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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
07/07/2009 |
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Data da última atualização: |
26/06/2012 |
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Autoria: |
KITAJIMA, E. W.; MASSOLA JÚNIOR, N. S. |
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Afiliação: |
ELLIOT W. KITAJIMA, ESALQ/USP; NELSON S. MASSOLA JÚNIOR, ESALQ/USP. |
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Título: |
Scanning electron microscopy and in situ immunogold labeling of the corn stunt spiroplasma. |
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Ano de publicação: |
2004 |
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Fonte/Imprenta: |
Summa Phytopathologica, Botucatu, v. 30, n. 4, p. 459-463, Oct./Dec. 2004. |
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Idioma: |
Inglês |
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Conteúdo: |
A report on three dimensional view of the corn stunt spiroplasma - CSS (Spiroplasma kunkelii), the causal agent of corn stunt disease, by scauning electron microscopy of freeze fractured leaves from infected maize(Zea mays) plants is presented. CSS was easily recognized in the sieve tubes because of its characteristic helical shape. The spiroplasma measured 0.2-0.3 um wide and 2-5 um long. In favorable cases it was possible to observe them crossing the sieve pores. Immunogold labeling experiments were carried out in thin sections of aldehyde-fixed and LRWhite-embedded leaf tissues from corn stunt-infected plants, using antibodies produced against pure culture of S. kunkelii. Colloidal gold particles were mostly present on the membrane of the single-membrane bounded corpuscles in the lumen of the sieve tubes, confirrning that they represent S. kunkelii in situ. In some few samples, phage like particles were found either outside or inside the spiroplasma and may represent phages already reported in pure cultures. |
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Palavras-Chave: |
Enfezamento do milho; Espiroplasma; Fago de espiroplasma; Imunocitoquímica in situ; Imunomarcação in situ; Mollicute; Vaso crivado. |
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Thesagro: |
Milho; Zea Mays. |
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Thesaurus Nal: |
Spiroplasma kunkelii. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 01780naa a2200253 a 4500
001 1082951
005 2012-06-26
008 2004 bl uuuu u00u1 u #d
100 1 $aKITAJIMA, E. W.
245 $aScanning electron microscopy and in situ immunogold labeling of the corn stunt spiroplasma.
260 $c2004
520 $aA report on three dimensional view of the corn stunt spiroplasma - CSS (Spiroplasma kunkelii), the causal agent of corn stunt disease, by scauning electron microscopy of freeze fractured leaves from infected maize(Zea mays) plants is presented. CSS was easily recognized in the sieve tubes because of its characteristic helical shape. The spiroplasma measured 0.2-0.3 um wide and 2-5 um long. In favorable cases it was possible to observe them crossing the sieve pores. Immunogold labeling experiments were carried out in thin sections of aldehyde-fixed and LRWhite-embedded leaf tissues from corn stunt-infected plants, using antibodies produced against pure culture of S. kunkelii. Colloidal gold particles were mostly present on the membrane of the single-membrane bounded corpuscles in the lumen of the sieve tubes, confirrning that they represent S. kunkelii in situ. In some few samples, phage like particles were found either outside or inside the spiroplasma and may represent phages already reported in pure cultures.
650 $aSpiroplasma kunkelii
650 $aMilho
650 $aZea Mays
653 $aEnfezamento do milho
653 $aEspiroplasma
653 $aFago de espiroplasma
653 $aImunocitoquímica in situ
653 $aImunomarcação in situ
653 $aMollicute
653 $aVaso crivado
700 1 $aMASSOLA JÚNIOR, N. S.
773 $tSumma Phytopathologica, Botucatu$gv. 30, n. 4, p. 459-463, Oct./Dec. 2004.
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Embrapa Agricultura Digital (CNPTIA) |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
07/01/2020 |
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Data da última atualização: |
04/02/2020 |
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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: |
LI, G.; LU, D.; MORAN, E.; CALVI, M. F.; DUTRA, L. V.; BATISTELLA, M. |
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Afiliação: |
GUIYING LI, Fujian Normal University; DENGSHENG LU, Fujian Normal University, Michigan StateUniversity; EMILIO MORAN, Michigan State University; MIQUÉIAS FREITAS CALVI, UFPA; LUCIANO VIEIRA DUTRA, INPE; MATEUS BATISTELLA, CNPTIA. |
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Título: |
Examining deforestation and agropasture dynamics along the Brazilian TransAmazon Highway using multitemporal Landsat imagery. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
GIScience & Remote Sensing, v. 56, n. 2, p. 161-183, 2019. |
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DOI: |
https://doi.org/10.1080/15481603.2018.1497438 |
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Idioma: |
Inglês |
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Conteúdo: |
This research aims to understand the difference of major land-cover change results caused in various time periods and to examine the impacts of human-induced factors on land-cover changes along the TransAmazon Highway region. The Landsat Thematic Mapper and Operational Land Imager data from 2011, 2014, and 2017 and our previous land-cover classification results in 1991, 2000, and 2008 were used to examine land-cover dynamics. A classification system consisting of five land-cover classes ? primary forest (PF), secondary forest (SF), agropasture (AP), urban area, and water ? were chosen. The hierarchical-based classification method was used to generate land-cover classification results, and the post-classification comparison approach was used to produce detailed ?from-to? conversions for each detection period. The emphasis was on deforestation of PF, dynamic change of SF and AP, and urbanization over time. The impacts of human-induced factors such as population and economic conditions on urban expansion, AP expansion, and deforestation were examined. This research indicated that selection of a suitable time period was critical for effectively detecting land-cover changes; that is, too long time period (i.e., 9 years) cannot accurately capture some land-cover changes such as the AP and SF in this research. Although deforestation ? the conversion from PF to SF and AP ? accounted for a large proportion of land-cover changes, the changes between SF and AP became moreproportion important than PF conversion, and required a short time period (i.e., 3 years here) for effectively reflecting their dynamics. Human-induced factors play important roles in deforestation, dynamic changes between AP and SF, and urbanization. MenosThis research aims to understand the difference of major land-cover change results caused in various time periods and to examine the impacts of human-induced factors on land-cover changes along the TransAmazon Highway region. The Landsat Thematic Mapper and Operational Land Imager data from 2011, 2014, and 2017 and our previous land-cover classification results in 1991, 2000, and 2008 were used to examine land-cover dynamics. A classification system consisting of five land-cover classes ? primary forest (PF), secondary forest (SF), agropasture (AP), urban area, and water ? were chosen. The hierarchical-based classification method was used to generate land-cover classification results, and the post-classification comparison approach was used to produce detailed ?from-to? conversions for each detection period. The emphasis was on deforestation of PF, dynamic change of SF and AP, and urbanization over time. The impacts of human-induced factors such as population and economic conditions on urban expansion, AP expansion, and deforestation were examined. This research indicated that selection of a suitable time period was critical for effectively detecting land-cover changes; that is, too long time period (i.e., 9 years) cannot accurately capture some land-cover changes such as the AP and SF in this research. Although deforestation ? the conversion from PF to SF and AP ? accounted for a large proportion of land-cover changes, the changes between SF and AP became moreproportion imp... Mostrar Tudo |
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Palavras-Chave: |
Agropasture expansion; Cobertura da terra; Human-induced factors; Multitemporal Landsat imagery; Secondary forest; TransAmazon; Transamazônica. |
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Thesagro: |
Desmatamento. |
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Thesaurus NAL: |
Deforestation; Land cover. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02700naa a2200313 a 4500
001 2118287
005 2020-02-04
008 2019 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1080/15481603.2018.1497438$2DOI
100 1 $aLI, G.
245 $aExamining deforestation and agropasture dynamics along the Brazilian TransAmazon Highway using multitemporal Landsat imagery.$h[electronic resource]
260 $c2019
520 $aThis research aims to understand the difference of major land-cover change results caused in various time periods and to examine the impacts of human-induced factors on land-cover changes along the TransAmazon Highway region. The Landsat Thematic Mapper and Operational Land Imager data from 2011, 2014, and 2017 and our previous land-cover classification results in 1991, 2000, and 2008 were used to examine land-cover dynamics. A classification system consisting of five land-cover classes ? primary forest (PF), secondary forest (SF), agropasture (AP), urban area, and water ? were chosen. The hierarchical-based classification method was used to generate land-cover classification results, and the post-classification comparison approach was used to produce detailed ?from-to? conversions for each detection period. The emphasis was on deforestation of PF, dynamic change of SF and AP, and urbanization over time. The impacts of human-induced factors such as population and economic conditions on urban expansion, AP expansion, and deforestation were examined. This research indicated that selection of a suitable time period was critical for effectively detecting land-cover changes; that is, too long time period (i.e., 9 years) cannot accurately capture some land-cover changes such as the AP and SF in this research. Although deforestation ? the conversion from PF to SF and AP ? accounted for a large proportion of land-cover changes, the changes between SF and AP became moreproportion important than PF conversion, and required a short time period (i.e., 3 years here) for effectively reflecting their dynamics. Human-induced factors play important roles in deforestation, dynamic changes between AP and SF, and urbanization.
650 $aDeforestation
650 $aLand cover
650 $aDesmatamento
653 $aAgropasture expansion
653 $aCobertura da terra
653 $aHuman-induced factors
653 $aMultitemporal Landsat imagery
653 $aSecondary forest
653 $aTransAmazon
653 $aTransamazônica
700 1 $aLU, D.
700 1 $aMORAN, E.
700 1 $aCALVI, M. F.
700 1 $aDUTRA, L. V.
700 1 $aBATISTELLA, M.
773 $tGIScience & Remote Sensing$gv. 56, n. 2, p. 161-183, 2019.
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