Simulation of maize growth under different sowing times and deficit irrigation conditions
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Bioscience journal (Online) |
Texto Completo: | https://seer.ufu.br/index.php/biosciencejournal/article/view/33239 |
Resumo: | Simulation models of crops are referred as an efficient complement for the experimental study. Also crop simulation models can be useful for making appropriate decisions on agricultural systems. So this study aimed to simulate the growth of maize under different sowing times and deficit irrigation conditions, using the Decision Support System for Agrotechnology Transfer (DSSAT) model in 2014 year. This study was conducted in the research field of Islamic Azad University of Karaj in 2013 year. The experiment was designed in a split-block with four replications. Treatments included four sowing times of April 30 (S1), May 20 (S2), June 10 (S3), and June 27 (S4) in the main plots and three irrigation levels of 40% available water depletion (W1), 60% available water depletion (W2), and 80% available water depletion in the sub-plots. Root Mean Square Error (RMSE) of grain yield for all four sowing times on three levels of irrigation in Karaj region varied from 581.43 to 1,990.81 kg per hectare. It was also calculated the model efficiency coefficient (d) ranged 0.87-0.98 for the trait. The RMSE of the total dry matter was determined 861.88-2,173.66 kg per hectare; that was while R2 (1:1) of total dry weight varied 0.89-0.98. The results indicate that the model's ability to predict dry matter yield of maize is good enough. |
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Simulation of maize growth under different sowing times and deficit irrigation conditions MaizeCERES-Maize modelYieldSimulationAgricultural SciencesSimulation models of crops are referred as an efficient complement for the experimental study. Also crop simulation models can be useful for making appropriate decisions on agricultural systems. So this study aimed to simulate the growth of maize under different sowing times and deficit irrigation conditions, using the Decision Support System for Agrotechnology Transfer (DSSAT) model in 2014 year. This study was conducted in the research field of Islamic Azad University of Karaj in 2013 year. The experiment was designed in a split-block with four replications. Treatments included four sowing times of April 30 (S1), May 20 (S2), June 10 (S3), and June 27 (S4) in the main plots and three irrigation levels of 40% available water depletion (W1), 60% available water depletion (W2), and 80% available water depletion in the sub-plots. Root Mean Square Error (RMSE) of grain yield for all four sowing times on three levels of irrigation in Karaj region varied from 581.43 to 1,990.81 kg per hectare. It was also calculated the model efficiency coefficient (d) ranged 0.87-0.98 for the trait. The RMSE of the total dry matter was determined 861.88-2,173.66 kg per hectare; that was while R2 (1:1) of total dry weight varied 0.89-0.98. The results indicate that the model's ability to predict dry matter yield of maize is good enough. EDUFU2016-10-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://seer.ufu.br/index.php/biosciencejournal/article/view/3323910.14393/BJ-v32n5a2016-33239Bioscience Journal ; Vol. 32 No. 5 (2016): Sept./Oct.; 1204-1212Bioscience Journal ; v. 32 n. 5 (2016): Sept./Oct.; 1204-12121981-3163reponame:Bioscience journal (Online)instname:Universidade Federal de Uberlândia (UFU)instacron:UFUenghttps://seer.ufu.br/index.php/biosciencejournal/article/view/33239/19007Brazil; ContemporaryCopyright (c) 2016 Fayaz Aghayari, Farzad Paknejad, Mohammad Nabi Ilkaeehttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessAghayari, FayazPaknejad, FarzadIlkaee, Mohammad Nabi2022-02-21T14:38:52Zoai:ojs.www.seer.ufu.br:article/33239Revistahttps://seer.ufu.br/index.php/biosciencejournalPUBhttps://seer.ufu.br/index.php/biosciencejournal/oaibiosciencej@ufu.br||1981-31631516-3725opendoar:2022-02-21T14:38:52Bioscience journal (Online) - Universidade Federal de Uberlândia (UFU)false |
dc.title.none.fl_str_mv |
Simulation of maize growth under different sowing times and deficit irrigation conditions |
title |
Simulation of maize growth under different sowing times and deficit irrigation conditions |
spellingShingle |
Simulation of maize growth under different sowing times and deficit irrigation conditions Aghayari, Fayaz Maize CERES-Maize model Yield Simulation Agricultural Sciences |
title_short |
Simulation of maize growth under different sowing times and deficit irrigation conditions |
title_full |
Simulation of maize growth under different sowing times and deficit irrigation conditions |
title_fullStr |
Simulation of maize growth under different sowing times and deficit irrigation conditions |
title_full_unstemmed |
Simulation of maize growth under different sowing times and deficit irrigation conditions |
title_sort |
Simulation of maize growth under different sowing times and deficit irrigation conditions |
author |
Aghayari, Fayaz |
author_facet |
Aghayari, Fayaz Paknejad, Farzad Ilkaee, Mohammad Nabi |
author_role |
author |
author2 |
Paknejad, Farzad Ilkaee, Mohammad Nabi |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Aghayari, Fayaz Paknejad, Farzad Ilkaee, Mohammad Nabi |
dc.subject.por.fl_str_mv |
Maize CERES-Maize model Yield Simulation Agricultural Sciences |
topic |
Maize CERES-Maize model Yield Simulation Agricultural Sciences |
description |
Simulation models of crops are referred as an efficient complement for the experimental study. Also crop simulation models can be useful for making appropriate decisions on agricultural systems. So this study aimed to simulate the growth of maize under different sowing times and deficit irrigation conditions, using the Decision Support System for Agrotechnology Transfer (DSSAT) model in 2014 year. This study was conducted in the research field of Islamic Azad University of Karaj in 2013 year. The experiment was designed in a split-block with four replications. Treatments included four sowing times of April 30 (S1), May 20 (S2), June 10 (S3), and June 27 (S4) in the main plots and three irrigation levels of 40% available water depletion (W1), 60% available water depletion (W2), and 80% available water depletion in the sub-plots. Root Mean Square Error (RMSE) of grain yield for all four sowing times on three levels of irrigation in Karaj region varied from 581.43 to 1,990.81 kg per hectare. It was also calculated the model efficiency coefficient (d) ranged 0.87-0.98 for the trait. The RMSE of the total dry matter was determined 861.88-2,173.66 kg per hectare; that was while R2 (1:1) of total dry weight varied 0.89-0.98. The results indicate that the model's ability to predict dry matter yield of maize is good enough. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-10-06 |
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://seer.ufu.br/index.php/biosciencejournal/article/view/33239 10.14393/BJ-v32n5a2016-33239 |
url |
https://seer.ufu.br/index.php/biosciencejournal/article/view/33239 |
identifier_str_mv |
10.14393/BJ-v32n5a2016-33239 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://seer.ufu.br/index.php/biosciencejournal/article/view/33239/19007 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2016 Fayaz Aghayari, Farzad Paknejad, Mohammad Nabi Ilkaee https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2016 Fayaz Aghayari, Farzad Paknejad, Mohammad Nabi Ilkaee https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.coverage.none.fl_str_mv |
Brazil; Contemporary |
dc.publisher.none.fl_str_mv |
EDUFU |
publisher.none.fl_str_mv |
EDUFU |
dc.source.none.fl_str_mv |
Bioscience Journal ; Vol. 32 No. 5 (2016): Sept./Oct.; 1204-1212 Bioscience Journal ; v. 32 n. 5 (2016): Sept./Oct.; 1204-1212 1981-3163 reponame:Bioscience journal (Online) instname:Universidade Federal de Uberlândia (UFU) instacron:UFU |
instname_str |
Universidade Federal de Uberlândia (UFU) |
instacron_str |
UFU |
institution |
UFU |
reponame_str |
Bioscience journal (Online) |
collection |
Bioscience journal (Online) |
repository.name.fl_str_mv |
Bioscience journal (Online) - Universidade Federal de Uberlândia (UFU) |
repository.mail.fl_str_mv |
biosciencej@ufu.br|| |
_version_ |
1797069076491665408 |