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Registro Completo |
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Biblioteca(s): |
Embrapa Agrobiologia; Embrapa Agropecuária Oeste; Embrapa Amazônia Ocidental; Embrapa Amazônia Oriental; Embrapa Cerrados; Embrapa Clima Temperado; Embrapa Hortaliças; Embrapa Meio-Norte; Embrapa Milho e Sorgo; Embrapa Rondônia; Embrapa Roraima; Embrapa Semiárido; Embrapa Soja; Embrapa Solos; Embrapa Suínos e Aves; Embrapa Tabuleiros Costeiros; Embrapa Unidades Centrais. MenosEmbrapa Agrobiologia; Embrapa Agropecuária Oeste; Embrapa Amazônia Ocidental; Embrapa Amazônia Oriental; Embrapa Cerrados; Embrapa Clima Temperado; Embrapa Hortaliças; Embrapa Meio-Norte; Embrapa Milho e Sorgo; Embrapa Rondônia... Mostrar Todas |
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Data corrente: |
12/03/1998 |
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Data da última atualização: |
17/09/2015 |
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Tipo da produção científica: |
Circular Técnica |
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Autoria: |
FERNANDES, F. T.; OLIVEIRA, E. de. |
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Afiliação: |
EMBRAPA/CNPMS. |
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Título: |
Principais doenças na cultura do milho. |
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Ano de publicação: |
1997 |
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Fonte/Imprenta: |
Sete Lagoas: EMBRAPA-CNPMS, 1997. |
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Páginas: |
80p. |
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Série: |
(EMBRAPA-CNPMS. Circular técnica, 26). |
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Idioma: |
Português |
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Conteúdo: |
Doencas foliares; Mancha por Phaeosphaeria; Ferrugem polysora; Ferrugem branca ou tropical; Ferrugem comum; Mancha por Helminthosporium turcicum; Mancha por Helminthosporium maydis; Mildio do sorgo em milho; Queima por Pseudomonas alboprecipitans; Podridao do cartucho por Erwinia chrysantemi; Podridoes do colmo e das raizes; Podridao por Diplodia maydis; Podridao por Fusarium; Podridao por Pythium; Antracnose do colmo (Podridao por Colletotrichum); Podridoes do colmo por bacterias; Doencas das espigas; Podridao branca da espiga; Podridao rosada da espiga; Carvao comum; Doencas causadas por mollicutes e por virus; Enfezamento palido; Enfezamento vermelho; Rayado fino; Mosaico comum do milho; Outras doencas na cultura do milho. |
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Palavras-Chave: |
Brasil; Centro Nacional de Pesquisa de Milho e Sorgo(Sete Lagoas; Control; Controle; Cultura; Culture; Diploidia maydis; Disease; Diseases; Disiase; Doen?a; Doenca da espiga; Doenca da folha; Doenca por virus; Doencas; EMBRAPA; Fitopatologia; Fungus; Maize; MG); Minas Gerais; Phytopathology; Plant disease; Plant diseases; Root rots; Spikes. |
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Thesagro: |
Bactéria; Colmo; Doença; Doença de Planta; Espiga; Folha; Fungo; Fusarium; Helminthosporium; Milho; Podridão da Raiz; Podridão do Colmo; Raiz; Vírus; Zea Mays. |
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Thesaurus Nal: |
Brazil; Colletotrichum; corn; leaves; Mollicutes; Phaeosphaeria; Pythium; stems. |
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Categoria do assunto: |
--
O Insetos e Entomologia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/37540/1/circ-26-1.pdf
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Marc: |
LEADER 02447nam a2200733 a 4500
001 1478849
005 2015-09-17
008 1997 bl uuuu 00u1 u #d
100 1 $aFERNANDES, F. T.
245 $aPrincipais doenças na cultura do milho.
260 $aSete Lagoas: EMBRAPA-CNPMS$c1997
300 $a80p.
490 $a(EMBRAPA-CNPMS. Circular técnica, 26).
520 $aDoencas foliares; Mancha por Phaeosphaeria; Ferrugem polysora; Ferrugem branca ou tropical; Ferrugem comum; Mancha por Helminthosporium turcicum; Mancha por Helminthosporium maydis; Mildio do sorgo em milho; Queima por Pseudomonas alboprecipitans; Podridao do cartucho por Erwinia chrysantemi; Podridoes do colmo e das raizes; Podridao por Diplodia maydis; Podridao por Fusarium; Podridao por Pythium; Antracnose do colmo (Podridao por Colletotrichum); Podridoes do colmo por bacterias; Doencas das espigas; Podridao branca da espiga; Podridao rosada da espiga; Carvao comum; Doencas causadas por mollicutes e por virus; Enfezamento palido; Enfezamento vermelho; Rayado fino; Mosaico comum do milho; Outras doencas na cultura do milho.
650 $aBrazil
650 $aColletotrichum
650 $acorn
650 $aleaves
650 $aMollicutes
650 $aPhaeosphaeria
650 $aPythium
650 $astems
650 $aBactéria
650 $aColmo
650 $aDoença
650 $aDoença de Planta
650 $aEspiga
650 $aFolha
650 $aFungo
650 $aFusarium
650 $aHelminthosporium
650 $aMilho
650 $aPodridão da Raiz
650 $aPodridão do Colmo
650 $aRaiz
650 $aVírus
650 $aZea Mays
653 $aBrasil
653 $aCentro Nacional de Pesquisa de Milho e Sorgo(Sete Lagoas
653 $aControl
653 $aControle
653 $aCultura
653 $aCulture
653 $aDiploidia maydis
653 $aDisease
653 $aDiseases
653 $aDisiase
653 $aDoen?a
653 $aDoenca da espiga
653 $aDoenca da folha
653 $aDoenca por virus
653 $aDoencas
653 $aEMBRAPA
653 $aFitopatologia
653 $aFungus
653 $aMaize
653 $aMG)
653 $aMinas Gerais
653 $aPhytopathology
653 $aPlant disease
653 $aPlant diseases
653 $aRoot rots
653 $aSpikes
700 1 $aOLIVEIRA, E. de
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Registro original: |
Embrapa Milho e Sorgo (CNPMS) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Solos. Para informações adicionais entre em contato com cnps.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Solos. |
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Data corrente: |
27/11/2018 |
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Data da última atualização: |
11/11/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
WALDNER, F.; SCHUCKNECHT, A.; LESIV, M.; GALLEGO, J.; SEE, L.; PÉREZ-HOYOS, A.; D'ANDRIMONT, R.; DE MAET, T.; LASO BAYAS, J. C.; FRITZ, S.; LEO, O.; KERDILES, H.; DÍEZ, M.; VAN TRICHT, K.; GILLIAMS, S.; SHELESTOV, A.; LAVRENIUK, M.; SIMÕES, M.; FERRAZ, R. P. D.; BELLÓN, B.; BÉGUÉ, A.; HAZEU, G.; STONACEK, V.; KOLOMAZNIK, J.; MISUREC, J.; VERÓN, S. R.; ABELLEYRA, D. de; PLOTNIKOV, D.; MINGYONG, L.; SINGHA, M.; PATIL, P.; ZHANG, M.; DEFOURNY, P. |
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Afiliação: |
FRANÇOIS WALDNER, UNIVERSITÉ CATHOLIQUE DE LOUVAIN, BELGIUM/COMMONWEALTH SCIENTIFIC AND INDUSTRIAL RESEARCH ORGANISATION, AGRICULTURE AND FOOD, AUSTRALIA; ANNE SCHUCKNECHT, EUROPEAN COMMISSION JOINT RESEARCH CENTRE, ISPRA, ITALY/KARLSRUHE INSTITUTE OF TECHNOLOGY, GARMISCH-PARTENKIRCHEN, GERMANY; MYROSLAVA LESIV, INTERNATIONAL INSTITUTE FOR APPLIED SYSTEMS ANALYSIS, LAXENBURG, AUSTRIA; JAVIER GALLEGO, EUROPEAN COMMISSION JOINT RESEARCH CENTRE, ISPRA, ITALY; LINDA SEE, INTERNATIONAL INSTITUTE FOR APPLIED SYSTEMS ANALYSIS, LAXENBURG, AUSTRIA; ANA PÉREZ-HOYOS, EUROPEAN COMMISSION JOINT RESEARCH CENTRE, ISPRA, ITALY; RAPHAËL D'ANDRIMONT, UNIVERSITÉ CATHOLIQUE DE LOUVAIN, BELGIUM/EUROPEAN COMMISSION JOINT RESEARCH CENTRE, ISPRA, ITALY; THOMAS DE MAET, UNIVERSITÉ CATHOLIQUE DE LOUVAIN, EARTH AND LIFE INSTITUTE, LOUVAIN-LA-NEUVE, BELGIUM; JUAN CARLOS LASO BAYAS, INTERNATIONAL INSTITUTE FOR APPLIED SYSTEMS ANALYSIS, LAXENBURG, AUSTRIA; STEFFEN FRITZ, INTERNATIONAL INSTITUTE FOR APPLIED SYSTEMS ANALYSIS, LAXENBURG, AUSTRIA; OLIVIER LEO, EUROPEAN COMMISSION JOINT RESEARCH CENTRE, ISPRA, ITALY; HERVÉ KERDILES, EUROPEAN COMMISSION JOINT RESEARCH CENTRE, ISPRA, ITALY; MÓNICA DÍEZ, DEIMOS IMAGING, BOECILLO, VALLADOLID, SPAIN; KRISTOF VAN TRICHT, VITO REMOTE SENSING, MOL, BELGIUM; SVEN GILLIAMS, VITO REMOTE SENSING, MOL, BELGIUM; ANDRII SHELESTOV, NATIONAL TECHNICAL UNIVERSITY OF UKRAINE IGOR SIKORSKY KYIV POLYTECHNIC INSTITUE, KYIV, UKRAINE; MYKOLA LAVRENIUK, NATIONAL TECHNICAL UNIVERSITY OF UKRAINE IGOR SIKORSKY KYIV POLYTECHNIC INSTITUE, KYIV, UKRAINE; MARGARETH GONCALVES SIMOES, CNPS; RODRIGO PECANHA DEMONTE FERRAZ, CNPS; BEATRIZ BELLÓN, CIRAD, UMR TETIS, MONTPELLIER, FRANCE; AGNÈS BÉGUÉ, CIRAD, UMR TETIS, MONTPELLIER, FRANCE/TETIS, CIRAD, IRSTEA, AGROPARISTECH, CNRS, UNIV MONTPELLIER, MONTPELLIER, FRANCE; GERARD HAZEU, WAGENINGEN ENVIRONMENTAL RESEARCH (ALTERRA), WAGENINGEN, THE NETHERLANDS; VACLAV STONACEK, GISAT S.R.O., PRAGUE, CZECH REPUBLIC; JAN KOLOMAZNIK, GISAT S.R.O., PRAGUE, CZECH REPUBLIC; JAN MISUREC, GISAT S.R.O., PRAGUE, CZECH REPUBLIC; SANTIAGO R. VERÓN, INSTITUTO NACIONAL DE TECNOLOGÍA AGROPECUARIA (INTA), HURLINGHAM, ARGENTINA/UNIVERSIDAD DE BUENOS AIRES AND CONICET, BUENOS AIRES, ARGENTINA; DIEGO DE ABELLEYRA, INSTITUTO NACIONAL DE TECNOLOGÍA AGROPECUARIA (INTA), HURLINGHAM, ARGENTINA; DMITRY PLOTNIKOV, TERRESTRIAL ECOSYSTEMS MONITORING LABORATORY, SPACE RESEARCH INSTITUTE OF RUSSIAN ACADEMY OF SCIENCES (IKI), MOSCOW, RUSSIA; LI MINGYONG, KEY LABORATORY OF DIGITAL EARTH SCIENCE, INSTITUDE OF REMOTE SENSING AND DIGITAL EARTH, CHINESE ACADEMY OF SCIENCES, BEIJING, CHINA; MRINAL SINGHA, KEY LABORATORY OF DIGITAL EARTH SCIENCE, INSTITUDE OF REMOTE SENSING AND DIGITAL EARTH, CHINESE ACADEMY OF SCIENCES, BEIJING, CHINA; PRASHANT PATIL, KEY LABORATORY OF DIGITAL EARTH SCIENCE, INSTITUDE OF REMOTE SENSING AND DIGITAL EARTH, CHINESE ACADEMY OF SCIENCES, BEIJING, CHINA; MIAO ZHANG, KEY LABORATORY OF DIGITAL EARTH SCIENCE, INSTITUDE OF REMOTE SENSING AND DIGITAL EARTH, CHINESE ACADEMY OF SCIENCES, BEIJING, CHINA; PIERRE DEFOURNY, UNIVERSITÉ CATHOLIQUE DE LOUVAIN, EARTH AND LIFE INSTITUTE, LOUVAIN-LA-NEUVE, BELGIUM. |
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Título: |
Conflation of expert and crowd reference data to validate global binary thematic maps. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
Remote Sensing of Environment, v. 221, p. 235-246, Feb. 2019. |
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DOI: |
https://doi.org/10.1016/j.rse.2018.10.039 |
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Idioma: |
Inglês |
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Conteúdo: |
With the unprecedented availability of satellite data and the rise of global binary maps, the collection of shared reference data sets should be fostered to allow systematic product benchmarking and validation. Authoritative global reference data are generally collected by experts with regional knowledge through photo-interpretation. During the last decade, crowdsourcing has emerged as an attractive alternative for rapid and relatively cheap data collection, beckoning the increasingly relevant question: can these two data sources be combined to validate thematic maps? In this article, we compared expert and crowd data and assessed their relative agreement for cropland identification, a land cover class often reported as difficult to map. Results indicate that observations from experts and volunteers could be partially conflated provided that several consistency checks are performed. We propose that conflation, i.e., replacement and augmentation of expert observations by crowdsourced observations, should be carried out both at the sampling and data analytics levels. The latter allows to evaluate the reliability of crowdsourced observations and to decide whether they should be conflated or discarded. We demonstrate that the standard deviation of crowdsourced contributions is a simple yet robust indicator of reliability which can effectively inform conflation. Following this criterion, we found that 70% of the expert observations could be crowdsourced with little to no effect on accuracy estimates, allowing a strategic reallocation of the spared expert effort to increase the reliability of the remaining 30% at no additional cost. Finally, we provide a collection of evidence-based recommendations for future hybrid reference data collection campaigns. MenosWith the unprecedented availability of satellite data and the rise of global binary maps, the collection of shared reference data sets should be fostered to allow systematic product benchmarking and validation. Authoritative global reference data are generally collected by experts with regional knowledge through photo-interpretation. During the last decade, crowdsourcing has emerged as an attractive alternative for rapid and relatively cheap data collection, beckoning the increasingly relevant question: can these two data sources be combined to validate thematic maps? In this article, we compared expert and crowd data and assessed their relative agreement for cropland identification, a land cover class often reported as difficult to map. Results indicate that observations from experts and volunteers could be partially conflated provided that several consistency checks are performed. We propose that conflation, i.e., replacement and augmentation of expert observations by crowdsourced observations, should be carried out both at the sampling and data analytics levels. The latter allows to evaluate the reliability of crowdsourced observations and to decide whether they should be conflated or discarded. We demonstrate that the standard deviation of crowdsourced contributions is a simple yet robust indicator of reliability which can effectively inform conflation. Following this criterion, we found that 70% of the expert observations could be crowdsourced with little to no effect o... Mostrar Tudo |
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Palavras-Chave: |
Amostragem sistemática estratificada; Avaliação da precisão; Crowdsourcing; Informação geográfica voluntária; Qualidade dos dados. |
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Thesagro: |
Fotointerpretação. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
LEADER 03404naa a2200589 a 4500
001 2100187
005 2021-11-11
008 2019 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.rse.2018.10.039$2DOI
100 1 $aWALDNER, F.
245 $aConflation of expert and crowd reference data to validate global binary thematic maps.$h[electronic resource]
260 $c2019
520 $aWith the unprecedented availability of satellite data and the rise of global binary maps, the collection of shared reference data sets should be fostered to allow systematic product benchmarking and validation. Authoritative global reference data are generally collected by experts with regional knowledge through photo-interpretation. During the last decade, crowdsourcing has emerged as an attractive alternative for rapid and relatively cheap data collection, beckoning the increasingly relevant question: can these two data sources be combined to validate thematic maps? In this article, we compared expert and crowd data and assessed their relative agreement for cropland identification, a land cover class often reported as difficult to map. Results indicate that observations from experts and volunteers could be partially conflated provided that several consistency checks are performed. We propose that conflation, i.e., replacement and augmentation of expert observations by crowdsourced observations, should be carried out both at the sampling and data analytics levels. The latter allows to evaluate the reliability of crowdsourced observations and to decide whether they should be conflated or discarded. We demonstrate that the standard deviation of crowdsourced contributions is a simple yet robust indicator of reliability which can effectively inform conflation. Following this criterion, we found that 70% of the expert observations could be crowdsourced with little to no effect on accuracy estimates, allowing a strategic reallocation of the spared expert effort to increase the reliability of the remaining 30% at no additional cost. Finally, we provide a collection of evidence-based recommendations for future hybrid reference data collection campaigns.
650 $aFotointerpretação
653 $aAmostragem sistemática estratificada
653 $aAvaliação da precisão
653 $aCrowdsourcing
653 $aInformação geográfica voluntária
653 $aQualidade dos dados
700 1 $aSCHUCKNECHT, A.
700 1 $aLESIV, M.
700 1 $aGALLEGO, J.
700 1 $aSEE, L.
700 1 $aPÉREZ-HOYOS, A.
700 1 $aD'ANDRIMONT, R.
700 1 $aDE MAET, T.
700 1 $aLASO BAYAS, J. C.
700 1 $aFRITZ, S.
700 1 $aLEO, O.
700 1 $aKERDILES, H.
700 1 $aDÍEZ, M.
700 1 $aVAN TRICHT, K.
700 1 $aGILLIAMS, S.
700 1 $aSHELESTOV, A.
700 1 $aLAVRENIUK, M.
700 1 $aSIMÕES, M.
700 1 $aFERRAZ, R. P. D.
700 1 $aBELLÓN, B.
700 1 $aBÉGUÉ, A.
700 1 $aHAZEU, G.
700 1 $aSTONACEK, V.
700 1 $aKOLOMAZNIK, J.
700 1 $aMISUREC, J.
700 1 $aVERÓN, S. R.
700 1 $aABELLEYRA, D. de
700 1 $aPLOTNIKOV, D.
700 1 $aMINGYONG, L.
700 1 $aSINGHA, M.
700 1 $aPATIL, P.
700 1 $aZHANG, M.
700 1 $aDEFOURNY, P.
773 $tRemote Sensing of Environment$gv. 221, p. 235-246, Feb. 2019.
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Embrapa Solos (CNPS) |
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