Two-Dimensional Hetero-Spectral Near-Infrared and Mid-Infrared Correlation Spectroscopy for Discrimination Adulterated Milk
YU Ge1, YANG Ren-jie2, Lü Ai-jun1, TAN En-zhong1
1. Department of Mathematics and Physics, Beijing Institute of Petrochemical Technology, Beijing 102617, China 2. College of Engineering and Technology, Tianjin Agricultural University, Tianjin 300384, China
Abstract：New approach for discriminant analysis of adulterated milk is proposed based on combining hetero-spectral two-dimensional (2D) near-infrared (NIR) and mid-infrared (IR) correlation spectroscopy along with multi-way partial least squares discriminant analysis (NPLS-DA). Firstly, 36 pure milk samples were collected and 36 adulterated milk with starch samples (0.01 to 1 g·L-1) were prepared by adding appropriate mass of starch into pure milk. Then, one-dimensional NIR transmittance spectra and IR attenuated total reflection spectra of pure milk and adulterated milk with starch were measured at room temperature. And the synchronous 2D NIR-IR (4 200～4 800 vs. 900～1 700 cm-1) correlation spectra of all samples were calculated. Due to the trace of adulterants, the synchronous 2D IR-NIR correlation spectral differences between adulterated milk with starch and pure milk are very subtle. Consequently, it was impossible to directly distinguish whether the sample was pure milk or adulterated milk. Finally, 2D IR-NIR correlation spectra were to build a discriminant model to classify adulterated milk and pure milk. The classification accuracy rates of samples in calibration set and in prediction set were 95.8% and 100% respectively. Also, the NPLS-DA models were built based on 2D NIR and 2D IR correlation spectra, respectively. The classification accuracy rates of samples in prediction set were 95.8%. Comparison results showed that the NPLS-DA model could provide better results using 2D NIR-IR correlation spectra than using 2D NIR, and 2D IR correlation spectra. The proposed method can not only effectively extract the feature information of adulterants in milk, but also explores a new perspective method for detection of adulterated food.
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