Aroma Detection of Beef and Pork using Electronic Nose Based on MQ3 and MQ5 Sensors

Abstract

The unstable availability and trading system of beef has resulted in many acts of pork adulteration by irresponsible parties. This action disadvantages consumers, especially Muslim consumers. Based on this, a rapid detection method for aroma identification is needed. The rapid aroma detection in this research uses an electronic nose based on MQ3 and MQ5 sensors with Arduino Mega as a microcontroller. Digital data displayed using Cool Term software is processed using Microsoft Excel and analyzed descriptively. The sensing process uses beef and pork with a temperature of 40 to 120 ^oC at every 10 ^oC increase. Based on the results, the optimum sensing temperature to differentiate beef and pork is at 70 ^oC. The sensor response pattern and beef and pork flavor print showed significant differences. Using PCA analysis with a total score plot of 100% shows that the electronic nose based on MQ3 and MQ5 sensors can detect differences in the aroma of beef and pork.