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Registro Completo |
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Biblioteca(s): |
Embrapa Milho e Sorgo. |
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Data corrente: |
13/03/2000 |
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Data da última atualização: |
28/09/2012 |
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Autoria: |
SILVA, F. F. da; GONCALVES, L. C.; RODRIGUES, J. A. S.; CORREA, C. E. S.; RODRIGUEZ, N. M.; BRITO, A. F.; MOURAO, G. B. |
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Afiliação: |
JOSE AVELINO SANTOS RODRIGUES, CNPMS. |
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Título: |
Qualidade de silagens de híbridos de sorgo (Sorghum bicolor (L.) Moench) de portes baixo, médio e alto com diferentes proporções de colmo+folhas/Panicula. 1. Avaliação do processo fermentativo. |
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Ano de publicação: |
1999 |
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Fonte/Imprenta: |
Revista Brasileira de Zootecnica, Viçosa, v. 28, n. 1, p. 14-20, 1999. |
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Idioma: |
Português |
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Conteúdo: |
O objetivo deste experimento foi avaliar a qualidade fermentativa de silagens de sorgo de portes baixo, medio e alto, com diferentes combinacoes de colmo+folhas/paniculas (100;00, 80;20, 60;40, 40;60, 20;80 e 00;100), por meio de analise laboratoriais. A planta inteira foi utilizada como controle. Os hibridos foram cultivados e ensilados aos 104 dias de idade em silos de laboratorio de PVC, com 10 cm de diametro de 40 cm de comprimento (tres repeticoes por tratamento). Os silos foram abertos aos 56 dias apos a ensilagem. Os teores de materia seca (MS), carboidratos soluveis, nitrogenio amoniacal (N-NH3) e pH foram determinados. As diferencas foram verificadas por intermedio de teste SNK. Os valores de pH das silagens foram, em media, 3,79 e os teores de N-NH3/nitrogenio total foram inferiores a 8% em todos os tratamentos. Os teores de MS das silagens variaram de 19,40 a 49,40%, mas todos os tratamentos conservaram-se bem de acordo com o pH e N-NH3. As densidades dos silos foram maiores que o aumento da participacao da panicula. Os valores de carboidratos soluveis do material original foram baixos para a maioria dos tratamentos, porem isto nao prejudicou a fermentacao da massa ensilada. |
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Palavras-Chave: |
Quality. |
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Thesagro: |
Fermentação; Qualidade; Silagem; Sorghum Bicolor; Sorgo. |
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Thesaurus Nal: |
fermentation; silage. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/67109/1/Qualidade-silagens-5.pdf
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Marc: |
LEADER 02127naa a2200289 a 4500
001 1483491
005 2012-09-28
008 1999 bl uuuu u00u1 u #d
100 1 $aSILVA, F. F. da
245 $aQualidade de silagens de híbridos de sorgo (Sorghum bicolor (L.) Moench) de portes baixo, médio e alto com diferentes proporções de colmo+folhas/Panicula. 1. Avaliação do processo fermentativo.$h[electronic resource]
260 $c1999
520 $aO objetivo deste experimento foi avaliar a qualidade fermentativa de silagens de sorgo de portes baixo, medio e alto, com diferentes combinacoes de colmo+folhas/paniculas (100;00, 80;20, 60;40, 40;60, 20;80 e 00;100), por meio de analise laboratoriais. A planta inteira foi utilizada como controle. Os hibridos foram cultivados e ensilados aos 104 dias de idade em silos de laboratorio de PVC, com 10 cm de diametro de 40 cm de comprimento (tres repeticoes por tratamento). Os silos foram abertos aos 56 dias apos a ensilagem. Os teores de materia seca (MS), carboidratos soluveis, nitrogenio amoniacal (N-NH3) e pH foram determinados. As diferencas foram verificadas por intermedio de teste SNK. Os valores de pH das silagens foram, em media, 3,79 e os teores de N-NH3/nitrogenio total foram inferiores a 8% em todos os tratamentos. Os teores de MS das silagens variaram de 19,40 a 49,40%, mas todos os tratamentos conservaram-se bem de acordo com o pH e N-NH3. As densidades dos silos foram maiores que o aumento da participacao da panicula. Os valores de carboidratos soluveis do material original foram baixos para a maioria dos tratamentos, porem isto nao prejudicou a fermentacao da massa ensilada.
650 $afermentation
650 $asilage
650 $aFermentação
650 $aQualidade
650 $aSilagem
650 $aSorghum Bicolor
650 $aSorgo
653 $aQuality
700 1 $aGONCALVES, L. C.
700 1 $aRODRIGUES, J. A. S.
700 1 $aCORREA, C. E. S.
700 1 $aRODRIGUEZ, N. M.
700 1 $aBRITO, A. F.
700 1 $aMOURAO, G. B.
773 $tRevista Brasileira de Zootecnica, Viçosa$gv. 28, n. 1, p. 14-20, 1999.
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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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