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.(AU)

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.

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.

Asian soybean rust: modeling the impact on soybean grain yield in the Triângulo Mineiro/Alto Paranaíba region, Minas Gerais, Brazil / Ferrugem asiática da soja: modelagem do impacto na produtividade da soja na região do Triângulo Mineiro/Alto Paranaíba, Minas Gerais, Brasil

Understanding the impact of Asian soybean rust on soybean yield is of great importance in the crop simulation model for this crop become it is possible to predict yield using different sowing dates and growth conditions. The goal of this study were to evaluate the performance of two soybean cultivars in Triângulo Mineiro/Alto Paranaíba, MG, Brazil and the effects of soybean rust on the yield of these cultivars using the CSM-CROPGRO Soybean model. Two soybean cultivars "NK 7074" (early) and "UFUS-Impacta" (medium late), which differ in their development cycles, were growing in Uberaba city during the 2009/2010 growing season. The validation for cultivar "UFUS-Impacta" was conducted comparing the measured and simulated yield data considering three different sowing dates in the "Uberlândia" city during the 2002/2003 growing season. Daily meteorological data obtained from six meteorological stations of the National Institute of Meteorology (INMET). To determine the performance of the soybean cultivars and the effect of soybean rust on yield, three different scenarios were used: no occurrence of rust (NOR) and occurrence of rust with inoculum concentrations of U5.000 and U10.000 urediniospores/mL. For all environments studied, the early cultivar had the best performance than the medium late cultivar. Soybean rust had the most effect on yield for the U10.000 scenario than for the U5.000 scenario. The best soybean performance occurred for "Araxá" and "Uberaba" cities. The SouthSoutheast area of the "Triângulo Mineiro/Alto Paranaíba" region was the most sensitive to the effect of rust on yield compared to the North region.

Compreender o impacto da ferrugem asiática na produtividade da soja é de grande importância para os modelos de simulação dessa cultura, pois pode-se prever a produtividade utilizando-se diferentes datas de semeadura e condições de crescimento. O objetivo deste estudo foi analisar a performance de duas cultivares de soja na região do Triângulo Mineiro/Alto Paranaíba, MG, Brasil e os efeitos da ferrugem asiática da soja na produtividade desses cultivares utilizando o modelo CSM-CROPGRO Soybean. Duas cultivares de soja NK 7074 (precoce) e UFUS-Impacta (semitardia), as quais diferem nos seus ciclos de desenvolvimento, foram cultivadas em Uberaba na safra 2009/2010. A validação para a cultivar UFUS-Impacta foi conduzida comparando os dados observados e simulados de produtividade considerando três diferentes datas de semeadura na safra 2002/2003 em Uberlândia, MG. Foram utilizados dados meteorológicos diários de seis estações meteorológicas do Instituto Nacional de Meteorologia (INMET). Para determinar o desempenho das cultivares de soja e o efeito da ferrugem na produtividade, utilizou-se três diferentes cenários denominados de: não ocorrência de ferrugem (NOR) e ocorrência de ferrugem nas concentrações de inóculo de U5.000 e U10.000 urediniósporos/mL. Para todos os ambientes estudados, a cultivar precoce teve o melhor desempenho em relação a cultivar semi-tardia. A ferrugem da soja teve maior impacto na produção para o cenário U10.000 do que para o cenário U5.000. O melhor desempenho das cultivares de soja foram para as cidades de Araxá e Uberaba. A área Sul-Sudeste do Triângulo Mineiro/Alto Paranaíba foi a mais sensível ao efeito da ferrugem na produtividade em comparação com a região norte.