Previsão de safra de arroz e introdução de um submodelo de brusone no modelo SimulArroz
Autor(a) principal: | |
---|---|
Data de Publicação: | 2020 |
Tipo de documento: | Tese |
Idioma: | por |
Título da fonte: | Manancial - Repositório Digital da UFSM |
Texto Completo: | http://repositorio.ufsm.br/handle/1/23554 |
Resumo: | The objectives of this thesis were (i) to adapt a methodology for rice yield forecast in Rio Grande do Sul – Brazil; (ii). to use hourly hydro-thermal time (HTT) to assess interannual and regional weather variability for rice blast risk in southern Brazil. For the objective (i) it was used Morell’s et al. (2016) yield forecast methodology, adapted for rice using SimulArroz v1.1 rice model, actual and historic weather data. Six different scenarios considering different levels of field information were used, changing number of sowing dates (1 to 4), number of cycle length or cultivars (1 to 3) during four growing seasons (2015 to 2018). Root mean square error (RMSE) comparing actual yield versus simulated yield for Rio Grande do Sul ranged from 618.3 kg ha-1 (8%) to 1024.8 kg ha-1 (13%). The recommended scenario for rice yield forecast was Complex 1 that used 3 sowing dates and the 3 most representative rice cultivars (C1), presenting good forecast predictability (RMSE = 618.3 kg ha-1 or RMSE (%) = 8). For objective (ii) a large data collected from multiple locations and years in southern Brazil were used. For each year x site x cultivar combination, HTT was calculated using hourly data of air temperature, relative humidity and wind speed collected from nearby weather station. The HTT was correlated with blast onset to define a threshold for blast onset. The seasonal HTT between years x sites ranged from 5.1oC h-1 year-1 to 725.3oC h-1 year-1. Blast risk started after HTT of 33.6oC h-1, 66.8oC h-1 and 75.6oC h-1 from Jun 1st until rice emergence (EM) and after HTT of 12.5oC h-1, 55.3oC h-1 and 121.8oC h-1 after EM for susceptible, medium-resistant and resistant cultivar, respectively. Based on the results, it would possible to improve fungicide management using the HTT approach over the calendarization approach, once we would be able to discriminate the cultivar and year influence, the two most important factors on rice blast epidemics. |
id |
UFSM-20_321578987537c80487f158d12e0a103a |
---|---|
oai_identifier_str |
oai:repositorio.ufsm.br:1/23554 |
network_acronym_str |
UFSM-20 |
network_name_str |
Manancial - Repositório Digital da UFSM |
repository_id_str |
3913 |
spelling |
2022-01-17T17:35:56Z2022-01-17T17:35:56Z2020-05-25http://repositorio.ufsm.br/handle/1/23554The objectives of this thesis were (i) to adapt a methodology for rice yield forecast in Rio Grande do Sul – Brazil; (ii). to use hourly hydro-thermal time (HTT) to assess interannual and regional weather variability for rice blast risk in southern Brazil. For the objective (i) it was used Morell’s et al. (2016) yield forecast methodology, adapted for rice using SimulArroz v1.1 rice model, actual and historic weather data. Six different scenarios considering different levels of field information were used, changing number of sowing dates (1 to 4), number of cycle length or cultivars (1 to 3) during four growing seasons (2015 to 2018). Root mean square error (RMSE) comparing actual yield versus simulated yield for Rio Grande do Sul ranged from 618.3 kg ha-1 (8%) to 1024.8 kg ha-1 (13%). The recommended scenario for rice yield forecast was Complex 1 that used 3 sowing dates and the 3 most representative rice cultivars (C1), presenting good forecast predictability (RMSE = 618.3 kg ha-1 or RMSE (%) = 8). For objective (ii) a large data collected from multiple locations and years in southern Brazil were used. For each year x site x cultivar combination, HTT was calculated using hourly data of air temperature, relative humidity and wind speed collected from nearby weather station. The HTT was correlated with blast onset to define a threshold for blast onset. The seasonal HTT between years x sites ranged from 5.1oC h-1 year-1 to 725.3oC h-1 year-1. Blast risk started after HTT of 33.6oC h-1, 66.8oC h-1 and 75.6oC h-1 from Jun 1st until rice emergence (EM) and after HTT of 12.5oC h-1, 55.3oC h-1 and 121.8oC h-1 after EM for susceptible, medium-resistant and resistant cultivar, respectively. Based on the results, it would possible to improve fungicide management using the HTT approach over the calendarization approach, once we would be able to discriminate the cultivar and year influence, the two most important factors on rice blast epidemics.Os objetivos desta tese foram (i) adaptar uma metodologia de previsão de safra para arroz no Rio Grande do Sul – Brasil; (ii). Usar tempo hidrotérmico horário (HTT) para avaliar a variabilidade climática interanual e regional para o risco de ocorrência de brusone em arroz irrigado no Sul do Brasil. Para o objetivo (i) foi utilizada a metodologia de previsão de safra de Morell et al. (2016), e adaptada para arroz irrigado utilizando o modelo SimulArroz v1.1, dados meteorológicos atuais e históricos. Seis cenários foram utilizados considerando níveis de informação, alterando o número de datas de semeadura (1 a 4), número de ciclos e cultivares por safra (1 a 3) durante quatro estações de crescimento (2015 a 2018). A raiz quadrada média do erro (RQME) entre produtividade atual versus produtividade simulada para o Rio Grande do Sul variou de 618.3 kg ha-1 (8%) a 1024.8 kg ha-1 (13%). O cenário recomendado para realizar a previsão de safra de arroz foi o complexo 1, que utilizou 3 datas de semeadura e as 3 cultivares mais representativas em área, apresentando boa previsibilidade de safra (RQME = 618.3 kg ha-1 ou RQME (%) = 8). Para o objetivo (ii) um grande volume de dados foi coletado em múltiplos locais e anos no Sul do Brasil. Para cada combinação de ano x local x cultivar, o tempo hidrotérmico horário foi calculado utilizando temperatura do ar, umidade relativa do ar e velocidade do vento obtidos de estações meteorológicas próximas dos experimentos. A HTT foi correlacionada com o aparecimento dos primeiros sintomas da brusone em arroz para definir limites baseados na HTT. A HTT sazonal entre anos x locais variou de 5.1oC h-1 ano-1 a 725.3oC h-1 ano-1. O risco para brusone iniciou após a HTT atingir 33.6oC h-1, 66.8oC h-1 e 75.6oC h-1 desde primeiro de junho até a emergência do arroz (EM) e após a EM o risco iniciou ao atingir HTT igual ou maior a 12.5oC h-1, 55.3oC h-1 e 121.8oC h-1 para cultivares suscetíveis, médio-resistentes e resistentes, respectivamente. Através desses resultados, surge uma alternativa para manejo de fungicidas utilizando como base a soma hidrotérmica horária em ao invés do manejo baseado em calendário civil, pois através da HTT é possível identificar a variabilidade interanual e de cultivar, os dois fatores mais importantes em epidemias de brusone em arroz.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/openAccessRisco de brusoneManejo integrado de doençasModelagem agrícolaSimulArrozOryza sativaSistemas para decisão e suporteBalanço no fornecimentoRice blastIntegrated management of diseasesCrop modellingSimulArrozOryza sativaDecision support systemsSupply balanceCNPQ::CIENCIAS AGRARIAS::AGRONOMIAPrevisão de safra de arroz e introdução de um submodelo de brusone no modelo SimulArrozRice yield forecast and introduction of blast disease submodel in SimulArroz modelinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisStreck, Nereu Augustohttp://lattes.cnpq.br/8121082379157248Costa, Ivan Francisco Dressler daZanon, Alencar JuniorOgoshi, ClaudioCera, Jossana CeolinSteinmetz, Silviohttp://lattes.cnpq.br/8974429786688486Silva, Michel Rocha da5001000000096006006006006006003b01ed40-f2a9-4cc8-9109-59e6f482b05d5604a7d3-aaf1-47dc-9d11-24bac37f7bd77c192458-1ad6-408b-9816-876d3c54fd227c7b164e-daea-46ed-90e4-44bf948e81888f3bbb51-bc7f-4f8d-8d19-cccb08d721d87d364a3f-f5eb-4898-902f-52c4209fa2db1983d434-8f3d-4650-bfdf-07552d21210freponame:Manancial - Repositório Digital da UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMORIGINALTES_PPGAGRONOMIA_2020_SILVA_MICHEL.pdfTES_PPGAGRONOMIA_2020_SILVA_MICHEL.pdfTese de Doutoradoapplication/pdf3401711http://repositorio.ufsm.br/bitstream/1/23554/1/TES_PPGAGRONOMIA_2020_SILVA_MICHEL.pdfa6cfb15bbcd6e6b15aff5c648a68b783MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805http://repositorio.ufsm.br/bitstream/1/23554/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81956http://repositorio.ufsm.br/bitstream/1/23554/3/license.txt2f0571ecee68693bd5cd3f17c1e075dfMD531/235542022-01-17 14:36:52.233oai:repositorio.ufsm.br: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ório Institucionalhttp://repositorio.ufsm.br/PUBhttp://repositorio.ufsm.br/oai/requestopendoar:39132022-01-17T17:36:52Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM)false |
dc.title.por.fl_str_mv |
Previsão de safra de arroz e introdução de um submodelo de brusone no modelo SimulArroz |
dc.title.alternative.eng.fl_str_mv |
Rice yield forecast and introduction of blast disease submodel in SimulArroz model |
title |
Previsão de safra de arroz e introdução de um submodelo de brusone no modelo SimulArroz |
spellingShingle |
Previsão de safra de arroz e introdução de um submodelo de brusone no modelo SimulArroz Silva, Michel Rocha da Risco de brusone Manejo integrado de doenças Modelagem agrícola SimulArroz Oryza sativa Sistemas para decisão e suporte Balanço no fornecimento Rice blast Integrated management of diseases Crop modelling SimulArroz Oryza sativa Decision support systems Supply balance CNPQ::CIENCIAS AGRARIAS::AGRONOMIA |
title_short |
Previsão de safra de arroz e introdução de um submodelo de brusone no modelo SimulArroz |
title_full |
Previsão de safra de arroz e introdução de um submodelo de brusone no modelo SimulArroz |
title_fullStr |
Previsão de safra de arroz e introdução de um submodelo de brusone no modelo SimulArroz |
title_full_unstemmed |
Previsão de safra de arroz e introdução de um submodelo de brusone no modelo SimulArroz |
title_sort |
Previsão de safra de arroz e introdução de um submodelo de brusone no modelo SimulArroz |
author |
Silva, Michel Rocha da |
author_facet |
Silva, Michel Rocha da |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Streck, Nereu Augusto |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/8121082379157248 |
dc.contributor.advisor-co1.fl_str_mv |
Costa, Ivan Francisco Dressler da |
dc.contributor.referee1.fl_str_mv |
Zanon, Alencar Junior |
dc.contributor.referee2.fl_str_mv |
Ogoshi, Claudio |
dc.contributor.referee3.fl_str_mv |
Cera, Jossana Ceolin |
dc.contributor.referee4.fl_str_mv |
Steinmetz, Silvio |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/8974429786688486 |
dc.contributor.author.fl_str_mv |
Silva, Michel Rocha da |
contributor_str_mv |
Streck, Nereu Augusto Costa, Ivan Francisco Dressler da Zanon, Alencar Junior Ogoshi, Claudio Cera, Jossana Ceolin Steinmetz, Silvio |
dc.subject.por.fl_str_mv |
Risco de brusone Manejo integrado de doenças Modelagem agrícola SimulArroz Oryza sativa Sistemas para decisão e suporte Balanço no fornecimento |
topic |
Risco de brusone Manejo integrado de doenças Modelagem agrícola SimulArroz Oryza sativa Sistemas para decisão e suporte Balanço no fornecimento Rice blast Integrated management of diseases Crop modelling SimulArroz Oryza sativa Decision support systems Supply balance CNPQ::CIENCIAS AGRARIAS::AGRONOMIA |
dc.subject.eng.fl_str_mv |
Rice blast Integrated management of diseases Crop modelling SimulArroz Oryza sativa Decision support systems Supply balance |
dc.subject.cnpq.fl_str_mv |
CNPQ::CIENCIAS AGRARIAS::AGRONOMIA |
description |
The objectives of this thesis were (i) to adapt a methodology for rice yield forecast in Rio Grande do Sul – Brazil; (ii). to use hourly hydro-thermal time (HTT) to assess interannual and regional weather variability for rice blast risk in southern Brazil. For the objective (i) it was used Morell’s et al. (2016) yield forecast methodology, adapted for rice using SimulArroz v1.1 rice model, actual and historic weather data. Six different scenarios considering different levels of field information were used, changing number of sowing dates (1 to 4), number of cycle length or cultivars (1 to 3) during four growing seasons (2015 to 2018). Root mean square error (RMSE) comparing actual yield versus simulated yield for Rio Grande do Sul ranged from 618.3 kg ha-1 (8%) to 1024.8 kg ha-1 (13%). The recommended scenario for rice yield forecast was Complex 1 that used 3 sowing dates and the 3 most representative rice cultivars (C1), presenting good forecast predictability (RMSE = 618.3 kg ha-1 or RMSE (%) = 8). For objective (ii) a large data collected from multiple locations and years in southern Brazil were used. For each year x site x cultivar combination, HTT was calculated using hourly data of air temperature, relative humidity and wind speed collected from nearby weather station. The HTT was correlated with blast onset to define a threshold for blast onset. The seasonal HTT between years x sites ranged from 5.1oC h-1 year-1 to 725.3oC h-1 year-1. Blast risk started after HTT of 33.6oC h-1, 66.8oC h-1 and 75.6oC h-1 from Jun 1st until rice emergence (EM) and after HTT of 12.5oC h-1, 55.3oC h-1 and 121.8oC h-1 after EM for susceptible, medium-resistant and resistant cultivar, respectively. Based on the results, it would possible to improve fungicide management using the HTT approach over the calendarization approach, once we would be able to discriminate the cultivar and year influence, the two most important factors on rice blast epidemics. |
publishDate |
2020 |
dc.date.issued.fl_str_mv |
2020-05-25 |
dc.date.accessioned.fl_str_mv |
2022-01-17T17:35:56Z |
dc.date.available.fl_str_mv |
2022-01-17T17:35:56Z |
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/1/23554 |
url |
http://repositorio.ufsm.br/handle/1/23554 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.cnpq.fl_str_mv |
500100000009 |
dc.relation.confidence.fl_str_mv |
600 600 600 600 600 600 |
dc.relation.authority.fl_str_mv |
3b01ed40-f2a9-4cc8-9109-59e6f482b05d 5604a7d3-aaf1-47dc-9d11-24bac37f7bd7 7c192458-1ad6-408b-9816-876d3c54fd22 7c7b164e-daea-46ed-90e4-44bf948e8188 8f3bbb51-bc7f-4f8d-8d19-cccb08d721d8 7d364a3f-f5eb-4898-902f-52c4209fa2db 1983d434-8f3d-4650-bfdf-07552d21210f |
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:Manancial - Repositório Digital da UFSM instname:Universidade Federal de Santa Maria (UFSM) instacron:UFSM |
instname_str |
Universidade Federal de Santa Maria (UFSM) |
instacron_str |
UFSM |
institution |
UFSM |
reponame_str |
Manancial - Repositório Digital da UFSM |
collection |
Manancial - Repositório Digital da UFSM |
bitstream.url.fl_str_mv |
http://repositorio.ufsm.br/bitstream/1/23554/1/TES_PPGAGRONOMIA_2020_SILVA_MICHEL.pdf http://repositorio.ufsm.br/bitstream/1/23554/2/license_rdf http://repositorio.ufsm.br/bitstream/1/23554/3/license.txt |
bitstream.checksum.fl_str_mv |
a6cfb15bbcd6e6b15aff5c648a68b783 4460e5956bc1d1639be9ae6146a50347 2f0571ecee68693bd5cd3f17c1e075df |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 |
repository.name.fl_str_mv |
Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM) |
repository.mail.fl_str_mv |
|
_version_ |
1794523887420047360 |