A lab-made e-nose-MOS device for assessing the bacterial growth in a solid culture medium
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10198/9307 |
Resumo: | The detection and level assessment of microorganisms is a practical quality/contamination indicator of food and water samples. Conventional analytical procedures (e.g., culture methods, immunological techniques, and polymerase chain reactions), while accurate and widely used, are time-consuming, costly, and generate a large amount of waste. Electronic noses (E-noses), combined with chemometrics, provide a direct, green, and non-invasive assessment of the volatile fraction without the need for sample pre-treatments. The unique olfactory fingerprint generated during each microorganism’s growth can be a vehicle for its detection using gas sensors. A lab-made E-nose, comprising metal oxide semiconductor sensors was applied, to analyze solid medium containing Gram-positive (Enterococcus faecalis and Staphylococcus aureus) or Gram-negative (Escherichia coli and Pseudomonas aeruginosa) bacteria. The electrical-resistance signals generated by the E-nose coupled with linear discriminant analysis allowed the discrimination of the four bacteria (90% of correct classifications for leave-one-out cross-validation). Furthermore, multiple linear regression models were also established allowing quantifying the number of colony-forming units (CFU) (0.9428 ≤ R2 ≤ 0.9946), with maximum root mean square errors lower than 4 CFU. Overall, the E-nose showed to be a powerful qualitative–quantitative device for bacteria preliminary analysis, being envisaged its possible application in solid food matrices. |
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A lab-made e-nose-MOS device for assessing the bacterial growth in a solid culture mediumElectronic noseMetal oxide semiconductor sensorsBacteria identificationGram-positiveGram-negativeColony-forming unitsLinear discriminant analysisMultiple linear regression modelsSimulated annealing algorithmThe detection and level assessment of microorganisms is a practical quality/contamination indicator of food and water samples. Conventional analytical procedures (e.g., culture methods, immunological techniques, and polymerase chain reactions), while accurate and widely used, are time-consuming, costly, and generate a large amount of waste. Electronic noses (E-noses), combined with chemometrics, provide a direct, green, and non-invasive assessment of the volatile fraction without the need for sample pre-treatments. The unique olfactory fingerprint generated during each microorganism’s growth can be a vehicle for its detection using gas sensors. A lab-made E-nose, comprising metal oxide semiconductor sensors was applied, to analyze solid medium containing Gram-positive (Enterococcus faecalis and Staphylococcus aureus) or Gram-negative (Escherichia coli and Pseudomonas aeruginosa) bacteria. The electrical-resistance signals generated by the E-nose coupled with linear discriminant analysis allowed the discrimination of the four bacteria (90% of correct classifications for leave-one-out cross-validation). Furthermore, multiple linear regression models were also established allowing quantifying the number of colony-forming units (CFU) (0.9428 ≤ R2 ≤ 0.9946), with maximum root mean square errors lower than 4 CFU. Overall, the E-nose showed to be a powerful qualitative–quantitative device for bacteria preliminary analysis, being envisaged its possible application in solid food matrices.MDPIBiblioteca Digital do IPBDias, TeresaSantos, Vitor S.Zorgani, TarekFerreiro, Nuno ManuelRodrigues, Ana IsabelZaghdoudi, KhalilVeloso, Ana C.A.Peres, António M.2014-02-12T13:10:57Z20232023-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10198/9307engDias, Teresa; Santos, Vitor S.; Zorgani, Tarek; Ferreiro, Nuno Manuel; Rodrigues, Ana Isabel; Zaghdoudi, Khalil; Veloso, Ana C.A.; Peres, António M.. (2023). A lab-made e-nose-MOS device for assessing the bacterial growth in a solid culture medium. Biosensors. eISSN 2079-6374. 13:1, p. 1-1310.3390/bios130100192079-6374info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-07T01:17:58Zoai:bibliotecadigital.ipb.pt:10198/9307Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:00:35.998605Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
A lab-made e-nose-MOS device for assessing the bacterial growth in a solid culture medium |
title |
A lab-made e-nose-MOS device for assessing the bacterial growth in a solid culture medium |
spellingShingle |
A lab-made e-nose-MOS device for assessing the bacterial growth in a solid culture medium Dias, Teresa Electronic nose Metal oxide semiconductor sensors Bacteria identification Gram-positive Gram-negative Colony-forming units Linear discriminant analysis Multiple linear regression models Simulated annealing algorithm |
title_short |
A lab-made e-nose-MOS device for assessing the bacterial growth in a solid culture medium |
title_full |
A lab-made e-nose-MOS device for assessing the bacterial growth in a solid culture medium |
title_fullStr |
A lab-made e-nose-MOS device for assessing the bacterial growth in a solid culture medium |
title_full_unstemmed |
A lab-made e-nose-MOS device for assessing the bacterial growth in a solid culture medium |
title_sort |
A lab-made e-nose-MOS device for assessing the bacterial growth in a solid culture medium |
author |
Dias, Teresa |
author_facet |
Dias, Teresa Santos, Vitor S. Zorgani, Tarek Ferreiro, Nuno Manuel Rodrigues, Ana Isabel Zaghdoudi, Khalil Veloso, Ana C.A. Peres, António M. |
author_role |
author |
author2 |
Santos, Vitor S. Zorgani, Tarek Ferreiro, Nuno Manuel Rodrigues, Ana Isabel Zaghdoudi, Khalil Veloso, Ana C.A. Peres, António M. |
author2_role |
author author author author author author author |
dc.contributor.none.fl_str_mv |
Biblioteca Digital do IPB |
dc.contributor.author.fl_str_mv |
Dias, Teresa Santos, Vitor S. Zorgani, Tarek Ferreiro, Nuno Manuel Rodrigues, Ana Isabel Zaghdoudi, Khalil Veloso, Ana C.A. Peres, António M. |
dc.subject.por.fl_str_mv |
Electronic nose Metal oxide semiconductor sensors Bacteria identification Gram-positive Gram-negative Colony-forming units Linear discriminant analysis Multiple linear regression models Simulated annealing algorithm |
topic |
Electronic nose Metal oxide semiconductor sensors Bacteria identification Gram-positive Gram-negative Colony-forming units Linear discriminant analysis Multiple linear regression models Simulated annealing algorithm |
description |
The detection and level assessment of microorganisms is a practical quality/contamination indicator of food and water samples. Conventional analytical procedures (e.g., culture methods, immunological techniques, and polymerase chain reactions), while accurate and widely used, are time-consuming, costly, and generate a large amount of waste. Electronic noses (E-noses), combined with chemometrics, provide a direct, green, and non-invasive assessment of the volatile fraction without the need for sample pre-treatments. The unique olfactory fingerprint generated during each microorganism’s growth can be a vehicle for its detection using gas sensors. A lab-made E-nose, comprising metal oxide semiconductor sensors was applied, to analyze solid medium containing Gram-positive (Enterococcus faecalis and Staphylococcus aureus) or Gram-negative (Escherichia coli and Pseudomonas aeruginosa) bacteria. The electrical-resistance signals generated by the E-nose coupled with linear discriminant analysis allowed the discrimination of the four bacteria (90% of correct classifications for leave-one-out cross-validation). Furthermore, multiple linear regression models were also established allowing quantifying the number of colony-forming units (CFU) (0.9428 ≤ R2 ≤ 0.9946), with maximum root mean square errors lower than 4 CFU. Overall, the E-nose showed to be a powerful qualitative–quantitative device for bacteria preliminary analysis, being envisaged its possible application in solid food matrices. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-02-12T13:10:57Z 2023 2023-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10198/9307 |
url |
http://hdl.handle.net/10198/9307 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Dias, Teresa; Santos, Vitor S.; Zorgani, Tarek; Ferreiro, Nuno Manuel; Rodrigues, Ana Isabel; Zaghdoudi, Khalil; Veloso, Ana C.A.; Peres, António M.. (2023). A lab-made e-nose-MOS device for assessing the bacterial growth in a solid culture medium. Biosensors. eISSN 2079-6374. 13:1, p. 1-13 10.3390/bios13010019 2079-6374 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
MDPI |
publisher.none.fl_str_mv |
MDPI |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799135234478833664 |