Paper
27 October 2006 Prediction of ethanol in bottled Chinese rice wine by NIR spectroscopy
Yibin Ying, Haiyan Yu, Xingxiang Pan, Tao Lin
Author Affiliations +
Proceedings Volume 6381, Optics for Natural Resources, Agriculture, and Foods; 638108 (2006) https://doi.org/10.1117/12.685986
Event: Optics East 2006, 2006, Boston, Massachusetts, United States
Abstract
To evaluate the applicability of non-invasive visible and near infrared (VIS-NIR) spectroscopy for determining ethanol concentration of Chinese rice wine in square brown glass bottle, transmission spectra of 100 bottled Chinese rice wine samples were collected in the spectral range of 350-1200 nm. Statistical equations were established between the reference data and VIS-NIR spectra by partial least squares (PLS) regression method. Performance of three kinds of mathematical treatment of spectra (original spectra, first derivative spectra and second derivative spectra) were also discussed. The PLS models of original spectra turned out better results, with higher correlation coefficient in calibration (Rcal) of 0.89, lower root mean standard error of calibration (RMSEC) of 0.165, and lower root mean standard error of cross validation (RMSECV) of 0.179. Using original spectra, PLS models for ethanol concentration prediction were developed. The Rcal and the correlation coefficient in validation (Rval) were 0.928 and 0.875, respectively; and the RMSEC and the root mean standard error of validation (RMSEP) were 0.135 (%, v v-1) and 0.177 (%, v v-1), respectively. The results demonstrated that VIS-NIR spectroscopy could be used to predict ethanol concentration in bottled Chinese rice wine.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yibin Ying, Haiyan Yu, Xingxiang Pan, and Tao Lin "Prediction of ethanol in bottled Chinese rice wine by NIR spectroscopy", Proc. SPIE 6381, Optics for Natural Resources, Agriculture, and Foods, 638108 (27 October 2006); https://doi.org/10.1117/12.685986
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KEYWORDS
Bioalcohols

Calibration

Spectroscopy

Near infrared

Statistical analysis

Near infrared spectroscopy

Error analysis

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