Artificial neural networks and multivariate calibration for spectrophotometric differential kinetic determinations of food antioxidants

Capillary Electrophoresis-Amperometric Determination of Antioxidant Propyl Gallate and Butylated Hydroxyanisole in Foods

Capillary electrophoretic separation coupled with end-column amperometric detection for the simultaneous quantification of butylated hydroxyanisole (BHA) and propyl gallate (PG) in food was developed. Important factors affecting separation and detection, such as the running buffer, separation voltage, and detection potential, were investigated in detail. An improved working electrode preparation method was used, where a carbon disk of 33 microm in diameter was sealed in a tip and positioned opposite the outlet of a capillary. The experiments indicated that the preparation method was simple, and the obtained electrode exhibited good flexibility and stability for the determination of phenolic antioxidants. The separation was carried out within 5 min using a 50 cm length capillary, with a solution containing 5 mM phosphate and 5 mM borax of pH 8.84 as a separation buffer, and a separation potential of 20 kV. Amperometric detection was achieved with an applied potential of 0.70 V versus Ag|AgCl| saturated KCl. There was excellent linearity between the peak current and the concentrations of the analytes in the range of 1.8 - 180.2 microg/mL for BHA and 10.6 - 212.2 microg/mL for PG, respectively. Relative standard deviations of 4.92% for BHA and 5.27% for PG were obtained, respectively. The developed method was successfully applied for the determination of antioxidants in several commercial foods.

Analysis of ultraviolet absorption spectrum of Chinese herbal medicine-Cortex Fraxini by double ANN

A fast, accurate and convenient method for the simultaneous determination of multi-component in the Chinese herbal medicine was proposed by using ultraviolet absorption spectrum. In this method, dummy components were added to training sample, and a double artificial neural network (DANN) that has the function of high self-revision and self-simulation was used. Effect of other interference components could be eliminated by adjusting concentration of dummy components. Therefore, the accuracy of concentration prediction for multi-component in the complicated Chinese herbal medicine was improved. It has been realized that two effective components of Cortex Fraxini, aesculin and aesculetin, were simultaneously determined, without any separation. The predicted accuracy was 92% within the permitted relative errors. The measurement precisions of the aesculin and aesculetin were 0.37% and 1.5%, respectively.

A study of molecular complex formation between propyl gallate and ascorbic acid in the microemulsion phase of sodium dodecyl sulfate, pentanol and water system

The association between two water-soluble antioxidants, i.e. ascorbic acid and propyl gallate have been studied by absorption spectroscopy in microemulsion formed in sodium dodecyl sulfate/pentanol/water micellar system. It has been shown that propyl gallate forms 1:1 molecular complex with ascorbic acid in every solution. Evolution of the absorption spectra during the study of molecular complex formation goes through well-defined isosbestic points. The association constants were calculated using curve-fitting procedure. The observed interactions are stronger in the less polar solvents.

Simultaneous Determination of Aniline and Cyclohexylamine by Principal Component Artificial Neural Networks

A specterophotometric method for simultaneous determination of aniline and cyclohexylamine using principal component artificial neural networks is proposed. This method is based on the reactions involving aniline and/or cyclohexylamine, with bis(acetylacetoneethylendiamine)tributylphosphine cobalt(III) perchlorate as a complexing reagent. A nonionic surfactant, Triton X-100, was used for dissolving the complexes and intensifying the signals. The absorption data were based on the spectra registered in the range of 350 - 550 nm. An artificial neural network consisting of three layers of nodes was trained by applying a back-propagation learning rule. Sigmoid transfer functions were used in the hidden and output layers to facilitate nonlinear calibration. The predictive ability of artificial neural networks was examined for the determination of aniline and cyclohexylamine in synthetic mixtures.