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Electronic nose dataset for beef quality monitoring in uncontrolled ambient conditions

In recent years, the development of a rapid, simple, and low-cost meat assessment system using an electronic nose (e-nose) has been the concern of researchers. In this data article, we provide a time series dataset that was obtained from a beef quality monitoring experiment using an e-nose in uncont...

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Detalles Bibliográficos
Autores principales: Wijaya, Dedy Rahman, Sarno, Riyanarto, Zulaika, Enny
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6282642/
https://www.ncbi.nlm.nih.gov/pubmed/30547068
http://dx.doi.org/10.1016/j.dib.2018.11.091
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author Wijaya, Dedy Rahman
Sarno, Riyanarto
Zulaika, Enny
author_facet Wijaya, Dedy Rahman
Sarno, Riyanarto
Zulaika, Enny
author_sort Wijaya, Dedy Rahman
collection PubMed
description In recent years, the development of a rapid, simple, and low-cost meat assessment system using an electronic nose (e-nose) has been the concern of researchers. In this data article, we provide a time series dataset that was obtained from a beef quality monitoring experiment using an e-nose in uncontrolled ambient conditions. The availability of this dataset will enable discussion on how to deal with noisy e-nose signals and non-optimum sensor array in beef quality monitoring. Hence, the development of proper signal processing and robust machine learning algorithm are several challenges that must be faced. Furthermore, this dataset can also be useful as a comparison dataset for similar e-nose applications, such as air quality monitoring, smart packaging system, and food quality monitoring.
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spelling pubmed-62826422018-12-13 Electronic nose dataset for beef quality monitoring in uncontrolled ambient conditions Wijaya, Dedy Rahman Sarno, Riyanarto Zulaika, Enny Data Brief Computer Science In recent years, the development of a rapid, simple, and low-cost meat assessment system using an electronic nose (e-nose) has been the concern of researchers. In this data article, we provide a time series dataset that was obtained from a beef quality monitoring experiment using an e-nose in uncontrolled ambient conditions. The availability of this dataset will enable discussion on how to deal with noisy e-nose signals and non-optimum sensor array in beef quality monitoring. Hence, the development of proper signal processing and robust machine learning algorithm are several challenges that must be faced. Furthermore, this dataset can also be useful as a comparison dataset for similar e-nose applications, such as air quality monitoring, smart packaging system, and food quality monitoring. Elsevier 2018-11-22 /pmc/articles/PMC6282642/ /pubmed/30547068 http://dx.doi.org/10.1016/j.dib.2018.11.091 Text en © 2018 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Computer Science
Wijaya, Dedy Rahman
Sarno, Riyanarto
Zulaika, Enny
Electronic nose dataset for beef quality monitoring in uncontrolled ambient conditions
title Electronic nose dataset for beef quality monitoring in uncontrolled ambient conditions
title_full Electronic nose dataset for beef quality monitoring in uncontrolled ambient conditions
title_fullStr Electronic nose dataset for beef quality monitoring in uncontrolled ambient conditions
title_full_unstemmed Electronic nose dataset for beef quality monitoring in uncontrolled ambient conditions
title_short Electronic nose dataset for beef quality monitoring in uncontrolled ambient conditions
title_sort electronic nose dataset for beef quality monitoring in uncontrolled ambient conditions
topic Computer Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6282642/
https://www.ncbi.nlm.nih.gov/pubmed/30547068
http://dx.doi.org/10.1016/j.dib.2018.11.091
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