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Registro Completo |
Biblioteca(s): |
Embrapa Gado de Leite. |
Data corrente: |
30/11/2023 |
Data da última atualização: |
30/11/2023 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
SANTOS, I. S.; TAVARES, C. P.; KLAFKE, G. M.; RECK, J.; MONTEIRO, C. M. O.; PRATA, M. C. de A.; GOLO. P. S.; SILVA, A. C.; COSTA-JUNIOR, L. M. |
Afiliação: |
IGOR S. SANTOS, UNIVERSIDADE FEDERAL DO MARANHÃO; CAIO P. TAVARES, UNIVERSIDADE FEDERAL DO MARANHÃO; GUILHERME M. KLAFKE, INSTITUTO DE PESQUISAS VETERINÁRIAS DESIDÉRIO FINAMOR; JOSÉ RECK, INSTITUTO DE PESQUISAS VETERINÁRIAS DESIDÉRIO FINAMOR; CAIO M. O. MONTEIRO, UNIVERSIDADE FEDERAL DE GOIÁS; MARCIA CRISTINA DE AZEVEDO PRATA, CNPGL; PATRÍCIA S. GOLO, UNIVERSIDADE FEDERAL RURAL DO RIO DE JANEIRO; ARISTOFANES C. SILVA, UNIVERSIDADE FEDERAL DO MARANHÃO; LIVIO M. COSTA-JUNIOR, UNIVERSIDADE FEDERAL DO MARANHÃO. |
Título: |
Automatic method based on deep learning to identify and account Rhipicephalus microplus larval hatching. |
Ano de publicação: |
2023 |
Fonte/Imprenta: |
Medical and Veterinary Entomology, v. 37, p. 665-674, 2023. |
DOI: |
http://doi.org/10.1111/mve.12664 |
Idioma: |
Inglês |
Conteúdo: |
Reports of Rhipicephalus microplus resistant populations worldwide have increased extensively, making it difficult to control this ectoparasite. The adult immersion test, commonly used to screen for acaricide resistance, produces the results only after 40 days of the tick collection because it needs the eggs to be laid and larvae to hatch. The present study aims to develop an automatic method, based on deep learning, to predict the hatching of R. microplus larva based on egg morphology. Initially, the time course of embryonic development of tick eggs was performed to discriminate between viable and non-viable eggs. Secondly, using artificial intelligence deep learning techniques, a method was developed to classify and count the eggs. The larval hatching rate of three populations of R. microplus was evaluated for the software validation process. Groups of three and six images of eggs with 12 days of embryonic development were submitted to the software to predict the larval hatching percent automatically. The results obtained by the software were compared with the prediction results of the hatching percentage performed manually by the specialist and with the results of the hatching percentage of larvae obtained in the biological assay. The group with three images of each population submitted to the software for automatic prediction of the larval hatching percent presented mean values of 96.35% ± 3.33 (Piracanjuba population), 95.98% ± 3.5 (Desterro population) and 0.0% ± 0.0 (Barbalha population). For groups with six images, the values were 94.41% ± 3.84 (Piracanjuba population), 95.93% ± 2.36 (Desterro population) and 0.0% ± 0.0 (Barbalha population). Biological assays showed the following hatching percentage values: 98% ± 1.73 (Piracanjuba population); 96% ± 2.1 (Desterro population); and 0.14% ± 0.25 (Barbalha population). There was no statistical difference between the evaluated methods. The automatic method for predicting the hatching percentage of R. microplus larvae was validated and proved to be effective, with considerable reduction in time to obtain results. MenosReports of Rhipicephalus microplus resistant populations worldwide have increased extensively, making it difficult to control this ectoparasite. The adult immersion test, commonly used to screen for acaricide resistance, produces the results only after 40 days of the tick collection because it needs the eggs to be laid and larvae to hatch. The present study aims to develop an automatic method, based on deep learning, to predict the hatching of R. microplus larva based on egg morphology. Initially, the time course of embryonic development of tick eggs was performed to discriminate between viable and non-viable eggs. Secondly, using artificial intelligence deep learning techniques, a method was developed to classify and count the eggs. The larval hatching rate of three populations of R. microplus was evaluated for the software validation process. Groups of three and six images of eggs with 12 days of embryonic development were submitted to the software to predict the larval hatching percent automatically. The results obtained by the software were compared with the prediction results of the hatching percentage performed manually by the specialist and with the results of the hatching percentage of larvae obtained in the biological assay. The group with three images of each population submitted to the software for automatic prediction of the larval hatching percent presented mean values of 96.35% ± 3.33 (Piracanjuba population), 95.98% ± 3.5 (Desterro population) and 0.0% ± 0.0 (... Mostrar Tudo |
Palavras-Chave: |
Controle; Eclosão larval; Larval hatching. |
Thesagro: |
Carrapato; Larva; Ovo; Resistência. |
Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal |
Marc: |
LEADER 03010naa a2200313 a 4500 001 2158936 005 2023-11-30 008 2023 bl uuuu u00u1 u #d 024 7 $ahttp://doi.org/10.1111/mve.12664$2DOI 100 1 $aSANTOS, I. S. 245 $aAutomatic method based on deep learning to identify and account Rhipicephalus microplus larval hatching.$h[electronic resource] 260 $c2023 520 $aReports of Rhipicephalus microplus resistant populations worldwide have increased extensively, making it difficult to control this ectoparasite. The adult immersion test, commonly used to screen for acaricide resistance, produces the results only after 40 days of the tick collection because it needs the eggs to be laid and larvae to hatch. The present study aims to develop an automatic method, based on deep learning, to predict the hatching of R. microplus larva based on egg morphology. Initially, the time course of embryonic development of tick eggs was performed to discriminate between viable and non-viable eggs. Secondly, using artificial intelligence deep learning techniques, a method was developed to classify and count the eggs. The larval hatching rate of three populations of R. microplus was evaluated for the software validation process. Groups of three and six images of eggs with 12 days of embryonic development were submitted to the software to predict the larval hatching percent automatically. The results obtained by the software were compared with the prediction results of the hatching percentage performed manually by the specialist and with the results of the hatching percentage of larvae obtained in the biological assay. The group with three images of each population submitted to the software for automatic prediction of the larval hatching percent presented mean values of 96.35% ± 3.33 (Piracanjuba population), 95.98% ± 3.5 (Desterro population) and 0.0% ± 0.0 (Barbalha population). For groups with six images, the values were 94.41% ± 3.84 (Piracanjuba population), 95.93% ± 2.36 (Desterro population) and 0.0% ± 0.0 (Barbalha population). Biological assays showed the following hatching percentage values: 98% ± 1.73 (Piracanjuba population); 96% ± 2.1 (Desterro population); and 0.14% ± 0.25 (Barbalha population). There was no statistical difference between the evaluated methods. The automatic method for predicting the hatching percentage of R. microplus larvae was validated and proved to be effective, with considerable reduction in time to obtain results. 650 $aCarrapato 650 $aLarva 650 $aOvo 650 $aResistência 653 $aControle 653 $aEclosão larval 653 $aLarval hatching 700 1 $aTAVARES, C. P. 700 1 $aKLAFKE, G. M. 700 1 $aRECK, J. 700 1 $aMONTEIRO, C. M. O. 700 1 $aPRATA, M. C. de A. 700 1 $aGOLO. P. S. 700 1 $aSILVA, A. C. 700 1 $aCOSTA-JUNIOR, L. M. 773 $tMedical and Veterinary Entomology$gv. 37, p. 665-674, 2023.
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Embrapa Gado de Leite (CNPGL) |
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Biblioteca(s): |
Embrapa Amazônia Ocidental; Embrapa Amazônia Oriental. |
Data corrente: |
03/03/2004 |
Data da última atualização: |
17/10/2016 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
Nacional - A |
Autoria: |
TRUJILLO, L.; LEHMANN, J.; CRAVO, M. da S.; ATROCH, A. L.; NASCIMENTO FILHO, F. J. do. |
Afiliação: |
Embrapa Amazônia Ocidental; INPA; Institute of Soil Science and Soil Geography.; ANDRE LUIZ ATROCH, CPAA; FIRMINO JOSE DO NASCIMENTO FILHO, CPAA. |
Título: |
Fertilization and cover crop effects on soil nitrogen and plant nutrition in a young guarana plantation. |
Ano de publicação: |
2003 |
Fonte/Imprenta: |
Acta Amazônica, v. 33, n. 4, p. 535-548, out./dez. 2003. |
DOI: |
http://dx.doi.org/10.1590/S0044-59672003000400001 |
Idioma: |
Inglês |
Conteúdo: |
O presente estudo quantificou os efeitos da fertilização mineral e da cobertura do solo com uma leguminosa (Pueraria phaseoloides (Roxb) Benth.) sobre a dinâmica de nutrientes no sistema solo-planta. |
Palavras-Chave: |
Acid tropical soil; Amazônia brasileira; Brasil; Brazilian Amazon; Cover trop; Fruit tree; Fruteira; Lixiviação de nitrogênio; Lixiviação do nitrogênio; Nitrogen leaching; Solo tropical ácido. |
Thesagro: |
Fruta; Guaraná; Nutrição Vegetal; Paullinia Cupana; Planta de Cobertura; Solo. |
Thesaurus NAL: |
Amazonia. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/148873/1/v33n4a01.pdf
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/28662/1/v33n4a01.pdf
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Marc: |
LEADER 01353naa a2200397 a 4500 001 1673114 005 2016-10-17 008 2003 bl uuuu u00u1 u #d 024 7 $ahttp://dx.doi.org/10.1590/S0044-59672003000400001$2DOI 100 1 $aTRUJILLO, L. 245 $aFertilization and cover crop effects on soil nitrogen and plant nutrition in a young guarana plantation. 260 $c2003 520 $aO presente estudo quantificou os efeitos da fertilização mineral e da cobertura do solo com uma leguminosa (Pueraria phaseoloides (Roxb) Benth.) sobre a dinâmica de nutrientes no sistema solo-planta. 650 $aAmazonia 650 $aFruta 650 $aGuaraná 650 $aNutrição Vegetal 650 $aPaullinia Cupana 650 $aPlanta de Cobertura 650 $aSolo 653 $aAcid tropical soil 653 $aAmazônia brasileira 653 $aBrasil 653 $aBrazilian Amazon 653 $aCover trop 653 $aFruit tree 653 $aFruteira 653 $aLixiviação de nitrogênio 653 $aLixiviação do nitrogênio 653 $aNitrogen leaching 653 $aSolo tropical ácido 700 1 $aLEHMANN, J. 700 1 $aCRAVO, M. da S. 700 1 $aATROCH, A. L. 700 1 $aNASCIMENTO FILHO, F. J. do 773 $tActa Amazônica$gv. 33, n. 4, p. 535-548, out./dez. 2003.
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