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In the past few decades, electronic nose technologies have been increasingly implemented for environmental monitoring. This research aims to develop a portable instrument to measure and monitor the presence of sulphate-reducing bacteria (SRB) using the artificial olfactory system. The unchecked growth of SRB in anaerobic environments causes severe microbiological corrosion problems. Conventional methods or detection kits currently available in the market for SRB detection are very time-consuming to use and are thus inefficient for field use. The electronic nose system comprises an array of metal-oxide semiconductor sensors, a data processing unit, and an artificial neural network (ANN) pattern recognition unit. This paper presents the hardware and software design of a data acquisition system for the development of an electronic nose using field programmable gate array (FPGA) as the data processing unit. The data acquisition system is successfully designed and tested. Data collected from assessment experiments show that the oxidation-reduction reaction attributed to the presence of SRB leaves an obvious pattern on the outputs of the sensor within three hours. The characteristics observed and data collected from experiments are used to configure the recognition system for the implementation of automated identification in the future.