Correlation Analysis between Sensors for Sensing Coffee Variations

An electronic nose is a combination of different sensors that are used as a substitute to the human nose in sensing the odor present in a compound. This paper was conducted to identify and correlate different sensors appropriate to be utilized in an electronic nose that is suitable for sensing the aroma of a coffee. Through different trial and error analyses, there are four identified sensors from the MQ family that are best to classify a coffee bean. The identification of the correlation of the different sensors from the MQ family such as MQ 2, MQ 7, MQ 135, and MQ 137 to be applied to different coffee samples was the focus of this paper. The detection of the aroma coming from the variety of Liberica, Excelsa, Robusta, and Arabica coffee was conducted and resulted in 192 gas data. The gas data was extracted based on sensed gas of the signal data sent by the four sensors to the Arduino. The result was identified that the four sensors can be utilized for an electronic nose intended to detect the aroma present in a coffee. This will be of contribution in determining the precise sensors to be associated with each other in discrimination a specific variety of coffee. The achievement of this paper entails a direction that could potentially revolutionized the coffee industry to be more engaging and adaptive to consumer’s preference through the application of electronic nose.