Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiarid environment

Detalhes bibliográficos
Autor(a) principal: Liu, Yi
Data de Publicação: 2012
Outros Autores: Yang, Shenjiao, Li, Shiqing, Chen, Fang
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Scientia Agrícola (Online)
Texto Completo: https://www.revistas.usp.br/sa/article/view/48812
Resumo: Effects of meteorological variables on crop production can be evaluated using various models. We have evaluated the ability of the Hybrid-Maize model to simulate growth, development and grain yield of maize (Zea mays L.) cultivated on the Loess Plateau, China, and applied it to assess effects of meteorological variations on the performance of maize under rain-fed and irrigated conditions. The model was calibrated and evaluated with data obtained from field experiments performed in 2007 and 2008, then applied to yield determinants using daily weather data for 2005-2009, in simulations under both rain-fed and irrigated conditions. The model accurately simulated Leaf Area Index , biomass, and soil water data from the field experiments in both years, with normalized percentage root mean square errors < 25 %. Gr.Y and yield components were also accurately simulated, with prediction deviations ranging from -2.3 % to 22.0 % for both years. According to the simulations, the maize potential productivity averaged 9.7 t ha-1 under rain-fed conditions and 11.53 t ha-1 under irrigated conditions, and the average rain-fed yield was 1.83 t ha-1 less than the average potential yield with irrigation. Soil moisture status analysis demonstrated that substantial potential yield may have been lost due to water stress under rain-fed conditions.
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spelling Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiarid environmentcrop simulationmaize modelpotential productivitywater stressspring maizeEffects of meteorological variables on crop production can be evaluated using various models. We have evaluated the ability of the Hybrid-Maize model to simulate growth, development and grain yield of maize (Zea mays L.) cultivated on the Loess Plateau, China, and applied it to assess effects of meteorological variations on the performance of maize under rain-fed and irrigated conditions. The model was calibrated and evaluated with data obtained from field experiments performed in 2007 and 2008, then applied to yield determinants using daily weather data for 2005-2009, in simulations under both rain-fed and irrigated conditions. The model accurately simulated Leaf Area Index , biomass, and soil water data from the field experiments in both years, with normalized percentage root mean square errors < 25 %. Gr.Y and yield components were also accurately simulated, with prediction deviations ranging from -2.3 % to 22.0 % for both years. According to the simulations, the maize potential productivity averaged 9.7 t ha-1 under rain-fed conditions and 11.53 t ha-1 under irrigated conditions, and the average rain-fed yield was 1.83 t ha-1 less than the average potential yield with irrigation. Soil moisture status analysis demonstrated that substantial potential yield may have been lost due to water stress under rain-fed conditions.Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz2012-10-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/sa/article/view/4881210.1590/S0103-90162012000500003Scientia Agricola; v. 69 n. 5 (2012); 300-307Scientia Agricola; Vol. 69 Núm. 5 (2012); 300-307Scientia Agricola; Vol. 69 No. 5 (2012); 300-3071678-992X0103-9016reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/sa/article/view/48812/52887Copyright (c) 2015 Scientia Agricolainfo:eu-repo/semantics/openAccessLiu, YiYang, ShenjiaoLi, ShiqingChen, Fang2012-12-21T11:36:26Zoai:revistas.usp.br:article/48812Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2012-12-21T11:36:26Scientia Agrícola (Online) - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiarid environment
title Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiarid environment
spellingShingle Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiarid environment
Liu, Yi
crop simulation
maize model
potential productivity
water stress
spring maize
title_short Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiarid environment
title_full Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiarid environment
title_fullStr Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiarid environment
title_full_unstemmed Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiarid environment
title_sort Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiarid environment
author Liu, Yi
author_facet Liu, Yi
Yang, Shenjiao
Li, Shiqing
Chen, Fang
author_role author
author2 Yang, Shenjiao
Li, Shiqing
Chen, Fang
author2_role author
author
author
dc.contributor.author.fl_str_mv Liu, Yi
Yang, Shenjiao
Li, Shiqing
Chen, Fang
dc.subject.por.fl_str_mv crop simulation
maize model
potential productivity
water stress
spring maize
topic crop simulation
maize model
potential productivity
water stress
spring maize
description Effects of meteorological variables on crop production can be evaluated using various models. We have evaluated the ability of the Hybrid-Maize model to simulate growth, development and grain yield of maize (Zea mays L.) cultivated on the Loess Plateau, China, and applied it to assess effects of meteorological variations on the performance of maize under rain-fed and irrigated conditions. The model was calibrated and evaluated with data obtained from field experiments performed in 2007 and 2008, then applied to yield determinants using daily weather data for 2005-2009, in simulations under both rain-fed and irrigated conditions. The model accurately simulated Leaf Area Index , biomass, and soil water data from the field experiments in both years, with normalized percentage root mean square errors < 25 %. Gr.Y and yield components were also accurately simulated, with prediction deviations ranging from -2.3 % to 22.0 % for both years. According to the simulations, the maize potential productivity averaged 9.7 t ha-1 under rain-fed conditions and 11.53 t ha-1 under irrigated conditions, and the average rain-fed yield was 1.83 t ha-1 less than the average potential yield with irrigation. Soil moisture status analysis demonstrated that substantial potential yield may have been lost due to water stress under rain-fed conditions.
publishDate 2012
dc.date.none.fl_str_mv 2012-10-01
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/48812
10.1590/S0103-90162012000500003
url https://www.revistas.usp.br/sa/article/view/48812
identifier_str_mv 10.1590/S0103-90162012000500003
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://www.revistas.usp.br/sa/article/view/48812/52887
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. 69 n. 5 (2012); 300-307
Scientia Agricola; Vol. 69 Núm. 5 (2012); 300-307
Scientia Agricola; Vol. 69 No. 5 (2012); 300-307
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
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