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Registro Completo |
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Biblioteca(s): |
Embrapa Meio Ambiente. |
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Data corrente: |
01/08/2017 |
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Data da última atualização: |
14/11/2017 |
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Tipo da produção científica: |
Resumo em Anais de Congresso |
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Autoria: |
HECK, D. W.; RODRIGUEZ, M. A. D.; DEL PONTE, E. M.; MIZUBUTI, E. S. G. |
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Afiliação: |
D. W. HECK, UFV; MIGUEL ANGEL DITA RODRIGUEZ, CNPMF; E. M. DEL PONTE; E. S. G. MIZUBUTI, UFV. |
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Título: |
Spatial pattern analysis of the incidence of Fusarium wilt of banana. |
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Ano de publicação: |
2016 |
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Fonte/Imprenta: |
In: WORKSHOP BRASILEIRO DE EPIDEMIOLOGIA DE DOENÇAS DE PLANTAS, 5., 2016, Cruz das Almas. Resumos de palestras... Cruz das Almas: Embrapa; Adab; UFRB; Ceplac; Uesb; 2016. Pôsteres. |
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Idioma: |
Inglês |
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Conteúdo: |
Fusarium wilt (FW), caused by the soil-borne fungus Fusarium oxysporum f. sp. cubense , is a highly destructive disease and a major threat to the banana industry. Understanding how FW epidemics develop is key to establish efficient management strategies. Epidemiological factors such as weevil borer, wind, water and cultural practices have been suggested to affect epidemics. Temporal and spatial patterns of FW remain poorly investigated worldwide and no study was conducted in Brazil. This work aimed to assess the incidence and the spatial pattern of FW for gaining understanding about epidemic processes. Fourteen fields planted to ?Maçã? (Silk, AAB) or ?Prata Mineira? (Pome, AAB) located at four banana-producing regions of the states of São Paulo and Paraná were inspected from March to July of 2016. In each field, all plants were visually assessed and diseased plants were geo-referenced using a handheld GPS device. FW incidence was calculated as the proportion of diseased plants in the field. The total number of plants/field was estimated based on the number of rows and spacing of plants within rows. Incidence maps were made based on the geo-referenced data. A quadrat-based, using three sizes of quadrats, and a point-process distance-based method were used to detect the within-field spatial pattern. Due the various shapes and sizes of the fields, the number of quadrats ranged from 100 to 259, 27 to 73 and from 5 to 19, from the smallest to greatest quadrat size. For the quadrat data, the null hypothesis of complete spatial randomness (CSR) was tested using a Pearson ?2 statistics. For the point-process data, the Kolmogorov-Smirnov (KS) test was used to compare the observed and expected distributions under a function T (specified as both the x and y coordinates of the diseased plant in the field). Finally, to investigate the spatial dependence between neighbors, the L-function was used to test for deviations from randomness. The analyses were conducted using the spatstat package of R. The FW incidence ranged from 2.1 to 38.5% across the fields. ?Prata Mineira? was least affected, on average (8.9%), than ?Maçã? (17.2%). CRS was rejected for all fields when using the two smallest quadrat size, suggesting aggregation. CRS was not rejected for three ?Maçã? fields (11, 14 and 15) when using the largest quadrat size. The K-S test did not reject the hypothesis of CSR for two fields (8 and 11). The L-function suggested aggregated patterns for the most fields. There was greater spatial dependence for ?Prata Mineira? than ?Maçã?. Spatial patterns were congruent among the methods and the spatial pattern of FW varied with banana cultivar. MenosFusarium wilt (FW), caused by the soil-borne fungus Fusarium oxysporum f. sp. cubense , is a highly destructive disease and a major threat to the banana industry. Understanding how FW epidemics develop is key to establish efficient management strategies. Epidemiological factors such as weevil borer, wind, water and cultural practices have been suggested to affect epidemics. Temporal and spatial patterns of FW remain poorly investigated worldwide and no study was conducted in Brazil. This work aimed to assess the incidence and the spatial pattern of FW for gaining understanding about epidemic processes. Fourteen fields planted to ?Maçã? (Silk, AAB) or ?Prata Mineira? (Pome, AAB) located at four banana-producing regions of the states of São Paulo and Paraná were inspected from March to July of 2016. In each field, all plants were visually assessed and diseased plants were geo-referenced using a handheld GPS device. FW incidence was calculated as the proportion of diseased plants in the field. The total number of plants/field was estimated based on the number of rows and spacing of plants within rows. Incidence maps were made based on the geo-referenced data. A quadrat-based, using three sizes of quadrats, and a point-process distance-based method were used to detect the within-field spatial pattern. Due the various shapes and sizes of the fields, the number of quadrats ranged from 100 to 259, 27 to 73 and from 5 to 19, from the smallest to greatest quadrat size. For the quadra... Mostrar Tudo |
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Thesagro: |
Banana; Fusarium. |
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Categoria do assunto: |
H Saúde e Patologia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/162233/1/heck-spatial.pdf
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Marc: |
LEADER 03314nam a2200169 a 4500
001 2073403
005 2017-11-14
008 2016 bl uuuu u00u1 u #d
100 1 $aHECK, D. W.
245 $aSpatial pattern analysis of the incidence of Fusarium wilt of banana.$h[electronic resource]
260 $aIn: WORKSHOP BRASILEIRO DE EPIDEMIOLOGIA DE DOENÇAS DE PLANTAS, 5., 2016, Cruz das Almas. Resumos de palestras... Cruz das Almas: Embrapa; Adab; UFRB; Ceplac; Uesb; 2016. Pôsteres.$c2016
520 $aFusarium wilt (FW), caused by the soil-borne fungus Fusarium oxysporum f. sp. cubense , is a highly destructive disease and a major threat to the banana industry. Understanding how FW epidemics develop is key to establish efficient management strategies. Epidemiological factors such as weevil borer, wind, water and cultural practices have been suggested to affect epidemics. Temporal and spatial patterns of FW remain poorly investigated worldwide and no study was conducted in Brazil. This work aimed to assess the incidence and the spatial pattern of FW for gaining understanding about epidemic processes. Fourteen fields planted to ?Maçã? (Silk, AAB) or ?Prata Mineira? (Pome, AAB) located at four banana-producing regions of the states of São Paulo and Paraná were inspected from March to July of 2016. In each field, all plants were visually assessed and diseased plants were geo-referenced using a handheld GPS device. FW incidence was calculated as the proportion of diseased plants in the field. The total number of plants/field was estimated based on the number of rows and spacing of plants within rows. Incidence maps were made based on the geo-referenced data. A quadrat-based, using three sizes of quadrats, and a point-process distance-based method were used to detect the within-field spatial pattern. Due the various shapes and sizes of the fields, the number of quadrats ranged from 100 to 259, 27 to 73 and from 5 to 19, from the smallest to greatest quadrat size. For the quadrat data, the null hypothesis of complete spatial randomness (CSR) was tested using a Pearson ?2 statistics. For the point-process data, the Kolmogorov-Smirnov (KS) test was used to compare the observed and expected distributions under a function T (specified as both the x and y coordinates of the diseased plant in the field). Finally, to investigate the spatial dependence between neighbors, the L-function was used to test for deviations from randomness. The analyses were conducted using the spatstat package of R. The FW incidence ranged from 2.1 to 38.5% across the fields. ?Prata Mineira? was least affected, on average (8.9%), than ?Maçã? (17.2%). CRS was rejected for all fields when using the two smallest quadrat size, suggesting aggregation. CRS was not rejected for three ?Maçã? fields (11, 14 and 15) when using the largest quadrat size. The K-S test did not reject the hypothesis of CSR for two fields (8 and 11). The L-function suggested aggregated patterns for the most fields. There was greater spatial dependence for ?Prata Mineira? than ?Maçã?. Spatial patterns were congruent among the methods and the spatial pattern of FW varied with banana cultivar.
650 $aBanana
650 $aFusarium
700 1 $aRODRIGUEZ, M. A. D.
700 1 $aDEL PONTE, E. M.
700 1 $aMIZUBUTI, E. S. G.
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Registro original: |
Embrapa Meio Ambiente (CNPMA) |
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Registro |
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Registro Completo
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Biblioteca(s): |
Embrapa Solos. |
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Data corrente: |
12/03/2002 |
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Data da última atualização: |
20/04/2021 |
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Autoria: |
ARAUJO FILHO, J. C. de; LOPES, O. F.; OLIVEIRA NETO, M. B. de; NOGUEIRA, L. R. Q.; BARRETO, A. C. |
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Afiliação: |
JOSE COELHO DE ARAUJO FILHO, CNPS; OSVALDO FERREIRA LOPES, CNPS; MANOEL BATISTA DE OLIVEIRA NETO, CNPS; LÚCIA RAQUEL QUEIROZ NOGUEIRA, CNPS; ANTÔNIO CARLOS BARRETO, CNPS. |
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Título: |
Levantamento de reconhecimento de média intensidade dos solos da região dos Tabuleiros Costeiros e da Baixada Litorânea do Estado de Sergipe. |
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Ano de publicação: |
1999 |
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Fonte/Imprenta: |
Rio de Janeiro: Embrapa Solos, 1999. |
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Volume: |
2 v. |
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Série: |
(Embrapa Solos. Boletim de pesquisa, 4). |
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ISSN: |
1517-5219 |
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Idioma: |
Português |
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Conteúdo: |
1. Introdução; 2.Características gerais da área estudada; 3. Métodos de trabalho: Prospecção e cartografia dos solos, Métodos de análise do solo; 4. Solos: critérios adotados para subdivisão de classes de solos e fases empregadas; Descrição das classes de solos; 5. Correlação da classificação de solos em vigor e o novo sistema de classificação de solos. 6. Conclusões. |
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Palavras-Chave: |
Baixada Litoranea; Perfil; Profile; Sergipe; Soil survey; Tabuleiros Costeiros. |
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Thesagro: |
Levantamento; Reconhecimento do solo; Solo. |
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Thesaurus NAL: |
Brazil. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/157543/1/Boletim-de-Pesquisa-4-1999.pdf
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Marc: |
LEADER 01308nam a2200313 a 4500
001 1336935
005 2021-04-20
008 1999 bl uuuu 00u1 u #d
022 $a1517-5219
100 1 $aARAUJO FILHO, J. C. de
245 $aLevantamento de reconhecimento de média intensidade dos solos da região dos Tabuleiros Costeiros e da Baixada Litorânea do Estado de Sergipe.
260 $aRio de Janeiro: Embrapa Solos$c1999
300 $a2 v.
490 $a(Embrapa Solos. Boletim de pesquisa, 4).$v2 v.
520 $a1. Introdução; 2.Características gerais da área estudada; 3. Métodos de trabalho: Prospecção e cartografia dos solos, Métodos de análise do solo; 4. Solos: critérios adotados para subdivisão de classes de solos e fases empregadas; Descrição das classes de solos; 5. Correlação da classificação de solos em vigor e o novo sistema de classificação de solos. 6. Conclusões.
650 $aBrazil
650 $aLevantamento
650 $aReconhecimento do solo
650 $aSolo
653 $aBaixada Litoranea
653 $aPerfil
653 $aProfile
653 $aSergipe
653 $aSoil survey
653 $aTabuleiros Costeiros
700 1 $aLOPES, O. F.
700 1 $aOLIVEIRA NETO, M. B. de
700 1 $aNOGUEIRA, L. R. Q.
700 1 $aBARRETO, A. C.
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