A comparative study to distinguish the vineyard of origin by NIRS using entire grapes, skins and seeds

Journal of the Science of Food and Agriculture

Volumn 93, Issue 4, 2013, Pages 967-972

  Ferrer Gallego, Raúl ^a   Hernández Hierro, José Miguel ^a,b   Rivas Gonzalo, Julián C ^a   Escribano Bailón, M Teresa ^a  

^a UNIVERSITY OF SALAMANCA   (Spain)

^b UNIVERSITY OF SEVILLE   (Spain)

Author keywords

Grapes; Near infrared spectroscopy; Phenolic compounds; Vineyards

Indexed keywords

PLANT MEDICINAL PRODUCT;

ARTICLE; COMPARATIVE STUDY; FIBER OPTICS; FRUIT; METHODOLOGY; NEAR INFRARED SPECTROSCOPY; PLANT SEED; RECEIVER OPERATING CHARACTERISTIC; REGRESSION ANALYSIS; VITIS; WINE;

FIBER OPTIC TECHNOLOGY; FRUIT; LEAST-SQUARES ANALYSIS; PLANT PREPARATIONS; ROC CURVE; SEEDS; SPECTROSCOPY, NEAR-INFRARED; VITIS; WINE;

VITACEAE;

EID: 84874018155     PISSN: 00225142     EISSN: 10970010     Source Type: Journal    
DOI: 10.1002/jsfa.5842     Document Type: Article

References (40)

1. Berrueta LA, Alonso-Salces RM and Heberger K, Supervised pattern recognition in food analysis. J Chromatogr A 1158: 196-214 (2007).
2. Kelly S, Heaton K and Hoogewerff J, Tracing the geographical origin of food: the application of multi-element and multi-isotope analysis. Trends Food Sci Technol 16: 555-567 (2005).
3. Luykx DMAM and van Ruth SM, An overview of analytical methods for determining the geographical origin of food products. Food Chem 107: 897-911 (2008).
4. Reid LM, O'Donnell CP and Downey G, Recent technological advances for the determination of food authenticity. Trends Food Sci Technol 17: 344-353 (2006).
5. Berente B, De la Calle García D, Reichenbächer M and Danzer K, Method development for the determination of anthocyanins in red wines by high-performance liquid chromatography and classification of German red wines by means of multivariate statistical methods. J Chromatogr A 871: 95-103 (2000).
6. Makris DP, Kallithraka S and Mamalos A, Differentiation of young red wines based on cultivar and geographical origin with application of chemometrics of principal polyphenolic constituents. Talanta 70: 1143-1152 (2006).
7. De Villiers A, Majek P, Lynen F, Crouch A, Lauer H and Sandra P, Classification of South African red and white wines according to grape variety based on the non-coloured phenolic content. Eur Food Res Technol 221: 520-528 (2005).
8. Almela L, Javaloy S, Fernández-López JA and López-Roca JM, Varietal classification of young red wines in terms of chemical and colour parameters. J Sci Food Agric 70: 173-180 (1996).
9. García-Marino M, Hernández-Hierro JM, Santos-Buelga C, Rivas-Gonzalo JC and Escribano-Bailón MT, Multivariate analysis of the polyphenol composition of Tempranillo and Graciano red wines. Talanta 85: 2060-2066 (2011).
10. Pérez-Magariño S, Ortega-Heras M, González-San José ML and Boger Z, Comparative study of artificial neural network and multivariate methods to classify Spanish DO rose wines. Talanta 62: 983-990 (2004).
11. Rodríguez-Delgado M-Á, González-Hernández G, Conde-González J-E and Pérez-Trujillo J-P, Principal component analysis of the polyphenol content in young red wines. Food Chem 78: 523-532 (2002).
12. Kallithraka S, Mamalos A and Makris DP, Differentiation of young red wines based on chemometrics of minor polyphenolic constituents. J Agric Food Chem 55: 3233-3239 (2007).
13. Fernandez-Novales J, Lopez MI, Sanchez MT, Morales J and Gonzalez-Caballero V, Shortwave-near infrared spectroscopy for determination of reducing sugar content during grape ripening, winemaking, and aging of white and red wines. Food Res Int 42: 285-291 (2009).
14. Boulet JC, Williams P and Doco T, A Fourier transform infrared spectroscopy study of wine polysaccharides. Carbohydr Polym 69: 79-85 (2007).
15. Jensen JS, Egebo M and Meyer AS, Identification of spectral regions for the quantification of red wine tannins with Fourier transform mid-infrared spectroscopy. J Agric Food Chem 56: 3493-3499 (2008).
16. Moreira JL and Santos L, Analysis of organic acids in wines by Fourier-transform infrared spectroscopy. Anal Bioanal Chem 382: 421-425 (2005).
17. Patz CD, Blieke A, Ristow R and Dietrich H, Application of FT-MIR spectrometry in wine analysis. Anal Chim Acta 513: 81-89 (2004).
18. Smyth HE, Cozzolino D, Cynkar WU, Dambergs RG, Sefton M and Gishen M, Near infrared spectroscopy as a rapid tool to measure volatile aroma compounds in Riesling wine: possibilities and limits. Anal Bioanal Chem 390: 1911-1916 (2008).
19. Urbano-Cuadrado M, Luque de Castro MD, Perez-Juan PM, Garcia-Olmo J and 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 527: 81-88 (2004).
20. Ferrer-Gallego R, Hernández-Hierro JM, Rivas-Gonzalo JC and Escribano-Bailón MT, Determination of phenolic compounds of grape skins during ripening by NIR spectroscopy. LWT-Food Sci Technol 44: 847-853 (2011).
21. Ferrer-Gallego R, Hernández-Hierro JM, Rivas-Gonzalo JC and Escribano-Bailón MT, Feasibility study on the use of near infrared spectroscopy to determine flavanols in grape seeds. Talanta 82: 1778-1783 (2010).
22. Cozzolino D, Holdstock M, Dambergs RG, Cynkar WU and Smith PA, Mid infrared spectroscopy and multivariate analysis: a tool to discriminate between organic and non-organic wines grown in Australia. Food Chem 116: 761-765 (2009).
23. Tarantilis PA, Troianou VE, Pappas CS, Kotseridis YS and Polissiou MG, Differentiation of Greek red wines on the basis of grape variety using attenuated total reflectance Fourier transform infrared spectroscopy. Food Chem 111: 192-196 (2008).
24. Cozzolino D, Smyth HE and Gishen M, Feasibility study on the use of visible and near-infrared spectroscopy together with chemometrics to discriminate between commercial white wines of different varietal origins. J Agric Food Chem 51: 7703-7708 (2003).
25. Louw L, Roux K, Tredoux A, Tomic O, Naes T, Nieuwoudt HH, et al, Characterization of selected South African young cultivar wines using FTMIR spectroscopy, gas chromatography, and multivariate data analysis. J Agric Food Chem 57: 2623-2632 (2009).
26. Urtubia A, Perez-Correa JR, Pizarro F and Agosin E, Exploring the applicability of MIR spectroscopy to detect early indications of wine fermentation problems. Food Control 19: 382-388 (2008).
27. Oliveri P, Di Egidio V, Woodcock T and Downey G, Application of class-modelling techniques to near infrared data for food authentication purposes. Food Chem 125: 1450-1456 (2011).
28. Oelofse A, Malherbe S, Pretorius IS and Du Toit M, Preliminary evaluation of infrared spectroscopy for the differentiation of Brettanomyces bruxellensis strains isolated from red wines. Int J Food Microbiol 143: 136-142 (2010).
29. Liu L, Cozzolino D, Cynkar WU, Gishen M and Colby CB, Geographic classification of Spanish and Australian Tempranillo red wines by visible and near-infrared spectroscopy combined with multivariate analysis. J Agric Food Chem 54: 6754-6759 (2006).
30. Bevin CJ, Dambergs RG, Fergusson AJ and Cozzolino D, Varietal discrimination of Australian wines by means of mid-infrared spectroscopy and multivariate analysis. Anal Chim Acta 621: 19-23 (2008).
31. Herrera J, Guesalaga A and Agosin E, Shortwave-near infrared spectroscopy for non-destructive determination of maturity of wine grapes. Meas Sci Technol 14: 689-697 (2003).
32. Le Moigne M, Maury C, Bertrand D and Jourjon F, Sensory and instrumental characterisation of Cabernet Franc grapes according to ripening stages and growing location. Food Qual Prefer 19: 220-231 (2008).
33. Arana I, Jaren C and Arazuri S, Maturity, variety and origin determination in white grapes (Vitis vinifera L.) using near infrared reflectance technology. J Near Infrared Spectrosc 13: 349-357 (2005).
34. Ferrer-Gallego R, Hernández-Hierro JM, Rivas-Gonzalo JC and Escribano-Bailón MT, Influence of climatic conditions on the phenolic composition of Vitis vinifera L. cv. Graciano. Anal Chim Acta 732: 73-77 (2012).
35. Ferrer-Gallego R, Garcia-Marino M, Hernandez-Hierro JM, Rivas-Gonzalo JC and Escribano-Bailon MT, Statistical correlation between flavanolic composition, colour and sensorial parameters in grape seed during ripening. Anal Chim Acta 660: 22-28 (2010).
36. Lars S and Svante W, Partial least squares analysis with cross-validation for the two-class problem: a Monte Carlo study. J Chemometrics 1: 185-196 (1987).
37. Massart DL, Vandeginste BG, Buydens LM, Lewis PJ, Smeyers-Verbeke J and Jong SD, Handbook of Chemometrics and Qualimetrics. Elsevier Science, Amsterdam (1998).
38. Shenk JS, The wonderful world of visible-near infrared spectra: theory and practice, in Near Infrared Spectroscopy: Proceedings of the 11th International Conference, ed. by Davies AMC and Garrido-Varo A. NIR Publications, Norwich, pp. 159-164 (2004).
39. Osborne BG, Fearn T and Hindle PT, Practical NIR Spectroscopy with Applications in Food and Beverage Analysis. Longman Scientific and Technical, Harlow (1993).
40. Siesler HW, Ozaky Y, Kawata S and Heise HM, Near Infrared Spectroscopy: Principles, Instruments, Applications. Wiley-VCH, Weinheim (2002).