Freshness assessment of tilapia fish in traditional market based on an electronic nose

Radi, Radi and Wahyudi, Eka and Adhityamurti, Muhammad Danu and Putro, Joko Purwo Leksono Yuroto and Barokah, Barokah and Rohmah, Dwi Noor (2021) Freshness assessment of tilapia fish in traditional market based on an electronic nose. Bulletin of Electrical Engineering and Informatics, 10 (5). 2466 – 2476. ISSN 20893191

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Abstract

This study evaluates an e-nose based on gas sensors to measure the freshness of tilapia. The device consists of a series of semiconductor sensors as detector, a combination of valve-vial-oxygen as sample delivery system, a microcontroller as interface and controller, and a computer for data recording and processing. The e-nose was firstly used to classify the fresh and non-fresh tilapia. A total of 48 samples of fresh tilapia and 50 samples of non-fresh tilapia were prepared and measured using the e-nose through three stages, namely: flushing, collecting, and purging. The sensor responses were processed into aroma patterns, then classified by two pattern classification softwares of principal component analysis (PCA) and neural network (NN). There were four methods for aroma patterns formation being evaluated: absolute data, normalized absolute data, relative data, normalized relative data. The results showed that the normalized absolute data method provides the best classification with the accuracy level of 93.88. With this method, the trained NN was used to predict the freshness of 15 tilapia samples collected from a traditional market. The result showed that 60.0 of the samples are classified into fresh category, 33.3 are in the non-fresh category, and 6.7 are not included in both categories. © CC BY-SA license.

Item Type: Article
Additional Information: Cited by: 5; All Open Access, Gold Open Access
Uncontrolled Keywords: Ammonia test kit; Aroma pattern; Electronic nose; Freshness level; Neural network; Sensor array; Tilapia
Subjects: Q Science > QC Physics
Divisions: Faculty of Agricultural Technology > Agricultural and Biosystems Engineering
Depositing User: Sri JUNANDI
Date Deposited: 30 Oct 2024 02:03
Last Modified: 30 Oct 2024 02:03
URI: https://ir.lib.ugm.ac.id/id/eprint/8422

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