Abstract
A new method for the discrimination of adulterated milk based on two-dimensional(2D) correlation infrared spectroscopy and least square support vector machines(LS-SVM)was proposed.48pure milk samples were collected and 16urea-tainted milk(0.01~0.3g/L),16 melamine-tainted milk(0.01~0.3g/L),16tetracycline-tainted milk(0.01~0.3g/L)were prepared.Based on the characteristics of 2D correlation infrared spectra of pure milk and adulterated milk,6apparent statistic parameters of all samples were extracted and calculated.These 6parameters were used as input for LS-SVM to build discriminant model of adulterated milk and pure milk.The recognition rate of unknown samples was 90.6%.The results reveal that parameterization of 2D correlation spectra in combination with LS-SVM method has a feasible potential to discrimination adulterated milk and pure milk.
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