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 | Acesso ao texto completo restrito à biblioteca da Embrapa Gado de Leite. Para informações adicionais entre em contato com cnpgl.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Gado de Leite; Embrapa Instrumentação. |
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Data corrente: |
28/09/2022 |
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Data da última atualização: |
28/09/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
COATRINI-SOARES, A.; COATRINI-SOARES, J.; POPOLIN NETO, M.; MELLO, S. S. de; PINTO, D. S. C.; CARVALHO, W. A.; GILMORE, M. S.; PIAZZETTA, M. H. O.; GOBBI, A. L.; BRANDÃO, H. M.; PAULOVICH, F. V.; OLIVEIRA JR, O. N.; MATTOSO, L. H. C. |
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Afiliação: |
LUIZ HENRIQUE CAPPARELLI MATTOSO, CNPDIA. |
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Título: |
Microfluidic E-tongue to diagnose bovine mastitis with milk samples using machine learning with decision tree models. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Chemical Engineering Journal, v. 451, e138523, 2022. |
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Páginas: |
1 - 9 |
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ISSN: |
1385-8947 |
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DOI: |
https://doi.org/10.1016/j.cej.2022.138523 |
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Idioma: |
Inglês |
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Conteúdo: |
We report an electronic tongue based on impedance spectroscopy to detect Staphylococcus aureus and diagnose bovine mastitis in milk samples. This was achieved with optimized sensing units made with layer-by-layer films and by treating the capacitance data with machine learning algorithms employing decision trees models. These films were made with chitosan, chondroitin sulfate, sericin and gold nanoparticles /sericin, whose molecularlevel interaction with S.aureus depended on the architecture according to PM-IRRAS measurements. The limit of detection in blank milk varied from 3.41 to 2.01 CFU/mL depending on the sensing unit. This sensitivity was complemented with the selectivity provided by combining the electrical responses of the four sensing units. Indeed, with machine learning it was possible to determine multidimensional calibration spaces (MCS) that could generate rules to explain how the milk samples could be discriminated. With a 7-dimension MCS, distinct S. aureus concentrations could be distinguished from possible interferents with a 100 % accuracy. In crude milk samples, 94 % accuracy was obtained with a 6-dimension MCS in multiclass classification for milk from different udders of a mastitis infected cow, including samples diluted 50-fold, in addition to milk from an infected cow treated with Bronopol and from a healthy cow. It is significant that in a ternary classification with these crude milk samples, a 2-dimension MCS could distinguish between milk from an infected cow, treated with Bronopol and from a healthy cow with 100 % accuracy. The combination of electronic tongues and machine learning ? as in this proof-of-concept study - is promising for diagnosis of mastitis at a low cost. MenosWe report an electronic tongue based on impedance spectroscopy to detect Staphylococcus aureus and diagnose bovine mastitis in milk samples. This was achieved with optimized sensing units made with layer-by-layer films and by treating the capacitance data with machine learning algorithms employing decision trees models. These films were made with chitosan, chondroitin sulfate, sericin and gold nanoparticles /sericin, whose molecularlevel interaction with S.aureus depended on the architecture according to PM-IRRAS measurements. The limit of detection in blank milk varied from 3.41 to 2.01 CFU/mL depending on the sensing unit. This sensitivity was complemented with the selectivity provided by combining the electrical responses of the four sensing units. Indeed, with machine learning it was possible to determine multidimensional calibration spaces (MCS) that could generate rules to explain how the milk samples could be discriminated. With a 7-dimension MCS, distinct S. aureus concentrations could be distinguished from possible interferents with a 100 % accuracy. In crude milk samples, 94 % accuracy was obtained with a 6-dimension MCS in multiclass classification for milk from different udders of a mastitis infected cow, including samples diluted 50-fold, in addition to milk from an infected cow treated with Bronopol and from a healthy cow. It is significant that in a ternary classification with these crude milk samples, a 2-dimension MCS could distinguish between milk from an i... Mostrar Tudo |
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Palavras-Chave: |
Impedance spectroscopy; Machine learning; Mastite; Multidimensional calibration space; S aureus; Sensors. |
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Thesagro: |
Bovino; Doença Animal; Gado Leiteiro. |
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Categoria do assunto: |
--
L Ciência Animal e Produtos de Origem Animal |
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Marc: |
LEADER 02936naa a2200409 a 4500
001 2146958
005 2022-09-28
008 2022 bl uuuu u00u1 u #d
022 $a1385-8947
024 7 $ahttps://doi.org/10.1016/j.cej.2022.138523$2DOI
100 1 $aCOATRINI-SOARES, A.
245 $aMicrofluidic E-tongue to diagnose bovine mastitis with milk samples using machine learning with decision tree models.$h[electronic resource]
260 $c2022
300 $a1 - 9
520 $aWe report an electronic tongue based on impedance spectroscopy to detect Staphylococcus aureus and diagnose bovine mastitis in milk samples. This was achieved with optimized sensing units made with layer-by-layer films and by treating the capacitance data with machine learning algorithms employing decision trees models. These films were made with chitosan, chondroitin sulfate, sericin and gold nanoparticles /sericin, whose molecularlevel interaction with S.aureus depended on the architecture according to PM-IRRAS measurements. The limit of detection in blank milk varied from 3.41 to 2.01 CFU/mL depending on the sensing unit. This sensitivity was complemented with the selectivity provided by combining the electrical responses of the four sensing units. Indeed, with machine learning it was possible to determine multidimensional calibration spaces (MCS) that could generate rules to explain how the milk samples could be discriminated. With a 7-dimension MCS, distinct S. aureus concentrations could be distinguished from possible interferents with a 100 % accuracy. In crude milk samples, 94 % accuracy was obtained with a 6-dimension MCS in multiclass classification for milk from different udders of a mastitis infected cow, including samples diluted 50-fold, in addition to milk from an infected cow treated with Bronopol and from a healthy cow. It is significant that in a ternary classification with these crude milk samples, a 2-dimension MCS could distinguish between milk from an infected cow, treated with Bronopol and from a healthy cow with 100 % accuracy. The combination of electronic tongues and machine learning ? as in this proof-of-concept study - is promising for diagnosis of mastitis at a low cost.
650 $aBovino
650 $aDoença Animal
650 $aGado Leiteiro
653 $aImpedance spectroscopy
653 $aMachine learning
653 $aMastite
653 $aMultidimensional calibration space
653 $aS aureus
653 $aSensors
700 1 $aCOATRINI-SOARES, J.
700 1 $aPOPOLIN NETO, M.
700 1 $aMELLO, S. S. de
700 1 $aPINTO, D. S. C.
700 1 $aCARVALHO, W. A.
700 1 $aGILMORE, M. S.
700 1 $aPIAZZETTA, M. H. O.
700 1 $aGOBBI, A. L.
700 1 $aBRANDÃO, H. M.
700 1 $aPAULOVICH, F. V.
700 1 $aOLIVEIRA JR, O. N.
700 1 $aMATTOSO, L. H. C.
773 $tChemical Engineering Journal$gv. 451, e138523, 2022.
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Registro original: |
Embrapa Instrumentação (CNPDIA) |
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| Acesso ao texto completo restrito à biblioteca da Embrapa Recursos Genéticos e Biotecnologia. Para informações adicionais entre em contato com cenargen.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Recursos Genéticos e Biotecnologia. |
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Data corrente: |
10/08/2017 |
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Data da última atualização: |
13/06/2024 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 2 |
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Autoria: |
OLIVEIRA, R. A. de; TEIXEIRA, A. B. S.; PIGNATARO, T. A.; FREITAS, M. L.; TEIXEIRA, H. C. A.; CARVALHO, J. de O.; DODE, M. A. N.; PIVATO, I.; BUDIK, S. |
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Afiliação: |
RODRIGO ARRUDA DE OLIVEIRA, UNB; ALINE BATISTA SILVA TEIXEIRA, UNB; TATIANA ALMEIDA PIGNATARO, UNB; MARIANE LEÃO FREITAS, UNB; HEITOR CASTRO ALVES TEIXEIRA, UNB; JOSÉ DE OLIVEIRA CARVALHO; MARGOT ALVES NUNES DODE, CENARGEN; IVO PIVATO, UNB; SVEN BUDIK, VETERINARY UNIVERSITY VIENNA, AUSTRIA. |
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Título: |
Evaluation of hypo-osmotic swelling test and supra vital staining technique as indicators for donkey semen freezability. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
Pferdeheilkunde, v. 33, n. 2, p. 159-164, 2017. |
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DOI: |
10.21836/PEM20170208 |
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Idioma: |
Inglês |
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Palavras-Chave: |
Eosin-nigrosin; Plasma membrane integrity. |
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Thesagro: |
Equus Asinus; Sêmen. |
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Thesaurus NAL: |
Cryopreservation; Reproduction. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 00884naa a2200289 a 4500
001 2073857
005 2024-06-13
008 2017 bl uuuu u00u1 u #d
024 7 $a10.21836/PEM20170208$2DOI
100 1 $aOLIVEIRA, R. A. de
245 $aEvaluation of hypo-osmotic swelling test and supra vital staining technique as indicators for donkey semen freezability.$h[electronic resource]
260 $c2017
650 $aCryopreservation
650 $aReproduction
650 $aEquus Asinus
650 $aSêmen
653 $aEosin-nigrosin
653 $aPlasma membrane integrity
700 1 $aTEIXEIRA, A. B. S.
700 1 $aPIGNATARO, T. A.
700 1 $aFREITAS, M. L.
700 1 $aTEIXEIRA, H. C. A.
700 1 $aCARVALHO, J. de O.
700 1 $aDODE, M. A. N.
700 1 $aPIVATO, I.
700 1 $aBUDIK, S.
773 $tPferdeheilkunde$gv. 33, n. 2, p. 159-164, 2017.
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Embrapa Recursos Genéticos e Biotecnologia (CENARGEN) |
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