Optimization of sowing date and irrigation levels for white oats using the CERES-Barley model

Detalhes bibliográficos
Autor(a) principal: Coelho, Anderson Prates [UNESP]
Data de Publicação: 2021
Outros Autores: de Faria, Rogério Teixeira [UNESP], Leal, Fábio Tiraboschi [UNESP], de Arruda Barbosa, José [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1007/s00484-021-02147-4
http://hdl.handle.net/11449/208689
Resumo: Studies on the use of deficit irrigation and application of models for estimating agronomic performance of crops can help in more sustainable agricultural managements. The objective of this study was to evaluate the effect of irrigation levels on the agronomic performance of white oat (Avena sativa L.) and accuracy of the CERES-Barley model in simulating white oat growth and yield, as well as performing long-term simulation to identify the best sowing time for each irrigation management. The experiment consisted of five irrigation levels (11%, 31%, 60%, 87%, and 100%), being conducted in two agricultural years in southeastern Brazil. The model was calibrated with data of the treatment without water deficit (100%) of the first year and validated with the data of the other treatments in the 2 years. Long-term analyses, with a historical series of 16 years, were performed to recommend the best sowing dates for each irrigation management. Deficit irrigation linearly reduces the agronomic performance of white oat. The high accuracy of white oat yield estimation (R2 = 0.86; RMSE = 616 kg ha−1) using the CERES-Barley model allowed the long-term simulation for establishing the best sowing date for each irrigation level. For higher irrigation levels, sowing in periods with lower temperature (May and June) is more appropriate, as the 1 °C increment in the average temperature before flowering reduces crop yield by 600 kg ha−1. At irrigation levels with higher deficit, sowing in periods with higher rainfall (March and April) promotes higher crop yield.
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spelling Optimization of sowing date and irrigation levels for white oats using the CERES-Barley modelAvena sativa LDSSATGrain yieldModelingSowing timeStudies on the use of deficit irrigation and application of models for estimating agronomic performance of crops can help in more sustainable agricultural managements. The objective of this study was to evaluate the effect of irrigation levels on the agronomic performance of white oat (Avena sativa L.) and accuracy of the CERES-Barley model in simulating white oat growth and yield, as well as performing long-term simulation to identify the best sowing time for each irrigation management. The experiment consisted of five irrigation levels (11%, 31%, 60%, 87%, and 100%), being conducted in two agricultural years in southeastern Brazil. The model was calibrated with data of the treatment without water deficit (100%) of the first year and validated with the data of the other treatments in the 2 years. Long-term analyses, with a historical series of 16 years, were performed to recommend the best sowing dates for each irrigation management. Deficit irrigation linearly reduces the agronomic performance of white oat. The high accuracy of white oat yield estimation (R2 = 0.86; RMSE = 616 kg ha−1) using the CERES-Barley model allowed the long-term simulation for establishing the best sowing date for each irrigation level. For higher irrigation levels, sowing in periods with lower temperature (May and June) is more appropriate, as the 1 °C increment in the average temperature before flowering reduces crop yield by 600 kg ha−1. At irrigation levels with higher deficit, sowing in periods with higher rainfall (March and April) promotes higher crop yield.Department of Rural Engineering School of Agricultural and Veterinarian Sciences São Paulo State University (Unesp), Via de Acesso Prof. Paulo Donato Castellane, s/n, CEPDepartment of Rural Engineering School of Agricultural and Veterinarian Sciences São Paulo State University (Unesp), Via de Acesso Prof. Paulo Donato Castellane, s/n, CEPUniversidade Estadual Paulista (Unesp)Coelho, Anderson Prates [UNESP]de Faria, Rogério Teixeira [UNESP]Leal, Fábio Tiraboschi [UNESP]de Arruda Barbosa, José [UNESP]2021-06-25T11:16:17Z2021-06-25T11:16:17Z2021-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1007/s00484-021-02147-4International Journal of Biometeorology.1432-12540020-7128http://hdl.handle.net/11449/20868910.1007/s00484-021-02147-42-s2.0-85106046332Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengInternational Journal of Biometeorologyinfo:eu-repo/semantics/openAccess2021-10-23T19:02:25Zoai:repositorio.unesp.br:11449/208689Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:27:37.868884Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Optimization of sowing date and irrigation levels for white oats using the CERES-Barley model
title Optimization of sowing date and irrigation levels for white oats using the CERES-Barley model
spellingShingle Optimization of sowing date and irrigation levels for white oats using the CERES-Barley model
Coelho, Anderson Prates [UNESP]
Avena sativa L
DSSAT
Grain yield
Modeling
Sowing time
title_short Optimization of sowing date and irrigation levels for white oats using the CERES-Barley model
title_full Optimization of sowing date and irrigation levels for white oats using the CERES-Barley model
title_fullStr Optimization of sowing date and irrigation levels for white oats using the CERES-Barley model
title_full_unstemmed Optimization of sowing date and irrigation levels for white oats using the CERES-Barley model
title_sort Optimization of sowing date and irrigation levels for white oats using the CERES-Barley model
author Coelho, Anderson Prates [UNESP]
author_facet Coelho, Anderson Prates [UNESP]
de Faria, Rogério Teixeira [UNESP]
Leal, Fábio Tiraboschi [UNESP]
de Arruda Barbosa, José [UNESP]
author_role author
author2 de Faria, Rogério Teixeira [UNESP]
Leal, Fábio Tiraboschi [UNESP]
de Arruda Barbosa, José [UNESP]
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Coelho, Anderson Prates [UNESP]
de Faria, Rogério Teixeira [UNESP]
Leal, Fábio Tiraboschi [UNESP]
de Arruda Barbosa, José [UNESP]
dc.subject.por.fl_str_mv Avena sativa L
DSSAT
Grain yield
Modeling
Sowing time
topic Avena sativa L
DSSAT
Grain yield
Modeling
Sowing time
description Studies on the use of deficit irrigation and application of models for estimating agronomic performance of crops can help in more sustainable agricultural managements. The objective of this study was to evaluate the effect of irrigation levels on the agronomic performance of white oat (Avena sativa L.) and accuracy of the CERES-Barley model in simulating white oat growth and yield, as well as performing long-term simulation to identify the best sowing time for each irrigation management. The experiment consisted of five irrigation levels (11%, 31%, 60%, 87%, and 100%), being conducted in two agricultural years in southeastern Brazil. The model was calibrated with data of the treatment without water deficit (100%) of the first year and validated with the data of the other treatments in the 2 years. Long-term analyses, with a historical series of 16 years, were performed to recommend the best sowing dates for each irrigation management. Deficit irrigation linearly reduces the agronomic performance of white oat. The high accuracy of white oat yield estimation (R2 = 0.86; RMSE = 616 kg ha−1) using the CERES-Barley model allowed the long-term simulation for establishing the best sowing date for each irrigation level. For higher irrigation levels, sowing in periods with lower temperature (May and June) is more appropriate, as the 1 °C increment in the average temperature before flowering reduces crop yield by 600 kg ha−1. At irrigation levels with higher deficit, sowing in periods with higher rainfall (March and April) promotes higher crop yield.
publishDate 2021
dc.date.none.fl_str_mv 2021-06-25T11:16:17Z
2021-06-25T11:16:17Z
2021-01-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1007/s00484-021-02147-4
International Journal of Biometeorology.
1432-1254
0020-7128
http://hdl.handle.net/11449/208689
10.1007/s00484-021-02147-4
2-s2.0-85106046332
url http://dx.doi.org/10.1007/s00484-021-02147-4
http://hdl.handle.net/11449/208689
identifier_str_mv International Journal of Biometeorology.
1432-1254
0020-7128
10.1007/s00484-021-02147-4
2-s2.0-85106046332
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv International Journal of Biometeorology
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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