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Reaction-Based Optical Fingerprinting Strategy in the Recognition of Proteins, Motor Oils, and Estimation of Food Irradiation Doses
1 , 1 , 2 , 1 , 1 , 1 , 1 , 2, 3 , 1 , * 1
1  Department of Chemistry, M.V. Lomonosov Moscow State University, Moscow, 119991 GSP-1, Russia
2  Physics Department, M.V. Lomonosov Moscow State University, Moscow, 119991 GSP-1, Russia
3  Skobeltsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, Moscow, 119991 GSP-1, Russia
Academic Editor: Nicole Jaffrezic-Renault

Abstract:

Colorimetric and fluorimetric fingerprinting techniques have gained popularity in solving various practical tasks associated with recognition and discrimination of samples. An underdeveloped aspect of optical fingerprinting methods is the use of kinetic factor that can serve as an additional variable. For the recognition of each type of sample we propose to select an indicator reaction whose rate is sensitive to the small variations in the composition of the sample. The samples and reactants are mixed in the 96-well fluorimetric plates, after which absorbance and fluorescence of the wells is registered photographically every several minutes. After digitization, the results are subjected to chemometric processing.

For the recognition of 8 model proteins or 10 samples of rennet enzymes, pre-oxidation of the sample with hypochlorite was suggested, and then a carbocyanine dye was added as reductant. For the recognition of motor oils, a set of reactions occurring in ethanol was proposed, and the reaction of oxidation of a commercial carbocyanine dye with nitric acid permitted to completely discriminate 6 oils. For the estimation of the doses absorbed by irradiated food (potatoes, ground beef), oxidation reactions of several carbocyanine dyes with hydrogen peroxide were used, which allowed for confident recognition of the dose to an order of magnitude (0, 100, 1000, 10,000 Gy). The proposed reaction-based approach turned out to be a powerful technique for solving various recognition tasks.

Keywords: colorimetric and fluorimetric sensors, kinetics, fingerprinting, recognition, irradiated food, proteins, motor oils, linear discriminant analysis

 
 
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