%A WANG Li;LIU Fei;HE Yong* %T Fast Detection of White Vinegar Varieties and pH by Vis/NIR Spectroscopy %0 Journal Article %D 2008 %J SPECTROSCOPY AND SPECTRAL ANALYSIS %R 10.3964/j.issn.1000-0593.2008.04.041 %P 813-816 %V 28 %N 04 %U {https://www.gpxygpfx.com/CN/abstract/article_369.shtml} %8 2008-04-29 %X White vinegar is a condiment indispensable in our life, but our understanding of the white vinegar and evaluation of its quality and function has been gained through routine chemical and physical analysis. It is called for to develop more time- and cost-efficient methodologies for white vinegar detection. Visible and near infrared spectroscopy (Vis/NIR) is a nondestructive, fast and accurate technique for the measurement of chemical components based on overtone and combination bands of specific functional groups. Vis/NIR transmittance spectroscopy and chemometrics methods were utilized in classification and pH mensuration of white vinegar in the present study. First, the spectral curves of white vinegar were obtained by handheld Vis/NIR spectroradiometer, then principal component analysis (PCA) was used to process the spectral data after pretreatment. Five principal components (PCs) were selected based on accumulative reliabilities (AR), and these selected PCs would be taken as the inputs of the three-layer back-propagation artificial neural network (BP-ANN). A total of 240 white vinegar samples were divided into calibration set and validation set randomly, the calibration set had 180 samples with 60 samples of each variety, and the validation set had 60 samples with 20 samples of each variety. The BP-ANN was trained using samples in calibration set, the optimal three-layer BP-ANN model with 5 nodes in input layer, 6 nodes in hidden layer, and 2 nodes in output layer would be obtained, and the transfer function of sigmoid was used in each layer. Then, this model was used to predict the samples in the validation set. The result indicated that a 100% recognition ration was achieved with the threshold predictive error ±0.1, the bias between predictive value and standard value was lower than 5%. It could be concluded that PCA combined with BP-ANN was an available method for varieties recognition and pH mensuration of white vinegar based on Vis/NIR transmittance spectroscopy.