Thus, they are complementary to each other on certain occasions, for example, when used as detectors for liquid chromatography. The data fusion of fluorescence and UV–visible spectroscopies is anticipated to be effective. However, there is little attention paid to such kind of data fusion for food authentication. Herein, we report the chemometric classification of Chinese lager beers according to manufacturer based on the data fusion of fluorescence, UV and visible spectroscopies. The objective of this study is not only to establish a model to differentiate Chinese beer manufacturers, but also to utilize the synergy between different spectroscopies, to show that fluorescence, UV and visible spectroscopies provide complementary information, and to reveal the extent the data fusion can improve the discrimination performance.