| |
|
|
 | Acesso ao texto completo restrito à biblioteca da Embrapa Gado de Leite. Para informações adicionais entre em contato com cnpgl.biblioteca@embrapa.br. |
|
Registro Completo |
|
Biblioteca(s): |
Embrapa Gado de Leite; Embrapa Instrumentação. |
|
Data corrente: |
28/09/2022 |
|
Data da última atualização: |
28/09/2022 |
|
Tipo da produção científica: |
Artigo em Periódico Indexado |
|
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. |
|
Afiliação: |
LUIZ HENRIQUE CAPPARELLI MATTOSO, CNPDIA. |
|
Título: |
Microfluidic E-tongue to diagnose bovine mastitis with milk samples using machine learning with decision tree models. |
|
Ano de publicação: |
2022 |
|
Fonte/Imprenta: |
Chemical Engineering Journal, v. 451, e138523, 2022. |
|
Páginas: |
1 - 9 |
|
ISSN: |
1385-8947 |
|
DOI: |
https://doi.org/10.1016/j.cej.2022.138523 |
|
Idioma: |
Inglês |
|
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 |
|
Palavras-Chave: |
Impedance spectroscopy; Machine learning; Mastite; Multidimensional calibration space; S aureus; Sensors. |
|
Thesagro: |
Bovino; Doença Animal; Gado Leiteiro. |
|
Categoria do assunto: |
--
L Ciência Animal e Produtos de Origem Animal |
|
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.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Instrumentação (CNPDIA) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
|
|
|
Registro Completo
|
Biblioteca(s): |
Embrapa Roraima. |
|
Data corrente: |
03/02/2021 |
|
Data da última atualização: |
18/06/2021 |
|
Tipo da produção científica: |
Artigo em Periódico Indexado |
|
Autoria: |
SOUZA, C. G.; PAIVA-RODRIGUES, R. M. S.; BARDALES-LOZANO, R. M.; CHAGAS, E. A.; GRANJA, F. |
|
Afiliação: |
EDVAN ALVES CHAGAS, CPAF-RR. |
|
Título: |
Variability of Myrciaria dubia genotypes (Myrtaceae) in native populations of Roraima state. |
|
Ano de publicação: |
2020 |
|
Fonte/Imprenta: |
Genetics and Molecular Research, v. 19, n. 2, 2020. |
|
Idioma: |
Inglês |
|
Conteúdo: |
Camu-camu, Myrciaria dubia (Myrtaceae) is a native species of the Amazon Rainforest that has been attracting attention worldwide and arousing great interest in the food and pharmacological industries due to the high concentrations of ascorbic acid in its fruit, which is exported to several countries. Characterizing different materials of M. dubia by means of molecular markers allows integration of agronomic and molecular information to aid in the search for more promising varieties. We examined the genetic variability of 11 populations of this species distributed along the Branco River hydrographic basin in state of Roraima in northern Brazil. The populations were defined taking into account the origin of the subsample. The 55 sub-samples present in the Embrapa Roraima Germplasm Collection were evaluated using five ISSR initiators (UBC 811, UBC 812, UBC 817, UBC 868 and UBC 880). The five primers tested generated 64 fragments, with a 98% polymorphism rate. The greatest genetic variation was expressed within the populations (66.6%), while the lowest divergence was determined among the populations (33.4%) of the collection. There was a significant correlation between genetic and geographical distances (Mantel test, r = 0.3%, P < 0.01). Analysis with the UPGMA method gave four subgroups showing that various individuals are genetically divergent and can be used in genetic breeding programs. |
|
Palavras-Chave: |
Camu-camu; Genetic Variability; Roraima. |
|
Categoria do assunto: |
-- |
|
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/220893/1/Variability-camu-camu-Genetics-and-Molecular-Research-v19-n2-p1-9-2020-02.16.04.031.00.03.pdf
|
|
Marc: |
LEADER 02024naa a2200205 a 4500
001 2129792
005 2021-06-18
008 2020 bl uuuu u00u1 u #d
100 1 $aSOUZA, C. G.
245 $aVariability of Myrciaria dubia genotypes (Myrtaceae) in native populations of Roraima state.$h[electronic resource]
260 $c2020
520 $aCamu-camu, Myrciaria dubia (Myrtaceae) is a native species of the Amazon Rainforest that has been attracting attention worldwide and arousing great interest in the food and pharmacological industries due to the high concentrations of ascorbic acid in its fruit, which is exported to several countries. Characterizing different materials of M. dubia by means of molecular markers allows integration of agronomic and molecular information to aid in the search for more promising varieties. We examined the genetic variability of 11 populations of this species distributed along the Branco River hydrographic basin in state of Roraima in northern Brazil. The populations were defined taking into account the origin of the subsample. The 55 sub-samples present in the Embrapa Roraima Germplasm Collection were evaluated using five ISSR initiators (UBC 811, UBC 812, UBC 817, UBC 868 and UBC 880). The five primers tested generated 64 fragments, with a 98% polymorphism rate. The greatest genetic variation was expressed within the populations (66.6%), while the lowest divergence was determined among the populations (33.4%) of the collection. There was a significant correlation between genetic and geographical distances (Mantel test, r = 0.3%, P < 0.01). Analysis with the UPGMA method gave four subgroups showing that various individuals are genetically divergent and can be used in genetic breeding programs.
653 $aCamu-camu
653 $aGenetic Variability
653 $aRoraima
700 1 $aPAIVA-RODRIGUES, R. M. S.
700 1 $aBARDALES-LOZANO, R. M.
700 1 $aCHAGAS, E. A.
700 1 $aGRANJA, F.
773 $tGenetics and Molecular Research$gv. 19, n. 2, 2020.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Roraima (CPAF-RR) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
| Nenhum registro encontrado para a expressão de busca informada. |
|
|
