<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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.</p>
</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.

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

Department of Agroindustrial Technology, Faculty of Agricultural Technology

Department of Computer Science and Electronics, Faculty of Mathematics and Natural Sciences

International Journal on Smart Sensing and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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...

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

Article Category: Article

Published Online: Jul 20, 2024

Page range: -

Received: Jun 26, 2023

DOI: https://doi.org/10.2478/ijssis-2024-0019

Keywords
electronic nose, tea dregs aroma, multilayer perceptron, machine learning

© 2024 Adi Djoko Guritno, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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

Article Category: Article

Published Online: Jul 20, 2024

Page range: -

Received: Jun 26, 2023

DOI: https://doi.org/10.2478/ijssis-2024-0019

Keywordselectronic nose, tea dregs aroma, multilayer perceptron, machine learning

© 2024 Adi Djoko Guritno, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Keywords
electronic nose, tea dregs aroma, multilayer perceptron, machine learning