A crop model-based approach for sunflower yields

Detalhes bibliográficos
Autor(a) principal: Leite, João Guilherme Dal Belo
Data de Publicação: 2014
Outros Autores: Silva, João Vasco, Justino, Flávio Barbosa, Ittersum, Martin K. van
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Scientia Agrícola (Online)
Texto Completo: https://www.revistas.usp.br/sa/article/view/100112
Resumo: Pushed by the Brazilian biodiesel policy, sunflower (Helianthus annuus L.) production is becoming increasingly regarded as an option to boost farmers' income, particularly under semi-arid conditions. Biodiesel related opportunities increase the demand for decision-making information at different levels, which could be met by simulation models. This study aimed to evaluate the performance of the crop model OILCROP-SUN to simulate sunflower development and growth under Brazilian conditions and to explore sunflower water- and nitrogen-limited, water-limited and potential yield and yield variability over an array of sowing dates in the northern region of the state of Minas Gerais, Brazil. For model calibration, an experiment was conducted in which two sunflower genotypes (H358 and E122) were cultivated in a clayey soil. Growth components (leaf area index, above ground biomass, grain yield) and development stages (crop phenology) were measured. A database composed of 27 sunflower experiments from five Brazilian regions was used for model evaluation. The spatial yield distribution of sunflower was mapped using ordinary kriging in ArcGIS. The model simulated sunflower grain productivity satisfactorily (Root Mean Square Error ≈ 13 %). Simulated yields were relatively high (1,750 to 4,250 kg ha-1) and the sowing window was fairly wide (Oct to Feb) for northwestern locations, where sunflower could be cultivated as a second crop (double cropping) at the end of the rainy season. The hybrid H358 had higher yields for all simulated sowing dates, growth conditions and selected locations.
id USP-18_fd77361aadbe61a19f30b4f6b3cbba06
oai_identifier_str oai:revistas.usp.br:article/100112
network_acronym_str USP-18
network_name_str Scientia Agrícola (Online)
repository_id_str
spelling A crop model-based approach for sunflower yields Pushed by the Brazilian biodiesel policy, sunflower (Helianthus annuus L.) production is becoming increasingly regarded as an option to boost farmers' income, particularly under semi-arid conditions. Biodiesel related opportunities increase the demand for decision-making information at different levels, which could be met by simulation models. This study aimed to evaluate the performance of the crop model OILCROP-SUN to simulate sunflower development and growth under Brazilian conditions and to explore sunflower water- and nitrogen-limited, water-limited and potential yield and yield variability over an array of sowing dates in the northern region of the state of Minas Gerais, Brazil. For model calibration, an experiment was conducted in which two sunflower genotypes (H358 and E122) were cultivated in a clayey soil. Growth components (leaf area index, above ground biomass, grain yield) and development stages (crop phenology) were measured. A database composed of 27 sunflower experiments from five Brazilian regions was used for model evaluation. The spatial yield distribution of sunflower was mapped using ordinary kriging in ArcGIS. The model simulated sunflower grain productivity satisfactorily (Root Mean Square Error ≈ 13 %). Simulated yields were relatively high (1,750 to 4,250 kg ha-1) and the sowing window was fairly wide (Oct to Feb) for northwestern locations, where sunflower could be cultivated as a second crop (double cropping) at the end of the rainy season. The hybrid H358 had higher yields for all simulated sowing dates, growth conditions and selected locations. Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz2014-10-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/sa/article/view/10011210.1590/0103-9016-2013-0356Scientia Agricola; v. 71 n. 5 (2014); 345-355Scientia Agricola; Vol. 71 Núm. 5 (2014); 345-355Scientia Agricola; Vol. 71 No. 5 (2014); 345-3551678-992X0103-9016reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/sa/article/view/100112/98785Copyright (c) 2015 Scientia Agricolainfo:eu-repo/semantics/openAccessLeite, João Guilherme Dal BeloSilva, João VascoJustino, Flávio BarbosaIttersum, Martin K. van2015-07-07T19:54:38Zoai:revistas.usp.br:article/100112Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2015-07-07T19:54:38Scientia Agrícola (Online) - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv A crop model-based approach for sunflower yields
title A crop model-based approach for sunflower yields
spellingShingle A crop model-based approach for sunflower yields
Leite, João Guilherme Dal Belo
title_short A crop model-based approach for sunflower yields
title_full A crop model-based approach for sunflower yields
title_fullStr A crop model-based approach for sunflower yields
title_full_unstemmed A crop model-based approach for sunflower yields
title_sort A crop model-based approach for sunflower yields
author Leite, João Guilherme Dal Belo
author_facet Leite, João Guilherme Dal Belo
Silva, João Vasco
Justino, Flávio Barbosa
Ittersum, Martin K. van
author_role author
author2 Silva, João Vasco
Justino, Flávio Barbosa
Ittersum, Martin K. van
author2_role author
author
author
dc.contributor.author.fl_str_mv Leite, João Guilherme Dal Belo
Silva, João Vasco
Justino, Flávio Barbosa
Ittersum, Martin K. van
description Pushed by the Brazilian biodiesel policy, sunflower (Helianthus annuus L.) production is becoming increasingly regarded as an option to boost farmers' income, particularly under semi-arid conditions. Biodiesel related opportunities increase the demand for decision-making information at different levels, which could be met by simulation models. This study aimed to evaluate the performance of the crop model OILCROP-SUN to simulate sunflower development and growth under Brazilian conditions and to explore sunflower water- and nitrogen-limited, water-limited and potential yield and yield variability over an array of sowing dates in the northern region of the state of Minas Gerais, Brazil. For model calibration, an experiment was conducted in which two sunflower genotypes (H358 and E122) were cultivated in a clayey soil. Growth components (leaf area index, above ground biomass, grain yield) and development stages (crop phenology) were measured. A database composed of 27 sunflower experiments from five Brazilian regions was used for model evaluation. The spatial yield distribution of sunflower was mapped using ordinary kriging in ArcGIS. The model simulated sunflower grain productivity satisfactorily (Root Mean Square Error ≈ 13 %). Simulated yields were relatively high (1,750 to 4,250 kg ha-1) and the sowing window was fairly wide (Oct to Feb) for northwestern locations, where sunflower could be cultivated as a second crop (double cropping) at the end of the rainy season. The hybrid H358 had higher yields for all simulated sowing dates, growth conditions and selected locations.
publishDate 2014
dc.date.none.fl_str_mv 2014-10-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://www.revistas.usp.br/sa/article/view/100112
10.1590/0103-9016-2013-0356
url https://www.revistas.usp.br/sa/article/view/100112
identifier_str_mv 10.1590/0103-9016-2013-0356
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://www.revistas.usp.br/sa/article/view/100112/98785
dc.rights.driver.fl_str_mv Copyright (c) 2015 Scientia Agricola
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2015 Scientia Agricola
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz
publisher.none.fl_str_mv Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz
dc.source.none.fl_str_mv Scientia Agricola; v. 71 n. 5 (2014); 345-355
Scientia Agricola; Vol. 71 Núm. 5 (2014); 345-355
Scientia Agricola; Vol. 71 No. 5 (2014); 345-355
1678-992X
0103-9016
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_ 1800222792364326912