[Progress in Application of Two-Dimensional Correlation Spectroscopy for Detection of Food Quality].

In recent years, the food safety and quality has always been a serious issue. Therefore, it is urgent to develop a rapid and widely available method to determine the quality of food. Due to high spectral resolution, good spectral selectivity and good ability of spectrogram analysis, the technology of two-dimensional (2D) correlation spectroscopy is an effective method for solving three major problems encountered by the conventional one-dimensional (1D) spectrum: low selectivity of the spectra, difficulty in extracting the information of the spectral feature and difficulty in spectrogram analysis. Therefore, 2D correlation spectroscopy, which is suited to distinguish similar samples hardly distinguished by the conventional 1D spectroscopy, has been successfully applied in many complex biological systems. The developmental process, the experimental way to obtain spectrum, the fundamental mathematical principle and the properties of 2D correlation spectroscopy were introduced in this paper. At the same time, it is pointed out that the origin of weak characteristic bands of substance can be verified in terms of the positive or negative corss peaks in synchronous 2D correlation spectrum combined with the existence or inexistence of corss peaks in asynchronous 2D correlation spectrum. The application of 2D near-infrared, mid-infrared, fluorescence, and raman correlation spectroscopy in the detection of food quality and adulteration, concentrated specifically on diary product, wine, oil, meat, honey, and rice were reviewed. Finally, the limitations and future development prospects were pointed out.

[Discrimination of adulterated milk based on Euclidian distances between two-dimensional infrared correlation spectra].

Based on Euclidian distances between synchronous two-dimensional infrared correlation spectra, in terms of the average Euclidian distances between unknown samples and "extreme samples", and average intra- and inter-Euclidian distances of samples in the calibration set, a new method for the discrimination of adulterated milk was proposed. Sixteen pure milk samples were collected and 16 adulterated milk samples with urea (0.01-0.3 g x L(-1)), and 16 adulterated milk samples with melamine (0.01-0.3 g x L(-1)) samples were prepared, respectively. The IR absorption spectra of all samples were measured at room temperature. The synchronous two-dimensional correlation spectra were generated from concentration-dependent spectral variation of adulterant in milk. The Euclidian distances were calculated between synchronous two-dimensional infrared correlation spectra of all samples. Then, the classification models were built respectively for adulterated milk with urea, and adiulterated milk with melamine. The "extreme samples", average intra- and inter-Euclidian distances were determined. Finally, the unknown samples in prediction set were predicted using constructed models in terms of classification rules of adulterated milk. The classification accuracy rates for pure milk and adulterated milk were 100%. The effectiveness of the proposed method was verified. The results obtained in this study revealed that synchronous two-dimensional infrared correlation spectra in combination with Euclidian distance has a feasible potential to discriminate adulterated milk and pure milk.