Hunan Provincial Research Institute of Agricultural Product Processing

Changsha, China

Hunan Provincial Research Institute of Agricultural Product Processing

Changsha, China
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Fan W.,Central South University | Shan Y.,Hunan Provincial Research Institute of Agricultural Product Processing | Shan Y.,Hunan Food Test and Analysis Center | Li G.,Hunan Provincial Research Institute of Agricultural Product Processing | And 5 more authors.
Food Analytical Methods | Year: 2012

In this paper, near-infrared (NIR) spectroscopy coupled with wavelength selection methods was used to predict total acid of vinegar. Three wavelength selection methods including competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variable elimination (MC-UVE), and moving window partial least squares (MWPLS) were employed to select the key wavelengths. Five wavelengths including 4,348, 4,694, 5,365, 7,104, and 7,236 cm -1 were selected by CARS method. Least squares (LS) regression model was built on the selected wavelengths. Compared to the partial least squares regression models based on full spectrum and wavelengths selected by MC-UVE and MWPLS, the performance of LS model was better, with higher determination coefficient for test (r 2) of 0.997, and lower root mean square error of prediction of 0.13 g/100 ml. Based on the results, it was concluded that NIR spectroscopy combined with CARS methods seem to be a rapid and effective alternative to the classical methods for the prediction of total acid of vinegar. © 2011 Springer Science+Business Media, LLC.


Fan W.,Central South University | Li H.,Central South University | Shan Y.,Hunan Provincial Research Institute of Agricultural Product Processing | Shan Y.,Hunan Food Test and Analysis Center | And 4 more authors.
Analytical Methods | Year: 2011

In this paper, near infrared spectroscopy combined with a wavelength selection method was used to identify fermented vinegar and blended vinegar. Competitive adaptive reweighted sampling (CARS) method was employed to select the key wavelengths. For classification of different vinegars, 11 wavelengths were selected and a PLS-DA model was calculated based on these selected wavelengths. The average error rate (AER) obtained by repeated double cross validation (RPCV) was 6.95%. The results indicated that NIR spectroscopy combined with a wavelength selection method could be applied as a fast alternative method for the identification of different vinegars. © The Royal Society of Chemistry 2011.

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