Abstract: In order to establish an accurate and rapid method for determination of the main pernicious gases NH3 and H2S in the piggery in South China, an electronic nose system was built. Gas samples were prepared with static volumetric method, and the fast independent component analysis (FICA) and the radial basis function neural networks (RBFNN) were applied to identify H2S gas alone and the mixed gas of H2S and NH3 between the range of 6.95- 69.53 mg/m3. The average identification accuracy of single gas reached 99.1%, while the average identification accuracy of mixed gas was 90.97%. The results show that good effect was obtained by applying FICA and RBFNN methods to quantitative identification of gases NH3 and H2S in piggery based on electronic nose system.