Utilization of the cropgro-soybean model to estimate yield loss caused by Asian rust in cultivars with different cycle

Rodrigues, Rui; Pedrini, João Eduardo; Fraisse, Clyde W.; Fernandes, J. M. C.; Justino, Flávio; Heinemann, A. B.; Costa, Luiz Cláudio; Vale, Francisco

doi:10.1590/s0006-87052012000200021

Cited by 14 publications

(5 citation statements)

References 24 publications

(23 reference statements)

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“…The genetic coefficients have been selected [21] to be the same group that the maturing soybean cultivars used in this study. The author determined the genetic coefficients in three cultivars, two seasons with four sowing dates, and additionally used the GLUE (Generalized Likelihood Uncertainty Estimation) methodology of DSSAT 4.5 to verify the estimation of genetic coefficients.…”

Section: Parameterization and Evaluation Modelmentioning

confidence: 99%

Modeling of Soybean under Present and Future Climates in Mozambique

Talacuece

Justino

Rodrigues

et al. 2016

Climate

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This study aims to calibrate and validate the generic crop model (CROPGRO-Soybean) and estimate the soybean yield, considering simulations with different sowing times for the current period (1990-2013) and future climate scenario (2014-2030). The database used came from observed data, nine climate models of CORDEX (Coordinated Regional climate Downscaling Experiment)-Africa framework and MERRA (Modern Era Retrospective-Analysis for Research and Applications) reanalysis. The calibration and validation data for the model were acquired in field experiments, carried out in the 2009/2010 and 2010/2011 growing seasons in the experimental area of the International Institute of Tropical Agriculture (IITA) in Angónia, Mozambique. The yield of two soybean cultivars: Tgx 1740-2F and Tgx 1908-8F was evaluated in the experiments and modeled for two distinct CO 2 concentrations. Our model simulation results indicate that the fertilization effect leads to yield gains for both cultivars, ranging from 11.4% (Tgx 1908-8F) to 15% (Tgx 1740-2Fm) when compared to the performance of those cultivars under current CO 2 atmospheric concentration. Moreover, our results show that MERRA, the RegCM4 (Regional Climatic Model version 4) and CNRM-CM5 (Centre National de Recherches Météorologiques-Climatic Model version 5) models provided more accurate estimates of yield, while others models underestimate yield as compared to observations, a fact that was demonstrated to be related to the model's capability of reproducing the precipitation and the surface radiation amount.

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Section: Parameterization and Evaluation Modelmentioning

confidence: 99%

Modeling of Soybean under Present and Future Climates in Mozambique

Talacuece

Justino

Rodrigues

et al. 2016

Climate

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“…Solar radiation values were estimated following the methodology presented by Allen et al (1998). Information about soil texture and soil organic carbon throughout the soil profile of the experimental site was obtained from Rodrigues et al (2013).…”

Section: Model Calibrationmentioning

confidence: 99%

A crop model-based approach for sunflower yields

Leite

Silva

Justino

et al. 2014

Sci. agric. (Piracicaba, Braz.)

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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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“…Contudo, o aumento da produtividade de soja está sujeito a riscos associados às variações do clima e neste sentido pesquisas indicam que as projeções climáticas apontam para impactos na produtividade bem como para uma nova geografia da sua produção (Bhatia, 2008;Assad, 2007;Rodrigues et al 2012;Pinto e Assad, 2008). O impacto na produtividade poderá ser acentuado quando fenômenos atmosférico-oceânicos, associados às variações do clima são considerados, tornando fatores de limitação para altos rendimentos (da Rocha et al, 2014;Erasmi et al, 2014; Nóia Júnior e Sentelhas, 2019), nitidamente pelo aumento da temperatura do ar e alternados quadros de regimes de precipitação que afetam o desenvolvimento da cultura.…”

Section: Introductionunclassified

Caracterização da variabilidade da precipitação no MATOPIBA, região produtora de soja

Reis

Silva

Bezerra

et al. 2020

Rev. Bras. Geog. Fis.

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A análise sobre a variabilidade dos padrões climatológicos espaciais e temporais das chuvas fornecem informações valiosas para a condução de cultivos agrícolas, principalmente em condições de sequeiro. Assim, o presente estudo objetivou caracterizar a variabilidade da precipitação no MATOPIBA, região produtora de soja, sob influência das fases do ENSO e do gradiente térmico do Atlântico Tropical. Foram utilizados dados diários de precipitação do período de 1980-2013 dispostos em uma grade de espaçamento de 0,25º x 0,25°, abrangendo 963 pontos sobre a região. O acumulado mensal da precipitação foi especializado por meio de sistemas geográficos de informação e da geoestatística. A variabilidade da precipitação foi analisada por meio da aplicação do teste de Mann-Kendall, considerando três cenários de condições meteorológicas (climatologia, favorável-wet e desfavorável-dry) à ocorrência da precipitação. Os volumes de chuvas foram relativamente maiores no cenário da fase fria do ENSO combinado com o gradiente inter-hemisférico apontando para o Sul (favorável-wet), em contrapartida, verificou-se um aumento de condições de risco hídrico nos anos com ocorrência da fase quente do ENSO e o gradiente apontando para o Norte (desfavorável-dry), embora com exceções registradas em algumas áreas no mês de Janeiro e Fevereiro. Tendências positivas e negativas foram identificadas, constatando indícios de alterações nos padrões da variável, previamente para os cenários da climatologia e desfavorável (dry). Os resultados poderão contribuir para o desenvolvimento de soluções e direcionamento na tomada de decisões pelos agentes da cadeia produtiva que visem a mitigação de impactos em decorrência da variabilidade da precipitação na região estudada. Characterization of rainfall variability in the MATOPIBA, soybean producing region AbstractThe analysis of spatial and temporal rainfall patterns variability provides invaluable information for the development of dryland agriculture systems. Therefore, the aim of the present study was to characterize the variability of rainfall in the MATOPIBA, an important soybean producing region, under the influence of ENSO phases and the tropical Atlantic thermal gradient. We used daily rainfall data for the period from 1980-2013 arranged in a 0.25º x 0.25º spacing grid, comprising 963 points over the study region. Monthly accumulated rainfall has been specialized through geographic information systems and geostatistics. Variability rainfall was analyzed by applying the Mann-Kendall test, considering three scenarios of meteorological conditions (climatology, favorable-wet and unfavorable-dry) to the occurrence of precipitation. Rainfall volumes were relatively higher in the ENSO cold phase scenario combined with the southward-favorable interhemispheric gradient. ENSO and the gradient pointing north (unfavorable-dry), although with exceptions recorded in some areas in January and February. Positive and negative trends were identified, showing evidence of changes in the variable's patterns, previously for the climatology and unfavorable (dry) scenarios. The results may contribute to the development of solutions and decision making direction by the agents of the productive chain aiming at mitigating impacts due to the variability of precipitation in the studied region.Keywords: Climate variability; ENSO; Agrometeorology

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Utilization of the cropgro-soybean model to estimate yield loss caused by Asian rust in cultivars with different cycle

Cited by 14 publications

References 24 publications

Modeling of Soybean under Present and Future Climates in Mozambique

Modeling of Soybean under Present and Future Climates in Mozambique

A crop model-based approach for sunflower yields

Caracterização da variabilidade da precipitação no MATOPIBA, região produtora de soja

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