Variáveis meteorológicas relacionadas ao início da epidemia causada por Phakopsora pachyrhizi em soja

Detalhes bibliográficos
Autor(a) principal: Silva, Angelica Marian da
Data de Publicação: 2018
Tipo de documento: Tese
Idioma: por
Título da fonte: Biblioteca Digital de Teses e Dissertações do UFSM
Texto Completo: http://repositorio.ufsm.br/handle/1/15387
Resumo: Asian soybean rust is caused by the pathogen Phakopsora pachyrhizi that develops and spreads rapidly under ambient conditions of humidity and temperature. The literature lacks information about the relationship between these factors and the appearance of the first symptom of the disease due mainly to the difficulty of performing this type of field experiment. The objective of this work was to identify which meteorological variables are determinant for the appearance of the first visible symptom of the disease using periods of days prior to Pearson (r) correlation, track analysis and principal component analysis field. The experiment was carried out in the agricultural years of 2015/16 and 2016/17, at the experimental station of the Phytus Institute, located in the municipality of Itaara, RS. The experiment was conducted in randomized blocks, with four replicates, in a factorial 5x2. Factor A consisting of five sowing seasons and factor C by two soybean cultivars. The meteorological observations concerning precipitation and temperature were obtained daily with the help of the automatic surface meteorological station. The cumulative precipitation in mm (PrecAcum), number of days without precipitation (NdSP), number of days with less than one mm (NdM1mm), number of days with precipitation between 1 and 25mm (Nd1-25mm), number of days with precipitation between 26 and 50mm (Nd26-50mm), number of days with precipitation between 51 and 75mm (Nd51-75mm) and referring to temperature were evaluated: mean temperature (NdTemp <15ºC), number of days with minimum temperatures above 15ºC (NdTemp>15ºC), number of days with minimum temperatures between 15-25ºC (NdT15-25ºC), number of days with minimum temperatures below 25ºC (NdTemp<25ºC), and, finally, the average relative humidity (URMédia). The main variable used was the date of the appearance of the first symptom, expressed in days after the emergency (AED). The periods used in the calculation of the meteorological variables were 5, 7, 8, 10, 11, 14 and 20 days prior to the appearance of the first symptom of the disease. Statistical analyzes were performed using Genes, Microsoft Office Excel and Minitab software. It was verified that the cultivars did not present expressive differences as the variables analyzed. The meteorological observations that included periods longer than 10 days were the ones that best characterized the beginning of the epidemic. The precipitation favored the anticipation of the symptoms directly and indirectly through Ndm1mm, Nd26-50mm and the average temperature was determinant in the 2016/17 crop, acting directly and indirectly on the main variable. The meteorological variables of greatest contribution to the appearance of the first symptom of P. pachyrhizi in the soybean crop, identified by the main components technique, were the number of days without precipitation, number of days with less than one mm, number of days with precipitation between 1 and 25mm and 26 and 50mm and number of days with a temperature between 15 and 25ºC.
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spelling 2019-01-17T13:01:54Z2019-01-17T13:01:54Z2018-03-02http://repositorio.ufsm.br/handle/1/15387Asian soybean rust is caused by the pathogen Phakopsora pachyrhizi that develops and spreads rapidly under ambient conditions of humidity and temperature. The literature lacks information about the relationship between these factors and the appearance of the first symptom of the disease due mainly to the difficulty of performing this type of field experiment. The objective of this work was to identify which meteorological variables are determinant for the appearance of the first visible symptom of the disease using periods of days prior to Pearson (r) correlation, track analysis and principal component analysis field. The experiment was carried out in the agricultural years of 2015/16 and 2016/17, at the experimental station of the Phytus Institute, located in the municipality of Itaara, RS. The experiment was conducted in randomized blocks, with four replicates, in a factorial 5x2. Factor A consisting of five sowing seasons and factor C by two soybean cultivars. The meteorological observations concerning precipitation and temperature were obtained daily with the help of the automatic surface meteorological station. The cumulative precipitation in mm (PrecAcum), number of days without precipitation (NdSP), number of days with less than one mm (NdM1mm), number of days with precipitation between 1 and 25mm (Nd1-25mm), number of days with precipitation between 26 and 50mm (Nd26-50mm), number of days with precipitation between 51 and 75mm (Nd51-75mm) and referring to temperature were evaluated: mean temperature (NdTemp <15ºC), number of days with minimum temperatures above 15ºC (NdTemp>15ºC), number of days with minimum temperatures between 15-25ºC (NdT15-25ºC), number of days with minimum temperatures below 25ºC (NdTemp<25ºC), and, finally, the average relative humidity (URMédia). The main variable used was the date of the appearance of the first symptom, expressed in days after the emergency (AED). The periods used in the calculation of the meteorological variables were 5, 7, 8, 10, 11, 14 and 20 days prior to the appearance of the first symptom of the disease. Statistical analyzes were performed using Genes, Microsoft Office Excel and Minitab software. It was verified that the cultivars did not present expressive differences as the variables analyzed. The meteorological observations that included periods longer than 10 days were the ones that best characterized the beginning of the epidemic. The precipitation favored the anticipation of the symptoms directly and indirectly through Ndm1mm, Nd26-50mm and the average temperature was determinant in the 2016/17 crop, acting directly and indirectly on the main variable. The meteorological variables of greatest contribution to the appearance of the first symptom of P. pachyrhizi in the soybean crop, identified by the main components technique, were the number of days without precipitation, number of days with less than one mm, number of days with precipitation between 1 and 25mm and 26 and 50mm and number of days with a temperature between 15 and 25ºC.A ferrugem asiática da soja é causada pelo patógeno Phakopsora pachyrhizi que se desenvolve e dissemina-se rapidamente em condições ambientais ideias de umidade e temperatura. A literatura carece de informações sobre a relação existente entre esses fatores e o aparecimento do primeiro sintoma da doença devido, principalmente, a dificuldade de realização deste tipo de experimento a campo. Com auxílio das metodologias estatísticas de correlação de Pearson (r), análise de trilha e análise de componentes principais (ACP) o objetivo desse trabalho foi identificar quais variáveis meteorológicas são determinantes para o aparecimento do primeiro sintoma visível da doença utilizando períodos de dias anteriores a sua identificação a campo. O experimento foi realizado nos anos agrícolas de 2015/16 e 2016/17, na estação experimental do Instituto Phytus, localizada no município de Itaara, RS. O experimento foi conduzido em blocos ao acaso, com quatro repetições, em um fatorial 5x2. O fator A constituído por cinco épocas de semeadura e o fator C por duas cultivares de soja. As observações meteorológicas referentes a precipitação e temperatura, foram obtidas diariamente com auxílio da estação meteorológica de superfície automática. As variáveis explicativas avaliadas, referentes a precipitação, foram: precipitação acumulada em milímetros (mm) (PrecAcum), número de dias sem precipitação (NdSP), número de dias com menos de um mm (NdM1mm), número de dias com precipitação entre 1 e 25mm (Nd1-25mm), número de dias com precipitação entre 26 e 50mm (Nd26-50mm), número de dias com precipitação entre 51 e 75mm (Nd51-75mm) e referentes a temperatura, foram avaliadas: temperatura mínima média do período (TempMédia), número de dias com temperatura mínima entre 15-25ºC (NdT15-25ºC), número de dias com temperaturas mínimas inferiores a 15ºC (NdTemp<15ºC), número de dias com temperaturas mínimas superiores a 25ºC (NdTemp>25ºC), e por fim, a umidade relativa média (URMédia). A variável principal utilizada foi a data do aparecimento do primeiro sintoma, expressa em dias após a emergência (DAE). Os períodos utilizados no cálculo das variáveis meteorológicas foram 5, 7, 8, 10, 11, 14 e 20 dias anteriores ao aparecimento do primeiro sintoma da doença. As análises estatísticas foram realizadas com auxílio do software Genes, Microsoft OfficeExcel e Minitab. Verificou-se que as cultivares não apresentaram diferenças expressivas quanto as variáveis analisadas. As observações meteorológicas que compreenderam períodos superiores a 10 dias foram as que melhor caracterizaram o início da epidemia. A precipitação favoreceu a antecipação dos sintomas de forma direta e indiretamente através Ndm1mm, Nd26-50mm e a temperatura mínima média foi determinante na safra 2016/17 atuando direta e indiretamente sobre a variável principal. As variáveis meteorológicas de maior contribuição para o aparecimento do primeiro sintoma de P. pachyrhizi na cultura da soja, identificadas pela técnica de componentes principais, foram o número de dias sem precipitação, número de dias com menos de um mm, número de dias com precipitação entre 1 e 25mm e 26 e 50mm e número de dias com temperatura entre 15 e 25ºC.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESporUniversidade Federal de Santa MariaCentro de Ciências RuraisPrograma de Pós-Graduação em AgronomiaUFSMBrasilAgronomiaAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessFerrugem asiáticaTemperaturaPrecipitaçãoAnálise de trilhaAnálise de componentes principaisAsian rustTemperaturePrecipitationPath analysisPrincipal component analysisCNPQ::CIENCIAS AGRARIAS::AGRONOMIAVariáveis meteorológicas relacionadas ao início da epidemia causada por Phakopsora pachyrhizi em sojaAnalysis of meteorological observations related to the appearance of the first symptom caused by Phakopsora pachyrhizi in soybeaninfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisLúcio, Alessandro Dal'Colhttp://lattes.cnpq.br/0972869223145503Costa, Ivan Francisco Dressler dahttp://lattes.cnpq.br/6426393869748708Balardin, Ricardo Silveirohttp://lattes.cnpq.br/6547445501940321Ruviaro, Claitonhttp://lattes.cnpq.br/3706288232300725Madalosso, Marcelo Gripahttp://lattes.cnpq.br/2188468950480104http://lattes.cnpq.br/7751879669041121Silva, Angelica Marian da500100000009600d51ee404-e7f0-41c1-bf30-c5fa02c4e509c33b1447-0081-478b-99c1-2f4a4b5a57ccc829a1ba-7182-4747-8ba2-ecf7c08a2b888bd40d26-8b20-4123-ba27-e45f40a9ab98c0b2a118-0c9e-43e5-b654-3d2fff1693a4e0816eea-fab5-42ec-a983-17c55833c257reponame:Biblioteca Digital de Teses e Dissertações do UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMORIGINALTES_PPGAGRONOMIA_2018_SILVA_ANGELICA.pdfTES_PPGAGRONOMIA_2018_SILVA_ANGELICA.pdfTese de Doutoradoapplication/pdf7041585http://repositorio.ufsm.br/bitstream/1/15387/1/TES_PPGAGRONOMIA_2018_SILVA_ANGELICA.pdf9b3c1b43ea821f486ce29aeb88662dafMD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; 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dc.title.por.fl_str_mv Variáveis meteorológicas relacionadas ao início da epidemia causada por Phakopsora pachyrhizi em soja
dc.title.alternative.eng.fl_str_mv Analysis of meteorological observations related to the appearance of the first symptom caused by Phakopsora pachyrhizi in soybean
title Variáveis meteorológicas relacionadas ao início da epidemia causada por Phakopsora pachyrhizi em soja
spellingShingle Variáveis meteorológicas relacionadas ao início da epidemia causada por Phakopsora pachyrhizi em soja
Silva, Angelica Marian da
Ferrugem asiática
Temperatura
Precipitação
Análise de trilha
Análise de componentes principais
Asian rust
Temperature
Precipitation
Path analysis
Principal component analysis
CNPQ::CIENCIAS AGRARIAS::AGRONOMIA
title_short Variáveis meteorológicas relacionadas ao início da epidemia causada por Phakopsora pachyrhizi em soja
title_full Variáveis meteorológicas relacionadas ao início da epidemia causada por Phakopsora pachyrhizi em soja
title_fullStr Variáveis meteorológicas relacionadas ao início da epidemia causada por Phakopsora pachyrhizi em soja
title_full_unstemmed Variáveis meteorológicas relacionadas ao início da epidemia causada por Phakopsora pachyrhizi em soja
title_sort Variáveis meteorológicas relacionadas ao início da epidemia causada por Phakopsora pachyrhizi em soja
author Silva, Angelica Marian da
author_facet Silva, Angelica Marian da
author_role author
dc.contributor.advisor1.fl_str_mv Lúcio, Alessandro Dal'Col
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/0972869223145503
dc.contributor.referee1.fl_str_mv Costa, Ivan Francisco Dressler da
dc.contributor.referee1Lattes.fl_str_mv http://lattes.cnpq.br/6426393869748708
dc.contributor.referee2.fl_str_mv Balardin, Ricardo Silveiro
dc.contributor.referee2Lattes.fl_str_mv http://lattes.cnpq.br/6547445501940321
dc.contributor.referee3.fl_str_mv Ruviaro, Claiton
dc.contributor.referee3Lattes.fl_str_mv http://lattes.cnpq.br/3706288232300725
dc.contributor.referee4.fl_str_mv Madalosso, Marcelo Gripa
dc.contributor.referee4Lattes.fl_str_mv http://lattes.cnpq.br/2188468950480104
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/7751879669041121
dc.contributor.author.fl_str_mv Silva, Angelica Marian da
contributor_str_mv Lúcio, Alessandro Dal'Col
Costa, Ivan Francisco Dressler da
Balardin, Ricardo Silveiro
Ruviaro, Claiton
Madalosso, Marcelo Gripa
dc.subject.por.fl_str_mv Ferrugem asiática
Temperatura
Precipitação
Análise de trilha
Análise de componentes principais
topic Ferrugem asiática
Temperatura
Precipitação
Análise de trilha
Análise de componentes principais
Asian rust
Temperature
Precipitation
Path analysis
Principal component analysis
CNPQ::CIENCIAS AGRARIAS::AGRONOMIA
dc.subject.eng.fl_str_mv Asian rust
Temperature
Precipitation
Path analysis
Principal component analysis
dc.subject.cnpq.fl_str_mv CNPQ::CIENCIAS AGRARIAS::AGRONOMIA
description Asian soybean rust is caused by the pathogen Phakopsora pachyrhizi that develops and spreads rapidly under ambient conditions of humidity and temperature. The literature lacks information about the relationship between these factors and the appearance of the first symptom of the disease due mainly to the difficulty of performing this type of field experiment. The objective of this work was to identify which meteorological variables are determinant for the appearance of the first visible symptom of the disease using periods of days prior to Pearson (r) correlation, track analysis and principal component analysis field. The experiment was carried out in the agricultural years of 2015/16 and 2016/17, at the experimental station of the Phytus Institute, located in the municipality of Itaara, RS. The experiment was conducted in randomized blocks, with four replicates, in a factorial 5x2. Factor A consisting of five sowing seasons and factor C by two soybean cultivars. The meteorological observations concerning precipitation and temperature were obtained daily with the help of the automatic surface meteorological station. The cumulative precipitation in mm (PrecAcum), number of days without precipitation (NdSP), number of days with less than one mm (NdM1mm), number of days with precipitation between 1 and 25mm (Nd1-25mm), number of days with precipitation between 26 and 50mm (Nd26-50mm), number of days with precipitation between 51 and 75mm (Nd51-75mm) and referring to temperature were evaluated: mean temperature (NdTemp <15ºC), number of days with minimum temperatures above 15ºC (NdTemp>15ºC), number of days with minimum temperatures between 15-25ºC (NdT15-25ºC), number of days with minimum temperatures below 25ºC (NdTemp<25ºC), and, finally, the average relative humidity (URMédia). The main variable used was the date of the appearance of the first symptom, expressed in days after the emergency (AED). The periods used in the calculation of the meteorological variables were 5, 7, 8, 10, 11, 14 and 20 days prior to the appearance of the first symptom of the disease. Statistical analyzes were performed using Genes, Microsoft Office Excel and Minitab software. It was verified that the cultivars did not present expressive differences as the variables analyzed. The meteorological observations that included periods longer than 10 days were the ones that best characterized the beginning of the epidemic. The precipitation favored the anticipation of the symptoms directly and indirectly through Ndm1mm, Nd26-50mm and the average temperature was determinant in the 2016/17 crop, acting directly and indirectly on the main variable. The meteorological variables of greatest contribution to the appearance of the first symptom of P. pachyrhizi in the soybean crop, identified by the main components technique, were the number of days without precipitation, number of days with less than one mm, number of days with precipitation between 1 and 25mm and 26 and 50mm and number of days with a temperature between 15 and 25ºC.
publishDate 2018
dc.date.issued.fl_str_mv 2018-03-02
dc.date.accessioned.fl_str_mv 2019-01-17T13:01:54Z
dc.date.available.fl_str_mv 2019-01-17T13:01:54Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/doctoralThesis
format doctoralThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://repositorio.ufsm.br/handle/1/15387
url http://repositorio.ufsm.br/handle/1/15387
dc.language.iso.fl_str_mv por
language por
dc.relation.cnpq.fl_str_mv 500100000009
dc.relation.confidence.fl_str_mv 600
dc.relation.authority.fl_str_mv d51ee404-e7f0-41c1-bf30-c5fa02c4e509
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dc.rights.driver.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Universidade Federal de Santa Maria
Centro de Ciências Rurais
dc.publisher.program.fl_str_mv Programa de Pós-Graduação em Agronomia
dc.publisher.initials.fl_str_mv UFSM
dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv Agronomia
publisher.none.fl_str_mv Universidade Federal de Santa Maria
Centro de Ciências Rurais
dc.source.none.fl_str_mv reponame:Biblioteca Digital de Teses e Dissertações do UFSM
instname:Universidade Federal de Santa Maria (UFSM)
instacron:UFSM
instname_str Universidade Federal de Santa Maria (UFSM)
instacron_str UFSM
institution UFSM
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