Development of a portable electronic nose for the classification of tea quality based on tea dregs aroma

Guritno, Adi Djoko and Harjoko, Agus and Tanuputri, Megita Ryanjani and Kusumaning Putri, Dyah Utami (2024) Development of a portable electronic nose for the classification of tea quality based on tea dregs aroma. International Journal on Smart Sensing and Intelligent Systems, 17: 20240019. pp. 1-13. ISSN 11785608

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Abstract

The current assessment of tea quality is considered subjective. This study aims to develop a portable electronic nose to assess the aroma of tea dregs objectively by relying on the aromatic capture process through sensors and using multilayer perceptron (MLP). A MLP with some hyperparameter variations is used and compared with five machine-learning classifiers. The classification using MLP model with ReLU activation function and 3 hidden layers with 100 hidden nodes resulted in the highest accuracy of 0.8750 ± 0.0241. The MLP model using ReLU activation function is better than Sigmoid while increasing the number of hidden layers and hidden nodes does not necessarily enhance its performance. In the future, this research can be improved by adding sensors to the portable electronic nose, increasing the number of datasets used, and using ensemble learning or deep learning models. © 2024 Adi Djoko Guritno, published by Sciendo.

Item Type: Article
Uncontrolled Keywords: electronic nose, tea dregs aroma, multilayer perceptron, machine learning
Subjects: S Agriculture > S Agriculture (General)
Divisions: Faculty of Agricultural Technology > Agro-Industrial Technology
Depositing User: Diah Ari Damayanti
Date Deposited: 03 Sep 2024 07:50
Last Modified: 03 Sep 2024 07:50
URI: https://ir.lib.ugm.ac.id/id/eprint/6146

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