Performance of electronic nose based on gas sensor-partition column for synthetic flavor classification

Electronic nose (e-nose) has been developed and implemented in a wide area, included in food industries. This study was conducted to investigate the performance of an e-nose that utilizes a packed gas chromatography column and a gas sensor for classification of synthetic flavor products. There were...

Full description

Saved in:
Bibliographic Details
Main Authors: Radi, Radi, Putro, Joko Purwo Leksono Yuroto, Adhityamurti, Muhammad Danu, Barokah, Barokah, Zamzami, Luthfi Fadillah, Setiawan, Andi
Format: Article PeerReviewed
Language:English
Published: Universitas Ahmad Dahlan 2022
Subjects:
Online Access:https://repository.ugm.ac.id/282753/1/22358-64122-1-PB.pdf
https://repository.ugm.ac.id/282753/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136522420&doi=10.12928%2fTELKOMNIKA.v20i5.22358&partnerID=40&md5=f795f45a592aba7e7b97d7147a811f8e
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universitas Gadjah Mada
Language: English
id id-ugm-repo.282753
record_format dspace
spelling id-ugm-repo.2827532024-01-02T03:36:01Z https://repository.ugm.ac.id/282753/ Performance of electronic nose based on gas sensor-partition column for synthetic flavor classification Radi, Radi Putro, Joko Purwo Leksono Yuroto Adhityamurti, Muhammad Danu Barokah, Barokah Zamzami, Luthfi Fadillah Setiawan, Andi Sustainable Agricultural Development Food Engineering Food technology Electronic nose (e-nose) has been developed and implemented in a wide area, included in food industries. This study was conducted to investigate the performance of an e-nose that utilizes a packed gas chromatography column and a gas sensor for classification of synthetic flavor products. There were six aroma variants of synthetic flavor evaluated, namely durian, jackfruit, ambonese banana, melon, orange and lemon. The e-nose was designed with four main parts, namely aroma provider, column and detector room, microcontroller, and data acquisition system. The device was operated automatically at a stable temperature of 60 °C. Collected data consisted of ten data of each sample was preprocessed by baseline equalization and normalization, extracted its distinctive feature and then were analyzed through pattern recognition analysis. There were two kinds of methods used to analyzed the patterns of the data, namely a fuzzy c-means clustering and an artificial neural network (ANN). With the fuzzy c-means clustering, the result was six data clusters with an unbalanced number of members, indicated that this analysis could not classify samples properly. Meanwhile, analysis with the ANN could classify properly the samples with the level of accuracy of 70. © This is an open access article under the CC BY-SA license. Universitas Ahmad Dahlan 2022-10-05 Article PeerReviewed application/pdf en https://repository.ugm.ac.id/282753/1/22358-64122-1-PB.pdf Radi, Radi and Putro, Joko Purwo Leksono Yuroto and Adhityamurti, Muhammad Danu and Barokah, Barokah and Zamzami, Luthfi Fadillah and Setiawan, Andi (2022) Performance of electronic nose based on gas sensor-partition column for synthetic flavor classification. Telkomnika (Telecommunication Computing Electronics and Control), 20 (5). pp. 1146-1158. ISSN 16936930 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136522420&doi=10.12928%2fTELKOMNIKA.v20i5.22358&partnerID=40&md5=f795f45a592aba7e7b97d7147a811f8e 10.12928/TELKOMNIKA.v20i5.22358
institution Universitas Gadjah Mada
building UGM Library
continent Asia
country Indonesia
Indonesia
content_provider UGM Library
collection Repository Civitas UGM
language English
topic Sustainable Agricultural Development
Food Engineering
Food technology
spellingShingle Sustainable Agricultural Development
Food Engineering
Food technology
Radi, Radi
Putro, Joko Purwo Leksono Yuroto
Adhityamurti, Muhammad Danu
Barokah, Barokah
Zamzami, Luthfi Fadillah
Setiawan, Andi
Performance of electronic nose based on gas sensor-partition column for synthetic flavor classification
description Electronic nose (e-nose) has been developed and implemented in a wide area, included in food industries. This study was conducted to investigate the performance of an e-nose that utilizes a packed gas chromatography column and a gas sensor for classification of synthetic flavor products. There were six aroma variants of synthetic flavor evaluated, namely durian, jackfruit, ambonese banana, melon, orange and lemon. The e-nose was designed with four main parts, namely aroma provider, column and detector room, microcontroller, and data acquisition system. The device was operated automatically at a stable temperature of 60 °C. Collected data consisted of ten data of each sample was preprocessed by baseline equalization and normalization, extracted its distinctive feature and then were analyzed through pattern recognition analysis. There were two kinds of methods used to analyzed the patterns of the data, namely a fuzzy c-means clustering and an artificial neural network (ANN). With the fuzzy c-means clustering, the result was six data clusters with an unbalanced number of members, indicated that this analysis could not classify samples properly. Meanwhile, analysis with the ANN could classify properly the samples with the level of accuracy of 70. © This is an open access article under the CC BY-SA license.
format Article
PeerReviewed
author Radi, Radi
Putro, Joko Purwo Leksono Yuroto
Adhityamurti, Muhammad Danu
Barokah, Barokah
Zamzami, Luthfi Fadillah
Setiawan, Andi
author_facet Radi, Radi
Putro, Joko Purwo Leksono Yuroto
Adhityamurti, Muhammad Danu
Barokah, Barokah
Zamzami, Luthfi Fadillah
Setiawan, Andi
author_sort Radi, Radi
title Performance of electronic nose based on gas sensor-partition column for synthetic flavor classification
title_short Performance of electronic nose based on gas sensor-partition column for synthetic flavor classification
title_full Performance of electronic nose based on gas sensor-partition column for synthetic flavor classification
title_fullStr Performance of electronic nose based on gas sensor-partition column for synthetic flavor classification
title_full_unstemmed Performance of electronic nose based on gas sensor-partition column for synthetic flavor classification
title_sort performance of electronic nose based on gas sensor-partition column for synthetic flavor classification
publisher Universitas Ahmad Dahlan
publishDate 2022
url https://repository.ugm.ac.id/282753/1/22358-64122-1-PB.pdf
https://repository.ugm.ac.id/282753/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136522420&doi=10.12928%2fTELKOMNIKA.v20i5.22358&partnerID=40&md5=f795f45a592aba7e7b97d7147a811f8e
_version_ 1787137339852587008