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Identification of edible vegetable oils based on infrared spectrum
  
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KeyWord:edible vegetable oil  identification  infrared spectrum  spectral pretreatment  Radial Basis Function neural network  Random Forest
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SUN Yijian，WANG Jifen，ZHANG Zhen School of Investigation, People′s Public Security University of China, Beijing 100038, China 
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Abstract:
      In order to establish the identification method of edible vegetable oils based on infrared spectrum, 296 samples of 5 kinds of common edible vegetable oils were collected, their infrared spectrum were collected and pretreated by Savitzky-Golay smoothing, Hilbert transform, IIR low-pass filter, IIR high pass filter, continuous wavelet transform, first derivative and second derivative respectively, and spectrums were identified by Radial Basis Function(RBF) neural network and Random Forest(RF) models. The results showed that the effect of RBF neural network was better than the RF model. After pretreating the infrared spectrum data by the Hilbert transform, the recognition rate of the RBF neural network model reached 100%. This method has the advantages of rapid non-destructive, high accuracy and good effect in the identification of edible vegetable oils.
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