Aroma Discrimination of Local Robusta Coffees Using Gas Sensor Array

Indonesia, the world's third-largest producer of Robusta coffee, still needs to improve its reputation to compete with Arabica coffee, particularly in terms of price. This study reports an effort to characterize local Robusta coffee using a gas sensor array, followed by a statistical analysis that distinguishes several types of Robusta coffee. Dry-processed coffee beans from four coffee-producing locations in Jember Regency were roasted at a medium level and ground at three levels. Coffee fume samples were produced by brewing the coffee powder with boiling water in a chamber. The sensor arrays, used as an e-nose for coffee discrimination, consisted of five gas sensors exposed to the fumes of coffee samples. The recorded sensor's response was normalized and analyzed using PCA and ANN by a lab-made software. The results have shown that using the e-nose as an alternative method for controlling coffee quality is very promising, as differences in aroma can be identified quickly and easily. The ANN's predictive ability was good, though a small proportion of unknown coffees could not be correctly predicted. Predictions on 48 unknown-coffees were found to be 100 % accurate from three locations, while for unknown-coffees from another location, only 42 % were correctly predicted. It also opens the opportunity to introduce some local Robusta coffees based on their area of origin, which have distinctive characteristics, using the e-nose as the initial discriminator before proceeding with the certification process in accordance with the specialty coffee standardization.