Electronic nose for classifying beef and pork using Naïve Bayes

Meat is one of the mainly consumed foods s by human. Hence, a certain degree of standards is required for it to be safely consumed. One of those standards includes the purity of the meat. There have been some cases of adulteration of pork in beef, possible to cause harm for the consumers. Therefore, in this research, we propose an easy to use and low-cost electronic nose system that is capable to determine whether the meat is a beef or pork. The electronic system was made using Arduino microcontroller and sensor array that consisted of eight Metal-Oxide Semiconductor gas sensors. For pattern classification, Naïve Bayes classifier preceded by min-max magnitude scaling was used to classify fresh beef and pork. The experimental result showed that the proposed system could distinguish beef and pork with 75% of classification accuracy based on k-fold cross validation.