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Registro Completo |
Biblioteca(s): |
Embrapa Suínos e Aves. |
Data corrente: |
18/12/2019 |
Data da última atualização: |
19/12/2019 |
Tipo da produção científica: |
Folder/Folheto/Cartilha |
Autoria: |
BARROS, E. C.; NICOLOSO, R. da S.; OLIVEIRA, P. A. V. de; CORREA, J. C. |
Afiliação: |
EVANDRO CARLOS BARROS, CNPSA; RODRIGO DA SILVEIRA NICOLOSO, CNPSA; PAULO ARMANDO VICTORIA DE OLIVEIRA, CNPSA; JULIANO CORULLI CORREA, CNPSA. |
Título: |
Potencial agronômico dos dejetos de suínos. |
Ano de publicação: |
2019 |
Fonte/Imprenta: |
Concórdia: Embrapa Suínos e Aves, 2019. |
Páginas: |
52 p. |
Idioma: |
Português |
Palavras-Chave: |
Tratamento de efluentes. |
Thesagro: |
Dejeto; Fertilizante; Meio Ambiente; Suinocultura; Tratamento. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/207427/1/final9052.pdf
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Marc: |
LEADER 00597nam a2200217 a 4500 001 2117243 005 2019-12-19 008 2019 bl uuuu 00u1 u #d 100 1 $aBARROS, E. C. 245 $aPotencial agronômico dos dejetos de suínos.$h[electronic resource] 260 $aConcórdia: Embrapa Suínos e Aves$c2019 300 $a52 p. 650 $aDejeto 650 $aFertilizante 650 $aMeio Ambiente 650 $aSuinocultura 650 $aTratamento 653 $aTratamento de efluentes 700 1 $aNICOLOSO, R. da S. 700 1 $aOLIVEIRA, P. A. V. de 700 1 $aCORREA, J. C.
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Registro original: |
Embrapa Suínos e Aves (CNPSA) |
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Registro Completo
Biblioteca(s): |
Embrapa Recursos Genéticos e Biotecnologia; Embrapa Roraima. |
Data corrente: |
25/08/2021 |
Data da última atualização: |
15/09/2021 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 2 |
Autoria: |
AMARO, G. C.; FIDELIS, E. G.; SILVA, R. S. da; MEDEIROS, C. M. de. |
Afiliação: |
GEORGE CORREA AMARO, CPAF-RR; ELISANGELA GOMES FIDELIS, CPAC. |
Título: |
Current and potential geographic distribution of red palm mite (Raoiella indica Hirst) in Brazil. |
Ano de publicação: |
2021 |
Fonte/Imprenta: |
Ecological Informatics, v. 65, 2021. |
Idioma: |
Inglês |
Conteúdo: |
The red palm mite, Raoiella indica Hirst, is the most invasive pest, having spread quickly to several countries. In Brazil it is already present in several regions and has a high potential for dispersion to other regions, which could severely affect the cultivation of coconuts, bananas, native and exotic palm trees, and tropical flowers, such as those of the Heliconiaceae family. Thus, we aimed to determine the regions of Brazil most prone to the occurrence of R. indica using Maxent with updated data on its occurrence and a selection of bioclimatic variables that may influence its establishment. The occurrence data used were obtained through a literature search, online databases, and surveys carried out in the field. The model indicated a high potential for the establishment of R. indica in the following locations: a large part of the State of Roraima, the eastern part of the State of Amazonas, the northern and central-western parts of the State of Par´a, and parts of the states of Acre and Amap´a (North Region); the coast of Brazil from Rio Grande do Norte to the states of Paraíba, Pernanbuco, Alagoas, Sergipe and Bahia (Northeast Region); the states of Rio de Janeiro and Espírito Santo, the far east of Minas Gerais, and almost the entire state of S?ao Paulo, except the northern part (Southeast Region); most of the State of Mato Grosso do Sul and the most southern portion of the State of Mato Grosso (Midwest Region); and the northern part of the State of Paran´a and small parts of the states of Santa Catarina and Rio Grande do Sul (South Region). The bioclimatic variables that most influenced the potential geographical distribution of R. indica were precipitation of driest month (Bio14), precipitation of wettest month (Bio13), mean diurnal range (Bio2), and isothermality (Bio3). The parameterization for the Maxent model provides an updated model to prevention invasion of R. indica due updated data on its occurrence used. Thus, potential geographic distribution of R. indica in Brazil should be consider from this study. MenosThe red palm mite, Raoiella indica Hirst, is the most invasive pest, having spread quickly to several countries. In Brazil it is already present in several regions and has a high potential for dispersion to other regions, which could severely affect the cultivation of coconuts, bananas, native and exotic palm trees, and tropical flowers, such as those of the Heliconiaceae family. Thus, we aimed to determine the regions of Brazil most prone to the occurrence of R. indica using Maxent with updated data on its occurrence and a selection of bioclimatic variables that may influence its establishment. The occurrence data used were obtained through a literature search, online databases, and surveys carried out in the field. The model indicated a high potential for the establishment of R. indica in the following locations: a large part of the State of Roraima, the eastern part of the State of Amazonas, the northern and central-western parts of the State of Par´a, and parts of the states of Acre and Amap´a (North Region); the coast of Brazil from Rio Grande do Norte to the states of Paraíba, Pernanbuco, Alagoas, Sergipe and Bahia (Northeast Region); the states of Rio de Janeiro and Espírito Santo, the far east of Minas Gerais, and almost the entire state of S?ao Paulo, except the northern part (Southeast Region); most of the State of Mato Grosso do Sul and the most southern portion of the State of Mato Grosso (Midwest Region); and the northern part of the State of Paran´a and small p... Mostrar Tudo |
Palavras-Chave: |
Ecological niche modeling; Environmental modeling; Raoiella indica. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/225457/1/1-s2.0-S1574954121001874-main.pdf
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Marc: |
LEADER 02649naa a2200193 a 4500 001 2133841 005 2021-09-15 008 2021 bl uuuu u00u1 u #d 100 1 $aAMARO, G. C. 245 $aCurrent and potential geographic distribution of red palm mite (Raoiella indica Hirst) in Brazil.$h[electronic resource] 260 $c2021 520 $aThe red palm mite, Raoiella indica Hirst, is the most invasive pest, having spread quickly to several countries. In Brazil it is already present in several regions and has a high potential for dispersion to other regions, which could severely affect the cultivation of coconuts, bananas, native and exotic palm trees, and tropical flowers, such as those of the Heliconiaceae family. Thus, we aimed to determine the regions of Brazil most prone to the occurrence of R. indica using Maxent with updated data on its occurrence and a selection of bioclimatic variables that may influence its establishment. The occurrence data used were obtained through a literature search, online databases, and surveys carried out in the field. The model indicated a high potential for the establishment of R. indica in the following locations: a large part of the State of Roraima, the eastern part of the State of Amazonas, the northern and central-western parts of the State of Par´a, and parts of the states of Acre and Amap´a (North Region); the coast of Brazil from Rio Grande do Norte to the states of Paraíba, Pernanbuco, Alagoas, Sergipe and Bahia (Northeast Region); the states of Rio de Janeiro and Espírito Santo, the far east of Minas Gerais, and almost the entire state of S?ao Paulo, except the northern part (Southeast Region); most of the State of Mato Grosso do Sul and the most southern portion of the State of Mato Grosso (Midwest Region); and the northern part of the State of Paran´a and small parts of the states of Santa Catarina and Rio Grande do Sul (South Region). The bioclimatic variables that most influenced the potential geographical distribution of R. indica were precipitation of driest month (Bio14), precipitation of wettest month (Bio13), mean diurnal range (Bio2), and isothermality (Bio3). The parameterization for the Maxent model provides an updated model to prevention invasion of R. indica due updated data on its occurrence used. Thus, potential geographic distribution of R. indica in Brazil should be consider from this study. 653 $aEcological niche modeling 653 $aEnvironmental modeling 653 $aRaoiella indica 700 1 $aFIDELIS, E. G. 700 1 $aSILVA, R. S. da 700 1 $aMEDEIROS, C. M. de 773 $tEcological Informatics$gv. 65, 2021.
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