Implementation of an electronic nose for classification of synthetic flavors

Radi Radi, Barokah Barokah, Dwi Noor Rohmah, Eka Wahyudi, Muhammad Danu Adhityamurti, Joko Purwo Leksono Yuroto Putro

Abstract


Electronic nose (e-nose) is an instrument designed to mimic the working principles of the biological olfactory system of humans or animals. E-nose is needed in various processs, especially which require the role of sense of smell, including in the food and flavor industry. The aroma of food products is one of the main quality attributes, thus, adding some additional components of flavor are necessary in some case on the food processing to improve aroma and taste. One of these additional substances is synthetic flavor. Therefore, measuring the synthetic flavor including classification and identification has become routine activities in the flavor and food industry. This study aimed to apply an e-nose for classifying of synthetic flavors. For this study, an e-nose was designed with an array of gases sensor as the main sensing component and Principal Component Analysis (PCA) for the pattern recognition software. This research was conducted as follow: preparation of the e-nose, preparation of sample, data collection, and analysis. There were nine samples of synthetic flavor with different aroma, namely: grapes, strawberry, mocha, pandanus, mango, jackfruit, orange, melon, and durian. The data collection process includes three stages, namely flushing 120 s, collecting 180 s, and purging 120 s. These sensor responses were then analyzed for forming aroma patterns of samples. There were four pre-treatment methods applied for aroma pattern formation, i.e: absolute data, normalize of absolute data, relative data, and normalize of relative data. Furthermore, the pre-treatment results in the form of aroma patterns were then further evaluated by using PCA method. The results showed that the absolute data treatment provided the best results as indicated by the distribution of aroma patterns of the samples that were grouped according to the type of sample tested.

Keywords


Aroma pattern; Classification; Electronic nose; Principal component analysis; Synthetic flavor



DOI: https://doi.org/10.11591/eei.v10i3.3018

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