Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiarid environment
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 met...
Ausführliche Beschreibung
Autor*in: |
Yi Liu [verfasserIn] Shenjiao Yang [verfasserIn] Shiqing Li [verfasserIn] Fang Chen [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch ; Spanisch ; Portugiesisch |
Erschienen: |
2012 |
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Schlagwörter: |
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Übergeordnetes Werk: |
In: Scientia Agricola - Universidade de São Paulo, 2004, 69(2012), 5, Seite 300-307 |
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Übergeordnetes Werk: |
volume:69 ; year:2012 ; number:5 ; pages:300-307 |
Links: |
Link aufrufen |
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DOI / URN: |
10.1590/S0103-90162012000500003 |
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Katalog-ID: |
DOAJ044726228 |
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10.1590/S0103-90162012000500003 doi (DE-627)DOAJ044726228 (DE-599)DOAJf8aedf4c5e8e466db0e98b50e16d4ca9 DE-627 ger DE-627 rakwb eng spa por S1-972 Yi Liu verfasserin aut Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiarid environment 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. crop simulation maize model potential productivity water stress spring maize Agriculture (General) Shenjiao Yang verfasserin aut Shiqing Li verfasserin aut Fang Chen verfasserin aut In Scientia Agricola Universidade de São Paulo, 2004 69(2012), 5, Seite 300-307 (DE-627)320569705 (DE-600)2016347-2 1678992X nnns volume:69 year:2012 number:5 pages:300-307 https://doi.org/10.1590/S0103-90162012000500003 kostenfrei https://doaj.org/article/f8aedf4c5e8e466db0e98b50e16d4ca9 kostenfrei http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162012000500003 kostenfrei https://doaj.org/toc/0103-9016 Journal toc kostenfrei https://doaj.org/toc/1678-992X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 69 2012 5 300-307 |
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10.1590/S0103-90162012000500003 doi (DE-627)DOAJ044726228 (DE-599)DOAJf8aedf4c5e8e466db0e98b50e16d4ca9 DE-627 ger DE-627 rakwb eng spa por S1-972 Yi Liu verfasserin aut Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiarid environment 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. crop simulation maize model potential productivity water stress spring maize Agriculture (General) Shenjiao Yang verfasserin aut Shiqing Li verfasserin aut Fang Chen verfasserin aut In Scientia Agricola Universidade de São Paulo, 2004 69(2012), 5, Seite 300-307 (DE-627)320569705 (DE-600)2016347-2 1678992X nnns volume:69 year:2012 number:5 pages:300-307 https://doi.org/10.1590/S0103-90162012000500003 kostenfrei https://doaj.org/article/f8aedf4c5e8e466db0e98b50e16d4ca9 kostenfrei http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162012000500003 kostenfrei https://doaj.org/toc/0103-9016 Journal toc kostenfrei https://doaj.org/toc/1678-992X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 69 2012 5 300-307 |
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10.1590/S0103-90162012000500003 doi (DE-627)DOAJ044726228 (DE-599)DOAJf8aedf4c5e8e466db0e98b50e16d4ca9 DE-627 ger DE-627 rakwb eng spa por S1-972 Yi Liu verfasserin aut Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiarid environment 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. crop simulation maize model potential productivity water stress spring maize Agriculture (General) Shenjiao Yang verfasserin aut Shiqing Li verfasserin aut Fang Chen verfasserin aut In Scientia Agricola Universidade de São Paulo, 2004 69(2012), 5, Seite 300-307 (DE-627)320569705 (DE-600)2016347-2 1678992X nnns volume:69 year:2012 number:5 pages:300-307 https://doi.org/10.1590/S0103-90162012000500003 kostenfrei https://doaj.org/article/f8aedf4c5e8e466db0e98b50e16d4ca9 kostenfrei http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162012000500003 kostenfrei https://doaj.org/toc/0103-9016 Journal toc kostenfrei https://doaj.org/toc/1678-992X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 69 2012 5 300-307 |
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10.1590/S0103-90162012000500003 doi (DE-627)DOAJ044726228 (DE-599)DOAJf8aedf4c5e8e466db0e98b50e16d4ca9 DE-627 ger DE-627 rakwb eng spa por S1-972 Yi Liu verfasserin aut Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiarid environment 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. crop simulation maize model potential productivity water stress spring maize Agriculture (General) Shenjiao Yang verfasserin aut Shiqing Li verfasserin aut Fang Chen verfasserin aut In Scientia Agricola Universidade de São Paulo, 2004 69(2012), 5, Seite 300-307 (DE-627)320569705 (DE-600)2016347-2 1678992X nnns volume:69 year:2012 number:5 pages:300-307 https://doi.org/10.1590/S0103-90162012000500003 kostenfrei https://doaj.org/article/f8aedf4c5e8e466db0e98b50e16d4ca9 kostenfrei http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162012000500003 kostenfrei https://doaj.org/toc/0103-9016 Journal toc kostenfrei https://doaj.org/toc/1678-992X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 69 2012 5 300-307 |
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Yi Liu |
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Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiarid environment |
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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. |
abstractGer |
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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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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Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiarid environment |
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