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Registro Completo |
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Biblioteca(s): |
Embrapa Cerrados. |
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Data corrente: |
19/11/2001 |
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Data da última atualização: |
19/11/2001 |
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Autoria: |
FARIA, L. C.; CARLIN, V. J.; NUNES JUNIOR, J.; MONTEIRO, P. M. F. O. |
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Título: |
Avaliacao de sete cultivares de soja em tres epocas de semeadura e em quatro densidades de plantio. |
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Ano de publicação: |
2000 |
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Fonte/Imprenta: |
In: REUNIAO DE PESQUISA DE SOJA DA REGIAO CENTRAL DO BRASIL, 22., 2000, Cuiaba, MT. Resumos. Cuiaba: Embrapa Soja, 2000. |
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Páginas: |
p.116. |
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Série: |
(Embrapa Soja. Documentos, 144). |
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Idioma: |
Português |
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Palavras-Chave: |
315; Brasil; Cultivar BRSGO 204; Cultivar BRSGO Catalao; Cultivar BRSGO Goiatuba; Cultivar BRSGO Jatai; Cultivar BRSGOBela Vista; Cultivar Emgopa; Cultivar Emgopa 316; Mato Grosso; Tangara da Serra. |
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Thesagro: |
Cerrado; Densidade de Plantio; Época de Semeadura; Glycine Max; Soja. |
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Thesaurus Nal: |
Brazil; sowing date; soybeans; varieties. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 01188nam a2200397 a 4500
001 1558453
005 2001-11-19
008 2000 bl uuuu u01u1 u #d
100 1 $aFARIA, L. C.
245 $aAvaliacao de sete cultivares de soja em tres epocas de semeadura e em quatro densidades de plantio.
260 $aIn: REUNIAO DE PESQUISA DE SOJA DA REGIAO CENTRAL DO BRASIL, 22., 2000, Cuiaba, MT. Resumos. Cuiaba: Embrapa Soja$c2000
300 $ap.116.
490 $a(Embrapa Soja. Documentos, 144).
650 $aBrazil
650 $asowing date
650 $asoybeans
650 $avarieties
650 $aCerrado
650 $aDensidade de Plantio
650 $aÉpoca de Semeadura
650 $aGlycine Max
650 $aSoja
653 $a315
653 $aBrasil
653 $aCultivar BRSGO 204
653 $aCultivar BRSGO Catalao
653 $aCultivar BRSGO Goiatuba
653 $aCultivar BRSGO Jatai
653 $aCultivar BRSGOBela Vista
653 $aCultivar Emgopa
653 $aCultivar Emgopa 316
653 $aMato Grosso
653 $aTangara da Serra
700 1 $aCARLIN, V. J.
700 1 $aNUNES JUNIOR, J.
700 1 $aMONTEIRO, P. M. F. O.
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Registro original: |
Embrapa Cerrados (CPAC) |
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Registro |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
16/05/2014 |
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Data da última atualização: |
20/05/2014 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
C - 0 |
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Autoria: |
BARBEDO, J. G. A. |
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Afiliação: |
JAYME GARCIA ARNAL BARBEDO, CNPTIA. |
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Título: |
Computer-aided disease diagnosis in aquaculture: current state and perspectives for the future. |
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Ano de publicação: |
2014 |
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Fonte/Imprenta: |
Revista Innover, São Luís, v. 1, n. 1, p. 19-32, mar. 2014. |
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Idioma: |
Inglês |
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Conteúdo: |
ABSTRACT. Automation of essential processes in agriculture is becoming widespread, especially when fast action is required. However, some processes that could greatly benefit from some degree of automation have such difficult characteristics, that even small improvements pose a great challenge. This is the case of fish disease diagnosis, a problem of great economic, social and ecological interest. Difficult problems like this often require a interdisciplinary approach to be tackled properly, as multifaceted issues can greatly benefit from the inclusion of different perspectives. In this context, this paper presents the most recent advances in research subjects such as expert systems applied to fish disease diagnosis, computer vision applied to aquaculture, and image-based disease diagnosis applied to agriculture, and discusses how those advances may be combined to support future developments towards more effective diagnosis tools. The paper finishes suggesting a possible solution to increase the degree of automation of fish disease diagnosis tools. |
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Palavras-Chave: |
Doenças em peixes; Processamento de imagem digital; Sistemas especialistas. |
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Thesagro: |
Aquicultura; Automação. |
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Thesaurus NAL: |
Aquaculture; Automation; Expert systems; Fish diseases; Image analysis. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/102242/1/aquaculture.pdf
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Marc: |
LEADER 01796naa a2200241 a 4500
001 1986333
005 2014-05-20
008 2014 bl uuuu u00u1 u #d
100 1 $aBARBEDO, J. G. A.
245 $aComputer-aided disease diagnosis in aquaculture$bcurrent state and perspectives for the future.$h[electronic resource]
260 $c2014
520 $aABSTRACT. Automation of essential processes in agriculture is becoming widespread, especially when fast action is required. However, some processes that could greatly benefit from some degree of automation have such difficult characteristics, that even small improvements pose a great challenge. This is the case of fish disease diagnosis, a problem of great economic, social and ecological interest. Difficult problems like this often require a interdisciplinary approach to be tackled properly, as multifaceted issues can greatly benefit from the inclusion of different perspectives. In this context, this paper presents the most recent advances in research subjects such as expert systems applied to fish disease diagnosis, computer vision applied to aquaculture, and image-based disease diagnosis applied to agriculture, and discusses how those advances may be combined to support future developments towards more effective diagnosis tools. The paper finishes suggesting a possible solution to increase the degree of automation of fish disease diagnosis tools.
650 $aAquaculture
650 $aAutomation
650 $aExpert systems
650 $aFish diseases
650 $aImage analysis
650 $aAquicultura
650 $aAutomação
653 $aDoenças em peixes
653 $aProcessamento de imagem digital
653 $aSistemas especialistas
773 $tRevista Innover, São Luís$gv. 1, n. 1, p. 19-32, mar. 2014.
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Embrapa Agricultura Digital (CNPTIA) |
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