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Geographic Classification of Chinese Grape Wines by Near-Infrared Reflectance Spectroscopy 被引量:1

Geographic Classification of Chinese Grape Wines by Near-Infrared Reflectance Spectroscopy
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摘要 Near-infrared reflectance spectroscopy (NIRS) was applied to classify grape wines of different geographical origins (Changli, Huailai, and Yantai, China). Near infrared (NIR) spectra were collected in transmission mode in the wavelength range of 800-2500 nm. Wines (n=90) were randomly split into two sets, calibration set (n=54) and validation set (n=36). Discriminant analysis models were developed using BP neural network and discriminant partial least-squares discriminant analysis (PLS-DA). The prediction performance of calibration models in different wavelength range was also investigated. BP neural network models and PLS-DA models correctly classified 100% of the wines in calibration set. When used to predict wines in validation set, BP neural network models correctly classified 100%, 81.8%, and 90.9% of the wines from Changli, Huailai, and Yantai respectively, and PLS-DA models correctly classified 100% of all samples. The results demonstrated that NIRS could be used to discriminate Chinese grape wines as a rapid and reliable method. Near-infrared reflectance spectroscopy (NIRS) was applied to classify grape wines of different geographical origins ( Changli, Huailai, and Yantai, China ). Near infrared ( NIR ) spectra were collected in transmission mode in the wavelength range of 800-2500 rim. Wines ( n =90) were randomly split into two sets, calibration set ( n = 54 ) and validation set ( n = 36 ). Discriminant analysis models were developed using BP neural network and diecriminant partial least-squares discriminant analysis (PLS-DA). The prediction performance of calibration models in different wavelength range was also investigated. BP neural network models and PLS-DA models correctly classified 100% of the wines in calibration set. When used to predict wines in validation set, BP neural network models correctly classified 100%, 81. 8%, and 90.9 % of the wines from Changli, Huailai, and Yantai respectively, and PLS-DA models correctly classified 100% of all samples. The results demonstrated that NIRS could be used to discriminate Chinese grape wines as a rapid and reliable method.
出处 《Journal of Donghua University(English Edition)》 EI CAS 2012年第1期40-45,共6页 东华大学学报(英文版)
关键词 near-infrared reflectance spectroscopy (NIRS) Chinese grape wines discriminant analysis models BP neural network PLS-DA near-infrared reflectance spectroscopy (NIRS) Chinese grape wines discriminant analysis models BP neural network PLS-DA
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  • 1Anderson K,Norman D,Wittwer G. Globalisation of the World's Wine Markets[J].World Economy,2003,(05):659-687.doi:10.1007/s12640-009-9045-x. 被引量:1
  • 2Addor F,Grazioli A. Geographical Indications beyond Wines and Spirits[J].The Journal of World Intellectual Property,2005,(06):865-897.doi:10.1016/j.jbiomech.2009.12.016. 被引量:1
  • 3Blakeney M. Proposals for the International Regulation of Geographical Indications[J].The Journal of World Intellectual Property,2001,(05):629-652. 被引量:1
  • 4Wang X B,Kireeva I. Protection of Geographical Indications in China Conflicts Causes and Solutions[J].The Journal of World Intellectual Property,2007,(02):79-96.doi:10.1084/jem.20091568. 被引量:1
  • 5Kwan W O,Kowalski B R,Skogerboe R K. Pattern Recognition Analysis of Elemental Data.Wines of Vitis vinifera cv.Pinot Noir from France and the United States[J].Journal of Agricultural and Food Chemistry,1979,(06):1321-1326.doi:10.1021/jf60226a039. 被引量:1
  • 6Sivertsen H K,Holen B,Nicolaysen F. Classification of French Red Wines according to Their Geographical Origin by the Use of Multivariate Analyses[J].Journal of the Science of Food and Agriculture,1999,(01):107-115.doi:10.1002/(SICI)1097-0010(199901)79:1<107::AID-JSFA193>3.0.CO;2-A. 被引量:1
  • 7Legin A,Rudnitskaya A,Lvova L. Evaluation of Italian Wine by the Electronic Tongue:Recognition Quantitative Analysis and Correlation with Human Sensory Perception[J].Analytica Chimica Acta,2003,(01):33-44.doi:10.1016/S0003-2670(03)00301-5. 被引量:1
  • 8Buratti S,Ballabio D,Benedetti S. Prediction of Italian Red Wine Sensorial Descriptors from Electronic Nose,Electronic Tongue and Spectrophotometric Measurements by Means of Genetic Algorithm Regression Models[J].Food Chemistry,2007,(01):211-218. 被引量:1
  • 9Liu L,Cozzolino D,Cynkar W U. Geographic Classification of Spanish and Australian Tempranillo Red Wines by Visible and Near-Infrared Spectroscopy Combined with Multivariate Analysis[J].Journal of Agricultural and Food Chemistry,2006,(18):6754-6759.doi:10.1021/jf061528b. 被引量:1
  • 10Osborne B G. Near Infrared Spectroscopy in Food Analysis[M].England:Longman Scientific and Technical,1986. 被引量:1

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