Simulation of maize growth under different sowing times and deficit irrigation conditions

Detalhes bibliográficos
Autor(a) principal: Aghayari, Fayaz
Data de Publicação: 2016
Outros Autores: Paknejad, Farzad, Ilkaee, Mohammad Nabi
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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spelling 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||
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