In order to explore the non-destructive, rapid and accurate method of distinguishing different types of strong-flavor Baijiu, different alcoholic strength and different brands of strong-flavor Baijiu were selected as the research object in this study. Using the Fourier transform mid-infrared spectrometer to collect the original spectra of 120 Baijiu samples, combining the smoothing filtering and the standard normal variate method to preprocess the original spectra respectively, and the principal component analysis was used to compare the spectral preprocessing effects. The spectral data were divided into training set and test set according to the Kennard-Stone method with a ratio of 7∶3. After the data normalized, the grasshopper algorithm was used to optimize the support vector machine and the error back-propagation artificial neural network for modeling and analysis. The test results showed that spectral preprocessing combined with principal component analysis cannot distinguish strong-flavor Baijiu with different alcoholic strength and brands, but the clustering distinction of Baijiu samples with different alcoholic strength after smoothing filtering treatment was better, and the clustering distinction of different brands of Baijiu samples after standard normal variate processing was better, both of them can effectively reduce the noise of mid-infrared spectrum and improve the recognition accuracy. When the discriminant analysis was performed based on the grasshopper algorithm was used to optimize the support vector machine and the error back-propagation artificial neural network models, the classification accuracy of Baijiu samples in both the training set and the test set was 100%. In summary, the method of mid-infrared spectroscopy combined with chemometrics can identify strong-flavor Baijiu with different alcoholic strength and brands quickly and accurately, and can provide digital solutions for Baijiu aroma differentiation, origin traceability, market supervision and after-sales management.
ZHOU Rui
,
CHEN Xiaoming
,
ZHANG Lili
,
ZHANG Liang
,
XU Defu
,
ZHANG Suyi
,
DAI Xiaoxue
,
MAO Hongchuan
,
XIE Fei
,
DAI Hancong
,
SONG Yan
,
GUO Jia
,
CHEN Wenyue
. Classification of strong-flavor Baijiu based on chemometrics and mid-infrared spectroscopy[J]. Food and Fermentation Industries, 2023
, 49(5)
: 88
-93
.
DOI: 10.13995/j.cnki.11-1802/ts.031674
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