    scopus 로고
    • Partial least squares for discrimination
    • Barker M, Rayens W. Partial least squares for discrimination. J. Chemom. 2002; 17: 166-173.
    • (2002) J. Chemom. , vol.17 , pp. 166-173
    • Barker, M.1    Rayens, W.2
  • 21
    • 46149090559 scopus 로고    scopus 로고
    • Varietal discrimination of Australian wines by means of mid-infrared spectroscopy and multivariate analysis
    • Bevin C, Dambergs R, Fergusson A, Cozzolino D. Varietal discrimination of Australian wines by means of mid-infrared spectroscopy and multivariate analysis. Anal. Chim. Acta 2008; 621: 19-23.
    • (2008) Anal. Chim. Acta , vol.621 , pp. 19-23
    • Bevin, C.1    Dambergs, R.2    Fergusson, A.3    Cozzolino, D.4
  • 22
    • 34248570502 scopus 로고    scopus 로고
    • Feasibility study on the use of a head space mass spectrometry electronic nose (MS e-nose) to monitor red wine spoilage induced by Brettanomyces yeast
    • Cynkar W, Cozzolino D, Dambergs B, Janik L, Gishen M. Feasibility study on the use of a head space mass spectrometry electronic nose (MS e-nose) to monitor red wine spoilage induced by Brettanomyces yeast. Sens. Actuators B 2007; 124: 167-171.
    • (2007) Sens. Actuators B , vol.124 , pp. 167-171
    • Cynkar, W.1    Cozzolino, D.2    Dambergs, B.3    Janik, L.4    Gishen, M.5
  • 23
    • 1242271199 scopus 로고    scopus 로고
    • Comparative study of artificial neural network and multivariate methods to classify Spanish DO rose wines
    • Perez-Magariño S, Ortega-Heras M, Gonzalez-San JoseM, Boger Z. Comparative study of artificial neural network and multivariate methods to classify Spanish DO rose wines. Talanta 2004; 62: 983-990.
    • (2004) Talanta , vol.62 , pp. 983-990
    • Perez-Magariño, S.1    Ortega-Heras, M.2    Gonzalez-San, J.3    Boger, Z.4
  • 24
    • 74549124768 scopus 로고    scopus 로고
    • Classification of Tempranillo wines according to geographic origen: combination of mass spectrometry based electronic nose and chemometrics
    • Cynkar W, Dambergs R, Smith P, Cozzolino D. Classification of Tempranillo wines according to geographic origen: combination of mass spectrometry based electronic nose and chemometrics. Anal. Chim. Acta 2010; 660: 227-231.
    • (2010) Anal. Chim. Acta , vol.660 , pp. 227-231
    • Cynkar, W.1    Dambergs, R.2    Smith, P.3    Cozzolino, D.4
  • 25
    • 34548242224 scopus 로고    scopus 로고
    • Preliminary study on the application of visible-near infrared spectroscopy and chemometrics to classify Riesling wines from different countries
    • Liu L, Cozzolino D, Cynkar W, Dambergs R, Janik L, O'Neill B, Colby C, Gishen M. Preliminary study on the application of visible-near infrared spectroscopy and chemometrics to classify Riesling wines from different countries. Food Chem. 2008; 106: 781-786.
    • (2008) Food Chem. , vol.106 , pp. 781-786
    • Liu, L.1    Cozzolino, D.2    Cynkar, W.3    Dambergs, R.4    Janik, L.5    O'Neill, B.6    Colby, C.7    Gishen, M.8
  • 26
    • 0037059576 scopus 로고    scopus 로고
    • Classification of Nebbiolo-based wines from Piedmont (Italy) by means of solid-phase microextraction-gas chromatography-mass spectrometry of volatile compounds
    • Marengo E, Aceto M, Maurino V. Classification of Nebbiolo-based wines from Piedmont (Italy) by means of solid-phase microextraction-gas chromatography-mass spectrometry of volatile compounds. J. Chromatogr. A 2001; 943: 123-137.
    • (2001) J. Chromatogr. A , vol.943 , pp. 123-137
    • Marengo, E.1    Aceto, M.2    Maurino, V.3
  • 27
    • 31344455098 scopus 로고    scopus 로고
    • Multivariate analysis for the classification and differentiation of Madeira wines according to main grape varieties
    • Camara J, Alves M, Marques J. Multivariate analysis for the classification and differentiation of Madeira wines according to main grape varieties. Talanta 2006; 68: 1512-1521.
    • (2006) Talanta , vol.68 , pp. 1512-1521
    • Camara, J.1    Alves, M.2    Marques, J.3
  • 28
    • 76449087184 scopus 로고    scopus 로고
    • Feature extraction and selection of volatile compounds for analytical classification of Chinese red wines from different varieties
    • Zhang J, Li L, Gao N, Wang D, Gao Q, Jiang S. Feature extraction and selection of volatile compounds for analytical classification of Chinese red wines from different varieties. Anal. Chim. Acta 2010; 662: 137-142.
    • (2010) Anal. Chim. Acta , vol.662 , pp. 137-142
    • Zhang, J.1    Li, L.2    Gao, N.3    Wang, D.4    Gao, Q.5    Jiang, S.6
  • 29
    • 0037200929 scopus 로고    scopus 로고
    • Pattern analysis techniques to process fermentation curves: application to discrimination of enological alcoholic fermentations
    • Roger JM, Sablayrolles JM, Steyer JP, Bellon-Maurel V. Pattern analysis techniques to process fermentation curves: application to discrimination of enological alcoholic fermentations. Biotechnol. Bioeng. 2002; 79(7): 804-815.
    • (2002) Biotechnol. Bioeng. , vol.79 , Issue.7 , pp. 804-815
    • Roger, J.M.1    Sablayrolles, J.M.2    Steyer, J.P.3    Bellon-Maurel, V.4
  • 30
    • 84951601886 scopus 로고
    • Cross validatory estimation of the number of components in factor and principal components models
    • Wold S. Cross validatory estimation of the number of components in factor and principal components models. Technometrics 1978; 4(20): 397-405.
    • (1978) Technometrics , vol.4 , Issue.20 , pp. 397-405
    • Wold, S.1
  • 32
    • 4544228364 scopus 로고    scopus 로고
    • Monitoring large scale wine fermentations with infrared spectroscopy
    • Urtubia A, Pérez-Correa R, Meurens M, Agosin E. Monitoring large scale wine fermentations with infrared spectroscopy. Talanta 2004; 64: 778-784.
    • (2004) Talanta , vol.64 , pp. 778-784
    • Urtubia, A.1    Pérez-Correa, R.2    Meurens, M.3    Agosin, E.4
  • 33
    • 0023442604 scopus 로고
    • Fitting curves to data using nonlinear regression: a practical and nonmathematical review
    • Motulsky H, Ransnas L. Fitting curves to data using nonlinear regression: a practical and nonmathematical review. FASEB Journal 1987; 1(5): 365-374.
    • (1987) FASEB Journal , vol.1 , Issue.5 , pp. 365-374
    • Motulsky, H.1    Ransnas, L.2
  • 34
    • 0033837801 scopus 로고    scopus 로고
    • Diagnosis and rectification of stuck and sluggish fermentations
    • Bisson L, Butzke C. Diagnosis and rectification of stuck and sluggish fermentations. Am. J. Enol. Vitic. 2000; 51(2): 168-177.
    • (2000) Am. J. Enol. Vitic. , vol.51 , Issue.2 , pp. 168-177
    • Bisson, L.1    Butzke, C.2


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