Abstract: In order to identify alcohol-free beer and ordinary beer quickly and accurately,a recognition model of the alcohol-free beer was established,which was based on fluorescent spectroscopy and probabilistic neural network.It was found experimentally that both alcohol-free beer and ordinary beer excited by ultraviolet-visible light could generate strong fluorescence. The fluorescent spectrum for alcohol-free beer is within a range from 420nm to 620nm,its peak wavelength of the fluorescence is about 490nm.The approximate coefficients,obtained by wavelet transform,were used as the network data,and a probabilistic neural network was trained and constructed.The trained probabilistic neural network was employed to recognize sixty beer samples,and the recognition rate was up to 98.33%.The whole research outcomes will provide a new method for recognizing alcohol-free beer.