An e-nose system based on near infrared spectral absorption technology which can be used to detect target gases accurately and efficiently was designed and implemented in this paper. The e-nose was composed of near infrared laser emission unit, gas cell unit, system controller unit, and human-machine interface. Principal Component Analysis (PCA) algorithm and Back Propagation (BP) neural network for analyzing the collected date were integrated into the upper computer software by the MATLAB Script node supplied by LabVIEW. The results indicate that the e-nose is stable, and its accuracy is 0.0001, when the time of the networks training reach more than 1 000. The recognition accuracy rate in recognizing the white vinegar, rice vinegar and apple vinegar is 100%, which can achieves the design goal of high-precision, high-stability, high resolution, and behaves good application prospects.