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 | Acesso ao texto completo restrito à biblioteca da Embrapa Suínos e Aves. Para informações adicionais entre em contato com cnpsa.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Suínos e Aves. |
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Data corrente: |
27/07/2021 |
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Data da última atualização: |
27/07/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
SOUZA, T. C. D. de; SILVA, V. S.; MORES, M. A. Z.; KRAMER, B.; LEME, R. A.; PORTO, G. da S.; ALFIERI, A. A. |
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Afiliação: |
TATIANA CAROLINA GOMES DUTRA DE SOUZA, UEL; VIRGINIA SANTIAGO SILVA, CNPSA; MARCOS ANTONIO ZANELLA MORES, CNPSA; BEATRIS KRAMER, CNPSA; RAQUEL ARRUDA LEME, UEL; GISELE DA SILVA PORTO, UEL; AMAURI ALCINDO ALFIERI, UEL. |
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Título: |
Mycoplasma hyopneumoniae in free-living wild boars in Paraná, Brazil. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Brazilian Journal of Microbiology, 3 May 2021. |
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DOI: |
https://doi.org/10.1007/s42770-021-00516-0 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract: This is the first study conducted in Paraná, Brazil, to investigate Mycoplasma hyopneumoniae (Mhyo) infection in free-living wild boars. Eighty-eight wild boars were managed by authorized controllers between 2017 and 2019 in the state of Paraná in southern Brazil. Management georeferencing, sex, and weight were recorded for each animal. The presence of Mhyo antibodies in wild boar serum samples was evaluated using a commercial indirect ELISA kit. The presence of enzootic pneumonia-like gross lesions was evaluated, and the observed macroscopic lesions were subjected to immunohistochemistry (IHC). The Chi-square test and the intensity of the association with the odds ratio and 95% confidence interval were used to evaluate the differences in the qualitative variables between groups (sex and municipality). Juvenile wild boars exhibited a higher seroprevalence than older ones (p = 0.005). The Teixeira Soares municipality differed in Mhyo seroprevalence in comparison with Castro (p < 0.001), Ponta Grossa (p = 0.004), and Carambeí (p < 0.001). Females were 6.79 times more likely to present consolidation lesions than males (p = 0.004). Among the evaluated lung samples with injuries, 57.1% (8/14) and 53.8% (7/13) were Mhyo positive by IHC in Castro and Ponta Grossa, respectively, confirming that the identified macroscopic lesions were caused by Mhyo. This study demonstrates the circulation of Mhyo in free-living wild boars, which raises concerns regarding the epidemiological role of this animal species for the spread of the pathogen. MenosAbstract: This is the first study conducted in Paraná, Brazil, to investigate Mycoplasma hyopneumoniae (Mhyo) infection in free-living wild boars. Eighty-eight wild boars were managed by authorized controllers between 2017 and 2019 in the state of Paraná in southern Brazil. Management georeferencing, sex, and weight were recorded for each animal. The presence of Mhyo antibodies in wild boar serum samples was evaluated using a commercial indirect ELISA kit. The presence of enzootic pneumonia-like gross lesions was evaluated, and the observed macroscopic lesions were subjected to immunohistochemistry (IHC). The Chi-square test and the intensity of the association with the odds ratio and 95% confidence interval were used to evaluate the differences in the qualitative variables between groups (sex and municipality). Juvenile wild boars exhibited a higher seroprevalence than older ones (p = 0.005). The Teixeira Soares municipality differed in Mhyo seroprevalence in comparison with Castro (p < 0.001), Ponta Grossa (p = 0.004), and Carambeí (p < 0.001). Females were 6.79 times more likely to present consolidation lesions than males (p = 0.004). Among the evaluated lung samples with injuries, 57.1% (8/14) and 53.8% (7/13) were Mhyo positive by IHC in Castro and Ponta Grossa, respectively, confirming that the identified macroscopic lesions were caused by Mhyo. This study demonstrates the circulation of Mhyo in free-living wild boars, which raises concerns regarding the epidemiologica... Mostrar Tudo |
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Palavras-Chave: |
Consolidação pulmonar; Enzootic pneumonia; Imunohistoquímica; Pulmonary consolidation. |
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Thesagro: |
Elisa; Micoplasmose; Pneumonia Enzoótica; Suíno. |
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Thesaurus Nal: |
Immunohistochemistry; Mycoplasmosis; Swine. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02528naa a2200337 a 4500
001 2133127
005 2021-07-27
008 2021 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1007/s42770-021-00516-0$2DOI
100 1 $aSOUZA, T. C. D. de
245 $aMycoplasma hyopneumoniae in free-living wild boars in Paraná, Brazil.$h[electronic resource]
260 $c2021
520 $aAbstract: This is the first study conducted in Paraná, Brazil, to investigate Mycoplasma hyopneumoniae (Mhyo) infection in free-living wild boars. Eighty-eight wild boars were managed by authorized controllers between 2017 and 2019 in the state of Paraná in southern Brazil. Management georeferencing, sex, and weight were recorded for each animal. The presence of Mhyo antibodies in wild boar serum samples was evaluated using a commercial indirect ELISA kit. The presence of enzootic pneumonia-like gross lesions was evaluated, and the observed macroscopic lesions were subjected to immunohistochemistry (IHC). The Chi-square test and the intensity of the association with the odds ratio and 95% confidence interval were used to evaluate the differences in the qualitative variables between groups (sex and municipality). Juvenile wild boars exhibited a higher seroprevalence than older ones (p = 0.005). The Teixeira Soares municipality differed in Mhyo seroprevalence in comparison with Castro (p < 0.001), Ponta Grossa (p = 0.004), and Carambeí (p < 0.001). Females were 6.79 times more likely to present consolidation lesions than males (p = 0.004). Among the evaluated lung samples with injuries, 57.1% (8/14) and 53.8% (7/13) were Mhyo positive by IHC in Castro and Ponta Grossa, respectively, confirming that the identified macroscopic lesions were caused by Mhyo. This study demonstrates the circulation of Mhyo in free-living wild boars, which raises concerns regarding the epidemiological role of this animal species for the spread of the pathogen.
650 $aImmunohistochemistry
650 $aMycoplasmosis
650 $aSwine
650 $aElisa
650 $aMicoplasmose
650 $aPneumonia Enzoótica
650 $aSuíno
653 $aConsolidação pulmonar
653 $aEnzootic pneumonia
653 $aImunohistoquímica
653 $aPulmonary consolidation
700 1 $aSILVA, V. S.
700 1 $aMORES, M. A. Z.
700 1 $aKRAMER, B.
700 1 $aLEME, R. A.
700 1 $aPORTO, G. da S.
700 1 $aALFIERI, A. A.
773 $tBrazilian Journal of Microbiology, 3 May 2021.
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Registro original: |
Embrapa Suínos e Aves (CNPSA) |
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Tipo/Formato |
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Voltar
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| Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
21/09/2020 |
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Data da última atualização: |
14/12/2021 |
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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: |
REIS, A. A. dos; SILVA, B. C.; WERNER, J. P. S.; SILVA, Y. F.; ROCHA, J. V.; FIGUEIREDO, G. K. D. A.; ANTUNES, J. F. G.; ESQUERDO, J. C. D. M.; COUTINHO, A. C.; LAMPARELLI, R. A. C; MAGALHÃES, P. S. G. |
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Afiliação: |
Feagri, Nipe/Unicamp; Feagri/Unicamp; Feagri/Unicamp; Feagri/Unicamp; Feagri/Unicamp; Feagri/Unicamp; JOAO FRANCISCO GONCALVES ANTUNES, CNPTIA; JULIO CESAR DALLA MORA ESQUERDO, CNPTIA; ALEXANDRE CAMARGO COUTINHO, CNPTIA; Nipe/Unicamp; Nipe/Unicamp. |
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Título: |
Exploring the potential of high-resolution PlanetScope imagery for pasture biomass estimation in an integrated crop-livestock system. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, v. 42-3, W12, p. 419-424, 2020. |
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DOI: |
https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-419-2020 |
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Idioma: |
Inglês |
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Notas: |
Publicado também em: IEEE LATIN AMERICAN GRSS; ISPRS REMOTE SENSING CONFERENCE, Santiago, 2020. Proceedings... [Piscataway]: IEEE, 2020. p. 675-680. LAGIRS 2020. |
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Conteúdo: |
ABSTRACT: Pasture biomass information is essential to monitor forage resources in grazed areas, as well as to support grazing management decisions. The increasing temporal and spatial resolutions offered by the new generation of orbital platforms, such as Planet CubeSat satellites, have improved the capability of monitoring pasture biomass using remotely-sensed data. In a preliminary study, we investigated the potential of spectral variables derived from PlanetScope imagery to predict pasture biomass in an area of Integrated Crop-Livestock System (ICLS) in Brazil. Satellite and field data were collected during the same period (May - August 2019) for calibration and validation of the relation between predictor variables and pasture biomass using the Random Forest (RF) regression algorithm. We used as predictor variables 24 vegetation indices derived from PlanetScope imagery, as well as the four PlanetScope bands, and field management information. Pasture biomass ranged from approximately 24 to 656 g.m-2, with a coefficient of variation of 54.96%. Near Infrared Green Simple Ratio (NIR/Green), Green Leaf Algorithm (GLA) vegetation indices and days after sowing (DAS) are among the most important variables as measured by the RF Variable Importance metric in the best RF model predicting pasture biomass, which resulted in Root Mean Square Error (RMSE) of 52.04 g.m-2 (32.75%). Accurate estimates of pasture biomass using spectral variables derived from PlanetScope imagery are promising, providing new insights into the opportunities and limitations related to the use of PlanetScope imagery for pasture monitoring. MenosABSTRACT: Pasture biomass information is essential to monitor forage resources in grazed areas, as well as to support grazing management decisions. The increasing temporal and spatial resolutions offered by the new generation of orbital platforms, such as Planet CubeSat satellites, have improved the capability of monitoring pasture biomass using remotely-sensed data. In a preliminary study, we investigated the potential of spectral variables derived from PlanetScope imagery to predict pasture biomass in an area of Integrated Crop-Livestock System (ICLS) in Brazil. Satellite and field data were collected during the same period (May - August 2019) for calibration and validation of the relation between predictor variables and pasture biomass using the Random Forest (RF) regression algorithm. We used as predictor variables 24 vegetation indices derived from PlanetScope imagery, as well as the four PlanetScope bands, and field management information. Pasture biomass ranged from approximately 24 to 656 g.m-2, with a coefficient of variation of 54.96%. Near Infrared Green Simple Ratio (NIR/Green), Green Leaf Algorithm (GLA) vegetation indices and days after sowing (DAS) are among the most important variables as measured by the RF Variable Importance metric in the best RF model predicting pasture biomass, which resulted in Root Mean Square Error (RMSE) of 52.04 g.m-2 (32.75%). Accurate estimates of pasture biomass using spectral variables derived from PlanetScope imagery are promisi... Mostrar Tudo |
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Palavras-Chave: |
Aprendizado de máquina; Dove satellites; Floresta aleatória; Índice de vegetação; Integração lavoura-pecuária; Integrated crop-livestock system; Machine Learning; Nano-Satellites; Pastureland; Random Forest; Vegetation Indices. |
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Thesagro: |
Biomassa; Pastagem. |
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Thesaurus NAL: |
Biomass; Pasture management; Vegetation index. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 03286naa a2200457 a 4500
001 2125045
005 2021-12-14
008 2020 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-419-2020$2DOI
100 1 $aREIS, A. A. dos
245 $aExploring the potential of high-resolution PlanetScope imagery for pasture biomass estimation in an integrated crop-livestock system.$h[electronic resource]
260 $c2020
500 $aPublicado também em: IEEE LATIN AMERICAN GRSS; ISPRS REMOTE SENSING CONFERENCE, Santiago, 2020. Proceedings... [Piscataway]: IEEE, 2020. p. 675-680. LAGIRS 2020.
520 $aABSTRACT: Pasture biomass information is essential to monitor forage resources in grazed areas, as well as to support grazing management decisions. The increasing temporal and spatial resolutions offered by the new generation of orbital platforms, such as Planet CubeSat satellites, have improved the capability of monitoring pasture biomass using remotely-sensed data. In a preliminary study, we investigated the potential of spectral variables derived from PlanetScope imagery to predict pasture biomass in an area of Integrated Crop-Livestock System (ICLS) in Brazil. Satellite and field data were collected during the same period (May - August 2019) for calibration and validation of the relation between predictor variables and pasture biomass using the Random Forest (RF) regression algorithm. We used as predictor variables 24 vegetation indices derived from PlanetScope imagery, as well as the four PlanetScope bands, and field management information. Pasture biomass ranged from approximately 24 to 656 g.m-2, with a coefficient of variation of 54.96%. Near Infrared Green Simple Ratio (NIR/Green), Green Leaf Algorithm (GLA) vegetation indices and days after sowing (DAS) are among the most important variables as measured by the RF Variable Importance metric in the best RF model predicting pasture biomass, which resulted in Root Mean Square Error (RMSE) of 52.04 g.m-2 (32.75%). Accurate estimates of pasture biomass using spectral variables derived from PlanetScope imagery are promising, providing new insights into the opportunities and limitations related to the use of PlanetScope imagery for pasture monitoring.
650 $aBiomass
650 $aPasture management
650 $aVegetation index
650 $aBiomassa
650 $aPastagem
653 $aAprendizado de máquina
653 $aDove satellites
653 $aFloresta aleatória
653 $aÍndice de vegetação
653 $aIntegração lavoura-pecuária
653 $aIntegrated crop-livestock system
653 $aMachine Learning
653 $aNano-Satellites
653 $aPastureland
653 $aRandom Forest
653 $aVegetation Indices
700 1 $aSILVA, B. C.
700 1 $aWERNER, J. P. S.
700 1 $aSILVA, Y. F.
700 1 $aROCHA, J. V.
700 1 $aFIGUEIREDO, G. K. D. A.
700 1 $aANTUNES, J. F. G.
700 1 $aESQUERDO, J. C. D. M.
700 1 $aCOUTINHO, A. C.
700 1 $aLAMPARELLI, R. A. C
700 1 $aMAGALHÃES, P. S. G.
773 $tThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences$gv. 42-3, W12, p. 419-424, 2020.
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