A crop model-based approach for sunflower yields
Pushed by the Brazilian biodiesel policy, sunflower (Helianthus annuus L.) production is becoming increasingly regarded as an option to boost farmers' income, particularly under semi-arid conditions. Biodiesel related opportunities increase the demand for decision-making information at different levels, which could be met by simulation models. This study aimed to evaluate the performance of the crop model OILCROP-SUN to simulate sunflower development and growth under Brazilian conditions and to explore sunflower water- and nitrogen-limited, water-limited and potential yield and yield variability over an array of sowing dates in the northern region of the state of Minas Gerais, Brazil. For model calibration, an experiment was conducted in which two sunflower genotypes (H358 and E122) were cultivated in a clayey soil. Growth components (leaf area index, above ground biomass, grain yield) and development stages (crop phenology) were measured. A database composed of 27 sunflower experiments from five Brazilian regions was used for model evaluation. The spatial yield distribution of sunflower was mapped using ordinary kriging in ArcGIS. The model simulated sunflower grain productivity satisfactorily (Root Mean Square Error ≈ 13 %). Simulated yields were relatively high (1,750 to 4,250 kg ha-1) and the sowing window was fairly wide (Oct to Feb) for northwestern locations, where sunflower could be cultivated as a second crop (double cropping) at the end of the rainy season. The hybrid H358 had higher yields for all simulated sowing dates, growth conditions and selected locations.
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Escola Superior de Agricultura "Luiz de Queiroz"
2014
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oai:scielo:S0103-901620140005000012014-10-01A crop model-based approach for sunflower yieldsLeite,João Guilherme Dal BeloSilva,João VascoJustino,Flávio BarbosaIttersum,Martin K. van production systems family farms biodiesel crops climate classification Pushed by the Brazilian biodiesel policy, sunflower (Helianthus annuus L.) production is becoming increasingly regarded as an option to boost farmers' income, particularly under semi-arid conditions. Biodiesel related opportunities increase the demand for decision-making information at different levels, which could be met by simulation models. This study aimed to evaluate the performance of the crop model OILCROP-SUN to simulate sunflower development and growth under Brazilian conditions and to explore sunflower water- and nitrogen-limited, water-limited and potential yield and yield variability over an array of sowing dates in the northern region of the state of Minas Gerais, Brazil. For model calibration, an experiment was conducted in which two sunflower genotypes (H358 and E122) were cultivated in a clayey soil. Growth components (leaf area index, above ground biomass, grain yield) and development stages (crop phenology) were measured. A database composed of 27 sunflower experiments from five Brazilian regions was used for model evaluation. The spatial yield distribution of sunflower was mapped using ordinary kriging in ArcGIS. The model simulated sunflower grain productivity satisfactorily (Root Mean Square Error ≈ 13 %). Simulated yields were relatively high (1,750 to 4,250 kg ha-1) and the sowing window was fairly wide (Oct to Feb) for northwestern locations, where sunflower could be cultivated as a second crop (double cropping) at the end of the rainy season. The hybrid H358 had higher yields for all simulated sowing dates, growth conditions and selected locations.info:eu-repo/semantics/openAccessEscola Superior de Agricultura "Luiz de Queiroz"Scientia Agricola v.71 n.5 20142014-10-01info:eu-repo/semantics/articletext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162014000500001en10.1590/0103-9016-2013-0356 |
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Leite,João Guilherme Dal Belo Silva,João Vasco Justino,Flávio Barbosa Ittersum,Martin K. van |
| spellingShingle |
Leite,João Guilherme Dal Belo Silva,João Vasco Justino,Flávio Barbosa Ittersum,Martin K. van A crop model-based approach for sunflower yields |
| author_facet |
Leite,João Guilherme Dal Belo Silva,João Vasco Justino,Flávio Barbosa Ittersum,Martin K. van |
| author_sort |
Leite,João Guilherme Dal Belo |
| title |
A crop model-based approach for sunflower yields |
| title_short |
A crop model-based approach for sunflower yields |
| title_full |
A crop model-based approach for sunflower yields |
| title_fullStr |
A crop model-based approach for sunflower yields |
| title_full_unstemmed |
A crop model-based approach for sunflower yields |
| title_sort |
crop model-based approach for sunflower yields |
| description |
Pushed by the Brazilian biodiesel policy, sunflower (Helianthus annuus L.) production is becoming increasingly regarded as an option to boost farmers' income, particularly under semi-arid conditions. Biodiesel related opportunities increase the demand for decision-making information at different levels, which could be met by simulation models. This study aimed to evaluate the performance of the crop model OILCROP-SUN to simulate sunflower development and growth under Brazilian conditions and to explore sunflower water- and nitrogen-limited, water-limited and potential yield and yield variability over an array of sowing dates in the northern region of the state of Minas Gerais, Brazil. For model calibration, an experiment was conducted in which two sunflower genotypes (H358 and E122) were cultivated in a clayey soil. Growth components (leaf area index, above ground biomass, grain yield) and development stages (crop phenology) were measured. A database composed of 27 sunflower experiments from five Brazilian regions was used for model evaluation. The spatial yield distribution of sunflower was mapped using ordinary kriging in ArcGIS. The model simulated sunflower grain productivity satisfactorily (Root Mean Square Error ≈ 13 %). Simulated yields were relatively high (1,750 to 4,250 kg ha-1) and the sowing window was fairly wide (Oct to Feb) for northwestern locations, where sunflower could be cultivated as a second crop (double cropping) at the end of the rainy season. The hybrid H358 had higher yields for all simulated sowing dates, growth conditions and selected locations. |
| publisher |
Escola Superior de Agricultura "Luiz de Queiroz" |
| publishDate |
2014 |
| url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162014000500001 |
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