摘要
To ensure authenticity of sesame oil,an authentication technology was proposed using ion mobility spectrometry(IMS)and chemometrics.One-class classification(OCC)methods including one-class partial least squares(OCPLS)and one-class support vector machine(OCSVM)were employed to build authentication models for sesame oil.Subsequently,an independent test set was used to validate the constructed models.Validation set of 45 adulterated oils indicated that prediction correction rate of OCPLS model reached 95.6%(43 out of 45).Moreover,the complete set of sesame oils adulterated by sesame oil essence could be identified as counterfeit.Compared with previous studies,OCPLS model could work to identify untargeted adulteration.In conclusion,OCC method could effectively detect adulterated sesame oils containing as little as 10%other vegetable oils.This study provided a rapid screening method for adulterated sesame oil in market surveillance and a reference for developing authentication methods of other edible oils.
基金
This work was supported by the National Science and Technology Major Project of China(2017YFC1601700)
the National Nature Foundation Committee of P.R.China(31871886)
the National Major Project for Agro-product Quality&Safety Risk Assessment(GJFP2019003)
the earmarked fund for China Agricultural Research System(CARS-12)
the Fundamental Research Funds for Central Non-profit Scientific Institution(1610172018002 and 1610172018012).
