Geographic Classification of Chinese Grape Wines by Near-Infrared Reflectance Spectroscopy

赵芳; 赵育; 毛文华; 战吉宬

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Geographic Classification of Chinese Grape Wines by Near-Infrared Reflectance Spectroscopy

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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.

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《东华大学学报：英文版》 |2012年第1期|40-45|共6页
作者
赵芳; 赵育; 毛文华; 战吉宬;
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作者单位

College of Food Science and Nutritional Engineering;

China Agricultural University;

Chinese Academy of Agricultural Mechanization Sciences;

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原文格式 PDF
正文语种 chi
中图分类食品化学;
关键词
near-infrared reflectance spectroscopy (NIRS); Chinese grape wines; discriminant analysis models; BP neural network; PLS-DA;

Geographic Classification of Chinese Grape Wines by Near-Infrared Reflectance Spectroscopy

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