Gas sensor array to classify the chicken meat with E. coli contaminant by using random forest and support vector machine

Astuti, Suryani Dyah and Tamimi, Mohammad H. and Pradhana, Anak A.S. and Alamsyah, Kartika A. and Purnobasuki, Hery and Khasanah, Miratul and Susilo, Yunus and Triyana, Kuwat and Kashif, Muhammad and Syahrom, Ardiyansyah (2021) Gas sensor array to classify the chicken meat with E. coli contaminant by using random forest and support vector machine. Biosensors and Bioelectronics: X, 9. ISSN 25901370

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Abstract

Microbes such as Escherichia coli (E. coli) can easily contaminate raw chicken meat in clean conditions, causing decay and unpleasant scents. This study aims to characterize gas patterns by comparing fresh chicken meat and E. coli bacteria contaminated chicken meat based on shelf life using a Gas Sensor Array (GSA) system (MQ2, MQ3, MQ7, MQ8, MQ135, and MQ136) on electronic nose. The findings revealed GSA capability to detect a variety of typical gas patterns formed by the samples. This gas detection property is indicated by the appearance of the variance in the sensors output voltage pattern for each sample variation. The data for fresh and contaminated samples were classified by the random forest (RF) classifier with 99.25 and 98.42 precision, respectively. Furthermore, the support vector machine (SVM) classifier correctly identified the fresh and contaminated samples with 98.61 and 86.66 accuracy, respectively. This finding offers insight for GSA capability in classifying chicken meat contaminated with E. coli using an RF and SVM. © 2021 The Author(s)

Item Type: Article
Additional Information: Cited by: 37; All Open Access, Gold Open Access
Uncontrolled Keywords: Animals; Contamination; Decision trees; Electronic nose; Escherichia coli; Food safety; Food supply; Gas detectors; Gases; Meats; Pollution detection; Chicken meat; Condition; Escherichia coli bacteria; Food security; Gas detection; Gas sensor arrays; Random forests; Sensor array systems; Shelf life; Support vectors machine; Article; artificial neural network; chicken meat; classifier; controlled study; electric potential; Escherichia coli; feature extraction; food contamination; gas; measurement accuracy; measurement precision; nonhuman; random forest; shelf life; support vector machine; Support vector machines
Subjects: Q Science > QC Physics
Divisions: Faculty of Mathematics and Natural Sciences > Physics Department
Depositing User: Sri JUNANDI
Date Deposited: 29 Oct 2024 04:28
Last Modified: 29 Oct 2024 04:28
URI: https://ir.lib.ugm.ac.id/id/eprint/8497

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