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Classification of Coffee Variety using Electronic Nose

There are numerous studies arising from utilizing an electronic nose as an alternative way to the human nose in sensing an odor. In this study, an electronic nose will be employed in distinguishing the variety of coffee based on the four commercially produced coffee such as Arabica, Robusta, Excelsa, and Liberica. The sensors equipped in the electronic nose were from the MQ family such as MQ 2, MQ 7, MQ 135, and MQ 137, the four sensors also underwent the analysis of correlation to better justify its implementation to the electronic nose. The detection of the aroma coming from the four varieties of coffee was conducted through the designed process of collecting aroma and resulted in 192 gas data. The gas data were extracted based on sensed gas of the signal data sent by the four sensors to the Arduino. Using the Gaussian Naïve Bayes algorithm, the classification resulted in an accuracy rate of 100%. In conclusion, the results of this study have discovered that the electronic nose sensing technique could be used as an effective method to classify coffee variety.