Feasibility of using a miniature NIR spectrometer to measure volumic mass during alcoholic fermentation

References

• Burns DA, Ciurczak EW. 2001. Handbook of Near-infrared Analysis. New York: Marcel Dekker.
   Google Scholar
• Burns DA, Ciurczak EW. 2008. Handbook of Near-infrared Analysis. Boca Raton, FL: CRC Press.
   Google Scholar
• Cozzolino D, Kwiatkowski MJ, Parker M, Cynkar WU, Dambergs RG, Gishen M, Herderich MJ. 2004. Prediction of phenolic compounds in red wine fermentation by visible and near infrared spectroscopy. Anal Chim Acta. 513:73–80.
   Web of Science ®Google Scholar
• Cozzolino D, Parker M, Dambergs RG, Herderich M, Gishen M. 2006. Chemometrics and visible-near infrared spectroscopy monitoring of red wine fermentation in a pilot scale. Biotechnol Bioeng. 95:1101–1107.
   PubMed Web of Science ®Google Scholar
• Cynkar W, Cozzolino D, Dambergs RG. 2009. The effect of sample storage and homogenization techniques on the chemical composition and near infrared spectra of white grapes. Food Res Int. 42:653–658.
   Web of Science ®Google Scholar
• Di Egidio V, Sinelli N, Giovanelli G, Moles A, Casiraghi E. 2010. NIR and MIR spectroscopy as rapid methods to monitor red wine fermentation. Eur Food Res Technol. 230:947–955.
   Web of Science ®Google Scholar
• Fernández-Novales J, López MI, Sánchez MT, García JA, Morales J. 2008. A feasibility study on the use of a miniature fiber optic NIR spectrometer for the prediction of volumic mass and reducing sugars in white wine fermentations. J Food Eng. 89:325–329.
   Web of Science ®Google Scholar
• Fernández-Novales J, López MI, Sánchez MT, Morales J, González-Caballero V. 2009. Shortwave-near infrared spectroscopy for non destructive determination of reducing sugars at stages of grape ripening, winemaking and aging of white and red wines. Food Res Int. 42:285–291.
   Web of Science ®Google Scholar
• Fernández-Novales J, Sánchez MT, López MI, García-Mesa JA, Ramírez P. 2010. Feasibility of using a miniature fiber optic ultraviolet-visible-near infrared spectrometer to assess total polyphenol index, color intensity and volumic mass in red wine fermentations J Food Proccess Eng in press, DOI: 10.1111/j.1745-4530.2009.00530.x.
   Google Scholar
• Liu F, He Y, Wang L, Pan H. 2007. Feasibility of the use of visible and near infrared spectroscopy to assess soluble solids content and pH of rice wines. J Food Eng. 83:430–435.
   Web of Science ®Google Scholar
• Martens H, Naes T. 1989. Multivariate Calibration. Chichester: John Wiley & Sons. p 419.
   Google Scholar
• Martens HA, Dardenne P. 1998. Validation and verification of regression in small data sets. Chemometr Intell Lab Syst. 44:99–121.
   Web of Science ®Google Scholar
• McGlone VA, Kawano S. 1998. Firmness, dry matter and soluble solids assessment of postharvest kiwifruit by NIR spectroscopy. Postharvest Biol Technol. 13:131–141.
   Web of Science ®Google Scholar
• Meuret M, Dardenne P, Biston R, Poty O. 1993. The use of NIR in predicting nutritive value of Mediterranean tree and shrub foliage. J Near Infrared Spec. 1:45–54.
   Google Scholar
• Miller CE. 2001. Chemical principles of near-infrared technology. In: Williams P, Norris K. editors. Near Infrared Technology in the Agricultural and Food Industries. St Paul, MN: American Association of Cereal Chemists. p 19–37.
   Google Scholar
• Murray I. 1986. The NIR spectra of homologous series of organic compounds. In: Hollo J, Kaffka KJ, Gonczy JL. editors. Near Infrared Diffuse Reflectance/Transmittance Spectroscopy, Proceedings International NIR/NIT Conference. Budapest: Akademiai Kiado. p 13–28.
   Google Scholar
• Naes T, Isaksson T, Fearn T, Davies A. 2002. A User-friendly Guide to Multivariate Calibration and Classification. Chichester, UK: NIR Publications.
   Google Scholar
• Official Journal of the European Union. 2005. Commission regulation (EC) 387 No 1293/2005 of 5 August 2005 amending regulation (EEC) No 2676/90 388 determining community methods for the analysis of wines. Official J L 389 205 (6 August): 12–15.
   Google Scholar
• Osborne BG, Fearn T, Hindle PH. 1993. Practical NlR spectroscopy with applications. In: Osborne BG, Fearn T, Hindle PH. editors. Food and Beverage Analysis. London: Longman Scientific and Technical. p 1–12.
   Google Scholar
• Peynaud E. 2000. Enología Práctica. Madrid, España: Mundi-Prensa.
   Google Scholar
• Ruiz-Hernández M. 1991. Vinificación en tinto. Madrid, España: Mundi-Prensa.
   Google Scholar
• Shao Y, He Y, Gómez AH, Pereir AG, Qiu Z, Zhang Y. 2007. Visible/near infrared spectrometric technique for nondestructive assessment of tomato “Heatwave” (Lycopersicum esculentum) quality characteristics. J Food Eng. 81:672–678.
   Web of Science ®Google Scholar
• Shenk JS, Westerhaus MOAnalysis of Agriculture and Food Products by Near Infrared Reflectance Spectroscopy. Silver Spring, MD: NIRSystems, Inc1995a.
   Google Scholar
• Shenk JS, Westerhaus MORoutine Operation, Calibration, Development and Network System Management Manual. Silver Spring, MD: NIRSystem, Inc1995b.
   Google Scholar
• Shenk JS, Westerhaus MO. 1996. Calibration the ISI way. In: Davies AMC, Williams PC. editors. Near Infrared Spectroscopy: The Future Waves. Chichester, UK: NIR Publications198–202.
   Google Scholar
• Shenk JS, Westerhaus MO, Abrams SM. 1989. Protocol for NIR calibrations: Monitoring analysis results and recalibration. In: Martens GC, Shenk JS, Barton II FE. editors. Near Infrared Spectroscopy (NIRS): Analysis of Forage Quality. Agriculture Handbook No. 643. Washington, DC: USDA-ARS, US Government Printing Office. p 104–110.
   Google Scholar
• Shenk JS, Workman J, Westerhaus M. 1992. Application of NIR spectroscopy to agricultural products. In: Burns DA, Ciurczak EW. editors. Handbook of Near-infrared Analysis. Practical Spectroscopy Series, 13. New York: Marcel Dekker. p 383–431.
   Google Scholar
• Skogerson K, Downey M, Mazza M, Boulton R. 2007. Rapid determination of phenolic components in red wines from UV-Visible spectra and the method of partial least squares. Am J Enol Viticult. 58:318–325.
   Web of Science ®Google Scholar
• Troost G. 1990. Tecnología del Vino. Barcelona, España: Omega.
   Google Scholar
• Urbano-Cuadrado M, De Castro MDL, Pérez-Juan PM, García-Olmo J, Gómez-Nieto MA. 2004. 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.
   Web of Science ®Google Scholar
• Windham WR, Mertens DR, Barton II FE. 1989. Protocol for NIRS calibration: Sample selection and equation development and validation. In: Martens GC, Shenk JS, Barton II FE. editors. Near Infrared Spectroscopy (NIRS): Analysis of Forage Quality, Agriculture Handbook No. 643. Washington, DC: USDA-ARS, US Government Printing Office. p 96–103.
   Google Scholar
• Williams PC. 2001. Implementation of near-infrared technology. In: Williams PC, Norris KH. editors. Near-infrared Technology in the Agricultural and Food Industries. St Paul, MN: AACC. p 145–169.
   Google Scholar
• Williams PC, Sobering DC. 1996. How do we do it: a brief summary of the methods we use in developing near infrared calibrations. In: Davies AMC, Williams P. editors. Near Infrared Spectroscopy: The Future Waves. Chichester, UK: NIR Publications. p 185–188.
   Google Scholar
• Yu H, Niu X, Lin H, Ying Y, Li B, Pan X. 2009. A feasibility study on on-line determination of rice wine composition by Vis–NIR spectroscopy and least-squares support vector machines. Food Chem. 113:291–296.
   Web of Science ®Google Scholar
• Zeaiter M, Roger JM, Bellon-Maurel V. 2006. Dynamic orthogonal projection. A new method to maintain the on-line robustness of multivariate calibrations, applications to NIR-based monitoring of wine fermentations. Chemometr Intell Lab. 80:227–235.
   Web of Science ®Google Scholar