Simultaneous determination of three antibiotics based on synchronous fluorescence combined with neural network

In order to determine the antibiotic mixture more quickly, conveniently and accurately at the same time, synchronous fluorescence spectra of 3 kinds of fluoroquinolones (ciprofloxacin, levofloxacin lactate, levofloxacin hydrochloride) were studied based on synchronous fluorescence spectroscopy combined with radial basis function neural network. The 3-D synchronous fluorescence spectrum for the 3-component mixed solution with concentration of 1.67ng/mL was measured. Then, simultaneous fluorescence spectra of 39 mixed solutions with different concentrations were measured. 35 of them were selected as the training group, and the other 4 were used as the prediction group. The spectral data corresponding to the training samples were taken as input to build and train the radial basis function neural network. The results show that, when Δλ=194nm, the concentration of each component in the prediction group is predicted by the trained neural network. The average relative errors of intensity prediction of 3 components were 3.59%, 3.47% and 3.09%, respectively. The method provides rapid, simple and accurate method for simultaneous determination of multiple antibiotic mixtures.