On tactical crop management using seasonal climate forecasts and simulation modelling: a case study for wheat
Autor(a) principal: | |
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Data de Publicação: | 1997 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Scientia Agrícola (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90161997000300014 |
Resumo: | The El Niño/Southern Oscillation phenomenon strongly influences rainfall distribution around the world. Using phases of the Southern Oscillation Index (SOI) allows a probabilistic forecast of future rainfall that can be useful to managers of agricultural systems. Using wheat as an example, we show in this study how the SOI phase system, when combined with a cropping systems simulation capability, can be used operationally to Improve tactical crop management and hence increase farm profits and/or decrease production risks. We show the validity of the approach for two contrasting locations, namely Dalby in Northern Australian and Piracicaba in Brazil At Dalby, highest median yields were achieved following a rapidly rising SOI phase in April/May and lowest median yields following a consistently negative phase. Conversely, highest median yields at Piracicaba followed a near zero April/May phase and lowest median yields when the phase was consistently positive. We show how tactical management options can range from crop or cultivar choice to nitrogen management and marketing of the future wheat crop. |
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Scientia Agrícola (Online) |
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On tactical crop management using seasonal climate forecasts and simulation modelling: a case study for wheatclimatic variabilitycrop and systems modellingcrop production forecastsThe El Niño/Southern Oscillation phenomenon strongly influences rainfall distribution around the world. Using phases of the Southern Oscillation Index (SOI) allows a probabilistic forecast of future rainfall that can be useful to managers of agricultural systems. Using wheat as an example, we show in this study how the SOI phase system, when combined with a cropping systems simulation capability, can be used operationally to Improve tactical crop management and hence increase farm profits and/or decrease production risks. We show the validity of the approach for two contrasting locations, namely Dalby in Northern Australian and Piracicaba in Brazil At Dalby, highest median yields were achieved following a rapidly rising SOI phase in April/May and lowest median yields following a consistently negative phase. Conversely, highest median yields at Piracicaba followed a near zero April/May phase and lowest median yields when the phase was consistently positive. We show how tactical management options can range from crop or cultivar choice to nitrogen management and marketing of the future wheat crop.Escola Superior de Agricultura "Luiz de Queiroz"1997-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90161997000300014Scientia Agricola v.54 n.spe 1997reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USP10.1590/S0103-90161997000300014info:eu-repo/semantics/openAccessMeinke,H.Stone,R.C.eng2005-05-31T00:00:00Zoai:scielo:S0103-90161997000300014Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2005-05-31T00:00Scientia Agrícola (Online) - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
On tactical crop management using seasonal climate forecasts and simulation modelling: a case study for wheat |
title |
On tactical crop management using seasonal climate forecasts and simulation modelling: a case study for wheat |
spellingShingle |
On tactical crop management using seasonal climate forecasts and simulation modelling: a case study for wheat Meinke,H. climatic variability crop and systems modelling crop production forecasts |
title_short |
On tactical crop management using seasonal climate forecasts and simulation modelling: a case study for wheat |
title_full |
On tactical crop management using seasonal climate forecasts and simulation modelling: a case study for wheat |
title_fullStr |
On tactical crop management using seasonal climate forecasts and simulation modelling: a case study for wheat |
title_full_unstemmed |
On tactical crop management using seasonal climate forecasts and simulation modelling: a case study for wheat |
title_sort |
On tactical crop management using seasonal climate forecasts and simulation modelling: a case study for wheat |
author |
Meinke,H. |
author_facet |
Meinke,H. Stone,R.C. |
author_role |
author |
author2 |
Stone,R.C. |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Meinke,H. Stone,R.C. |
dc.subject.por.fl_str_mv |
climatic variability crop and systems modelling crop production forecasts |
topic |
climatic variability crop and systems modelling crop production forecasts |
description |
The El Niño/Southern Oscillation phenomenon strongly influences rainfall distribution around the world. Using phases of the Southern Oscillation Index (SOI) allows a probabilistic forecast of future rainfall that can be useful to managers of agricultural systems. Using wheat as an example, we show in this study how the SOI phase system, when combined with a cropping systems simulation capability, can be used operationally to Improve tactical crop management and hence increase farm profits and/or decrease production risks. We show the validity of the approach for two contrasting locations, namely Dalby in Northern Australian and Piracicaba in Brazil At Dalby, highest median yields were achieved following a rapidly rising SOI phase in April/May and lowest median yields following a consistently negative phase. Conversely, highest median yields at Piracicaba followed a near zero April/May phase and lowest median yields when the phase was consistently positive. We show how tactical management options can range from crop or cultivar choice to nitrogen management and marketing of the future wheat crop. |
publishDate |
1997 |
dc.date.none.fl_str_mv |
1997-06-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90161997000300014 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90161997000300014 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S0103-90161997000300014 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Escola Superior de Agricultura "Luiz de Queiroz" |
publisher.none.fl_str_mv |
Escola Superior de Agricultura "Luiz de Queiroz" |
dc.source.none.fl_str_mv |
Scientia Agricola v.54 n.spe 1997 reponame:Scientia Agrícola (Online) instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Scientia Agrícola (Online) |
collection |
Scientia Agrícola (Online) |
repository.name.fl_str_mv |
Scientia Agrícola (Online) - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
scientia@usp.br||alleoni@usp.br |
_version_ |
1748936455767457792 |