Electronic Nose for Analysis of Coffee Beans Obtained from Different Altitudes and Origin

Abstract

The coffee industry is facing increasing challenges due to climate change, pests, diseases, which leads to the reduced production and negative impact on coffee qualities. Thus, quality assurance of coffee from production to roasting and brewing becomes more important, especially coffee flavor and aroma. This research aims to study the applicability of electronic nose (e-nose) and algorithm to detect coffee aroma obtained from different origins. The coffee beans used in this experiment were obtained from different areas in northern Thailand. These coffee beans have different growing conditions, altitude, processing and roasting condition. In this study, the three aspects of e-nose were investigated; (i) e-nose sensitivity to coffee odors, (ii) e-nose capability of correctly recognizing the detected odors and (iii) factors that influence coffee odors such as altitude, processing and roasting conditions. The e-nose system comprises of eight metal oxide semiconductor (MOX) gas sensors and in-house developed analysis software. Principal Component Analysis (PCA) is a classification algorithm for pattern recognition of different coffee aroma. Based on experimental results, the e-nose technology shows a capability to detect and distinguish the coffee odors caused by different altitude, processing and roasting process. E-nose is a suitable method for aroma detection in coffee industry to enhance the quality.