Studies On Application Of Fluorescence Spectroscopy In Food Safety Supervision

Using fluorescence spectroscopy and artificial neural network method, we made successful measurement and identification of some materials in this letter, such as synthetic food colors, chinese liquors, fermented wines including rice wines and wines, stuffs relating to food safety as of melamine, and et al. Characteristics and features of these fluorescence spectra are discussed, and basic systems for real time monitoring of food safety using fluorescence spectroscopy are further designed.In the experiments, we successfully obtained the three-dimensional fluorescence spectra of eleven synthetic food colors (including Ponceau 4R, Amaranth, Allura Red, Acid Red, Erythrosine, New Red, Sunset Yellow, Tartrazine, Quinoline Yellow, Brilliant Blue, and Indigotine) allowed by-Chinese government currently and several industrial pigments (including Sudan I and Sudan IV) which are often added to food illegally. Fluorescence emission spectra of these synthetic food colors and industrial pigments are also obtained under the conditions that the solutions are detected at ten different concentrations with their own optimal excitation wavelength. With these experiments above, spectral features of each synthetic food color or industrial pigment can be achieved. The relationship between fluorescence intensity and the corresponding concentration of the solution can also be determined. The results indicate that with excitation of short wavelength these synthetic food colors and industrial pigments all produce fluorescence light of high intensity, and each fluorescence spectra of them has its distinct characteristics.After that we extracted some characteristic parameters from the fluorescence spectra and handled them by some new methods such as the wavelet transformation and derivative spectra. Using the data above, we built up and trained the BP, RBF and PNN neural networks through which we can not only identify these synthetic food colors easily, quickly and precisely but also determine the concentration of their solutions. The accuracy rates of identification reach 100%, and the average relative error remains under 4% for each detection:Here, for the first time, we not only accurately identified these synthetic food colors and industrial pigments but also determined the concentration of them in mixed solutions at the same time.From the experiments we built up the fluorescence data base of Chinese liquors and added some new data from fluorescence data of recent liquor samples. We initially convert six characteristic parameters to one characteristic vector. The six parameters include numbers of fluorescence peaks, wavelength at maximum fluoresence intensity, optimal excitation wavelength, and three linewidths at 1/4,1/2,3/4 of maximum fluorescence emission spectra. Based on Euclidean distance, using methods such as automatic extraction, search and comparison, discriminant classification, vector operation, and decision of threshold values, we built the identification system of Chinese liquors on fluorescence spectra. The system exploits the advantage of fluorescence spectroscopy and computer intelligent technology, and realizes the identification of Chinese liquors from their species and years in a scientific, instrumental, and intelligent manner.In addition, we made quantitative measurement of concentrations of melamine using fluorescence spectroscopy technique for the first time with an average relative error under 1.5%. We also detected and analyzed the fluorescence data of the cooking oil after it was heated. The result shows that under light excitation of 400 nm the cooking oil produces fluorescent light with high intensity. We even obtained the rules how the two fluorescence peaks change with heating time and the number of times, and made some analysis about them. Moreover, we studied the fluorescence spectroscopy of some pesticides and some fermented wines including rice wines, beers, and wines. All the experimental results above indicate that fluorescence spectroscopy which can be used in both qualitative and quantitative detection, is the fingerprint and the characteristic information of the fluorescent materials.We further made a feasibility study of setting up a system for real time monitoring of food safety using fluorescence spectroscopy. We proposed some design solutions, and details about elements, structures and configurations were carefully considered.In conclusion, the work in this letter not only provides a new way in riching and developing the detecting techniques for food safety, but also provides technical support in innovative methods and improvements on food safety supervision.