利用太赫兹技术和统计方法鉴别地沟油

基于普通食用油和地沟油的太赫兹吸收光谱,利用0.16~1.30 THz频域的吸收谱,进行聚类分析,8种地沟油组成一类,食用油自成一类。随机选择了2种地沟油作为验证样品,将其余油样进行聚类,采用概率神经网络法对验证样品进行判定,并成功将2种油判定为地沟油。结果表明,太赫兹时域光谱技术结合统计方法可推广成为鉴别地沟油的快速有效手段。

Discerning of swill-cooked dirty oil by terahertz technology and statistical method

Cluster analysis (CA) was used to analyze edible oil and swill-cooked dirty oil based on the terahertz absorption spectra at 0.16-1.30 THz. Eight kinds of swill-cooked dirty oils were clusterd together and edible oil was separated. Two kinds of swill-cooked dirty oils were selected randomly from nine samples as validation samples, and the rest samples were analyzed by CA. Based on the built CA model, probabilistic neural network (PNN) was adopted to recognize the validation samples, and swill-cooked dirty oils were accurately discerned. It was demonstrated that terahertz technology combined with statistical methods could be extended to become a fast and effective way to discern swill-cooked dirty oil.