A brief introduction to multivariate methods in grape and wine analysis

References

• Downey G. Authentication of food and food ingredients by near infrared spectroscopy. J Near Infrared Spec. 1996;4:47–61.
   Google Scholar
• Downey G. Food and food ingredient authentication by mid-infrared spectroscopy and chemometrics. Trends Anal Chem. 1998;17: 418–424.
   Web of Science ®Google Scholar
• Arhurst PR, Dennis MJ. Food Authentication. London, UK: Blackie Academic and Professional; 1996.
   Google Scholar
• Munck L, Norgaard L, Engelsen SB, Bro R, Andersson CA. Chemometrics in food science: a demonstration of the feasibility of a highly exploratory, inductive evaluation strategy of fundamental scientific significance. Chem Intell Lab Sys. 1998;44:31–60.
   Web of Science ®Google Scholar
• Francis IL, Høj PB, Dambergs RG, et al. In: Blair R, Williams P, Pretorious IS, editors. Proceedings 12th Australian Wine Industry Technical Conference. Adelaide, Australia: Winetitles; 2005.
   Google Scholar
• Bendell A, Disney J, McCollin C. The future role of statistics in quality engineering and management. The Statistician. 1999;48:299–326.
   Google Scholar
• Martens H, Martens M. Multivariate Analysis of Quality. An Introduction. Hoboken, NJ: John Wiley and Sons, Ltd; 2000.
   Google Scholar
• Naes T, Isaksson T, Fearn T, Davies T. A User-friendly guide to multivariate calibration and classification. Chichester, UK: NIR Publications; 2002.
   Google Scholar
• Wold S, Sjöstrom M, Eriksson L. PLS-regression: a basic tool of chemometrics. Chem Intell Lab Sys. 2001;58:109–130.
   Web of Science ®Google Scholar
• Otto M. Chemometrics: Statistics and computer application in analytical chemistry. Hoboken, NJ; Wiley-VCH; 1999.
   Google Scholar
• Siebert KJ. Chemometrics in brewing: a review. J Amer Soc Brew Chem. 2001;59:147–156.
   Web of Science ®Google Scholar
• Adams MJ. Chemometrics in analytical spectroscopy (RSC Spectroscopy Monographs). London, UK: The Royal Society of Chemistry; 1995.
   Google Scholar
• Brereton RG. Introduction to multivariate calibration in analytical chemistry. The Analyst. 2000;125:2125–2154.
   Web of Science ®Google Scholar
• Arvantoyannis I, Katsota MN, Psarra P, Soufleros E, Kallinthraka S. Application of quality control methods for assessing wine authenticity: Use of multivariate analysis (chemometrics). Trends Food Sci Technol. 1999;10:321–336.
   Web of Science ®Google Scholar
• Cordella Ch, Moussa I, Martel A-C, Sbirrazzuoli N, Lizzani-Cuvelier L. Recent developments in food characterisation and adulteration detection: technique-oriented perspectives. J Agric Food Chem. 2000;50: 1751–1764.
   Web of Science ®Google Scholar
• Cozzolino D, Smyth HE, Gishen M. Feasibility study on the use of visible and near infrared spectroscopy to discriminate between white wine of different varietal origin. J Agric Food Chem. 2003;54: 7703–7708.
   Google Scholar
• Cozzolino D, Kwiatkowski MY, Parker M, et al. Prediction of phenolic compounds in red wine fermentations by visible and near infrared spectroscopy. Anal Chim Acta. 2003;513:73–80.
   Web of Science ®Google Scholar
• Dambergs RG, Kambouris A, Francis IL, Gishen M. Rapid analysis of methanol in grape-derived distillation products using near infrared transmission spectroscopy. J Agric Food Chem. 2002;50:3079–3084.
   PubMed Web of Science ®Google Scholar
• Dambergs RG, Esler MB, Gishen M. Application in analysis of beverages and brewing products. In: Roberts CA, Workman J, Reeves JB, editors. Near Infrared Spectroscopy in Agriculture. Madison: Agronomy Monograph; 2004.
   Google Scholar
• Geladi P. Chemometrics in spectroscopy. Part I. Classical chemometrics. Spectrochimica Acta Part B. 2003;58:767–782.
   Web of Science ®Google Scholar
• Wold S. Chemometrics; what do we mean with it, and what do we want from it? Chem Intell Lab Sys. 1995;30:109–115.
   Web of Science ®Google Scholar
• Wise BM, Gallagher NB. The process chemometrics approach to process monitoring and fault detection. J Proc Cont. 1996;6:329–348.
   Web of Science ®Google Scholar
• Di Natale C, Davide FAM, D’Amico A, et al. Complex chemical pattern recognition with sensor array: the discrimination of vintage years of wine. Sensor Actuat. 1995;25:801–804.
   Web of Science ®Google Scholar
• Di Natale C, Paolesse R, Burgio M, Martinelli E, Pennazza G, D’Amico A. Application of metalloporphyrins-based gas and liquid sensor arrays to the analysis of red wine. Anal Chim Acta. 2004;513:49–56.
   Web of Science ®Google Scholar
• Di Natale C, Paolesse R, Macagnano A, et al. Application of a combined artificial olfaction and taste system to the quantification of relevant compounds in red wine. Sensor Actuat. 2000;69:342–347
   Web of Science ®Google Scholar
• Gutierrez A, Burgos JA, Garcera C, Padilla AI, Zarzo M, Chirivella C, Ruiz M L, Molto E. Optimization of an aroma sensor for assessing grape quality for wine making. Spanish J Agric Res. 2007;5:157–163.
   Web of Science ®Google Scholar
• Deisingh AK, Stone DC, Thompson M. Applications of electronic noses and tongues in food analysis. Int J Food Sci Tech. 2004;39:587–604.
   Web of Science ®Google Scholar
• Cozzolino D, Smyth HE, Lattey KA, et al. Combining mass spectrometry based electronic nose, visible-near infrared spectroscopy and chemometrics to assess the sensory properties of Australian Riesling wines. Anal Chim Acta. 2006;563:319–324.
   Web of Science ®Google Scholar
• Cynkar WU, Cozzolino D, Dambergs RG, 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. Sensor Actuat. 2007;124:167–171.
   Web of Science ®Google Scholar
• Aleixandre M, Lozano J, Gutierrez J, Sayago I, Fernandez MJ, Horrillo MC. Portable e-nose to classify different kinds of wine. Sensors and Actuators. 2008;131:71–76.
   Web of Science ®Google Scholar
• Buratti S, Bendetti S, Scampicchio M, Pangerod EC. Characterization and classification of Italian Barbera wines by using an electronic nose and an amperometric electronic tongue. Anal Chim Acta. 2004;525: 133–139.
   Web of Science ®Google Scholar
• Penza M, Cassano G. Chemometric characterization of Italian wines by thin-film multisensors array and artificial neural networks. Food Chem. 2004;86:283–296.
   Web of Science ®Google Scholar
• McKellar RC, Vasantha-Rupasinghe HP, Xuewen L, Knight KP. The electronic nose as a tool for the classification of fruit and grape wines from different Ontario wineries. J Sci Food Agric. 2005;85:2391–2396.
   Web of Science ®Google Scholar
• Lozano J, Santos JP, Aleixandre M, Sayago I, Gutierrez J, Horrillo MC. Identification of typical wine aromas by means of electronic nose. IEEE Sensors J. 2006;6:173–178.
   Web of Science ®Google Scholar
• Lozano J, Santos JP, Horrillo MC. Classification of white wine aromas with an electronic nose. Talanta. 2005;67:610–617.
   Web of Science ®Google Scholar
• Cozzolino D, Parker M, Dambergs RG, Herderich M, Gishen M. Chemometrics and visible-near infrared spectroscopic monitoring of red wine fermentation in a pilot scale. Biotech Bioeng. 2006;95: 1101–1107.
   PubMed Web of Science ®Google Scholar
• Esler MB, Gishen M, Francis IL, et al. Effects of variety and region on new infrared reflectance spectroscopic analysis of quality parameters in red wine grapes. In: Cho RK, Davies AMC, editors. Proceedings of the 10th International Conference. Chichester, UK: NIR Publications; 2002.
   Google Scholar
• Shenk JS, Berzaghi P, Westerhaus MO. Investigation of a LOCAL calibration procedure for near infrared instruments. J Near Infrared Spec. 1997;5:223–226.
   Google Scholar
• Dambergs RG, Cozzolino D, Cynkar WU, Janik L, Gishen M. The determination of red-grape quality parameters using the LOCAL algorithm. J Near Infrared Spec. 2006;14:71–79.
   Web of Science ®Google Scholar
• Urbano-Cuadrado M, Luque de Castro MD, Perez-Juan PM, Garcia-Olmo J, Gomez-Nieto MA. Near infrared reflectance, spectroscopy and multivariate analysis in enology – Determination or screening of fifteen parameters in different types of wines. Anal Chim Acta. 2004;527:81–88.
   Web of Science ®Google Scholar
• Sauvage L, Frank D, Stearne J, Milikan MB. Trace metal studies of selected white wines and alternative approach. Anal Chim Acta. 2002;458:223–230.
   Web of Science ®Google Scholar
• Manley M, van Zyl A, Wolf EEH. The evaluation of the applicability of Fourier transform near-infrared (FT-NIR) sppectroscopy in the measurement of analytical parameters in must and wine. S A J Oenol Viti. 2001;22:93–100.
   Google Scholar
• Soriano PM, Pérez-Juan A, Vicario JM, González Pérez-Coello MS. Determination of anthocyanins in red wine using a newly developed method based on Fourier transform infrared spectroscopy. Food Chem. 2007;104:1295–1303.
   Web of Science ®Google Scholar
• Patz C-D, Blieke A, Ristow R, Dietrich H. Application of FT-MIR spectrometry in wine analysis. Anal Chim Acta. 2004;513:81–89.
   Web of Science ®Google Scholar
• Coimbra MA, Goncalves F, Barros AS, Delgadillo I. Fourier transform infrared spectroscopy and chemometric analysis of white wine polysaccharide extracts. J Agric Food Chem. 2002;50:3405–3411.
   Web of Science ®Google Scholar
• Lletí R, Meléndez E, Ortiz MC, Sarabia LA, Sánchez MS. Outliers in partial least squares regression: Application to calibration of wine grade with mean infrared data. Anal Chim Acta. 2005;544:60–70.
   Web of Science ®Google Scholar
• Nieuwoudt HH, Prior BA, Pretorius IS, Manley M, Bauer FF. Principal component analysis applied to Fourier transform infrared spectroscopy for the design of calibration sets for glycerol prediction models in wine and for the detection and classification of outlier samples. J Agric Food Chem. 2004;52:3726–3735.
   PubMed Web of Science ®Google Scholar
• Cozzolino D, Cynkar W, Janik L, Dambergs RG, Gishen M. Analysis of grape and wine by near infrared spectroscopy – a review. J Near Infrared Spectros. 2006;14:279–289.
   Web of Science ®Google Scholar
• Dixit V, Tewari JC, Cho B K, Irudayraj JMK. Identification and quantification of industrial grade glycerol adulteration in red wine with Fourier transform infrared spectroscopy using chemometrics and artificial neural networks. Appl Spectros. 2005;59:1553–1561.
   Web of Science ®Google Scholar
• Le Moigne M, Maury Ch, Bertrand D, Jourjon F. Sensory and instrumental characterisation of Cabernet Franc grapes according to ripening stages and growing location. Food Qual Pref. 2008;19:220–231.
   Web of Science ®Google Scholar
• Janik L, Cynkar WU, Cozzolino D, Dambergs RG, Gishen M. The prediction of total anthocyanin concentration in red-grape homogenates using near-infrared spectroscopy and artificial neural networks. Anal Chim Acta. 2007;594:107–118.
   PubMed Web of Science ®Google Scholar