Electronic nose method for classification of coffee, in comparison with laboratory instrument and sensory test

Electronic nose (EN) is a usefully device for quality evaluation in the secondary coffee processing, especially for recognition of coffee aroma. However, complexity of coffee volatile compounds influences its performance. This study aimed to design an EN and investigate its performance for classifying of coffee. The EN was designed with eight MOS sensors integrated with corresponding analysis software to classify six coffee samples consisting of three kinds of Arabica and three kinds of Robusta. All samples were prepared with same treatment. Each sample was prepared as ground coffee, and then it was poured inside a chamber. Volatile compounds were allowed to vaporize, then mixed with oxygen and exposed at a constant flow speed to the EN. For this experiment, analysis was focused on the sensor array response to the presented sample. The sensor signals were recorded and presented into aroma patterns, then they were analyzed with principle component analysis (PCA). The aroma pattern distribution viewed on the PCA scatter was then compared to the common analysis methods, namely sensory test and high performance liquid chromatography-photodiode array (HPLC-PDA) analysis. The results showed that roasting degree influenced on the sensor array signal, aroma patterns of dark roasted coffee tend to generate a diffuse distribution, while aroma patterns of light, both coffees were classified. The result is suitable to the two methods, either sensory test or HPLC-PDA analysis. Both also generated the distinguished data only for light degree. The result showed that the EN can be developed for further coffee recognition at secondary coffee processing.