Eficiência do modelo Ceres-Maize na simulação do desempenho de híbridos de milho

O modelo Ceres-Maize foi desenvolvido para simulação do desenvolvimento e desempenho da cultura do milho e tem sido utilizado como ferramenta de auxílio no planejamento das safras e tomadas de decisões pelos agricultores de diversos países. Com o objetivo de avaliar a eficiência do modelo Ceres-Maize na simulação do desempenho de híbridos de milho nas condições tropicais, foi conduzido um experimento utilizando cinco híbridos (AG7000, AG8060, DKB199, GNZ2004 e P30F90) avaliados em três épocas de semeadura (24/11/2006, 19/12/2006 e 13/01/2007) na Universidade Federal de Lavras, Lavras, MG. O delineamento foi o DBC com três repetições. Avaliaram-se datas de florescimento e maturidade fisiológica, número de grãos por metro quadrado, massa de grãos e produtividade de grãos, que foram comparados com os dados simulados pelo quadrado médio do erro (RSME), porcentagem de desvio (PD) e índice de concordância (d). Os resultados indicaram que o milho semeado em janeiro apresentou menores valores de número de grãos por metro quadrado, massa de grão e produtividade de grãos do que semeaduras em novembro e dezembro. O Ceres-Maize mostrou-se muito eficiente para simular as datas de florescimento e de maturidade fisiológica em razão dos valores de RSME terem sido inferiores a 10%, os de 'd' superiores a 0,80 e o maior valor de PD -11%. Para o número de grãos por metro quadrado, massa de grãos e produtividade de grãos, a simulação foi considerada boa com valores de RSME inferiores a 20%. Para essas variáveis foram observados maiores valores de PD, principalmente na última época de semeadura, evidenciando que condições ambientais não favoráveis ao bom desempenho da cultura afetam a eficiência da simulação. O modelo Ceres-Maize mostrou ser boa ferramenta de simulação das características agronômicas de híbridos de milho.

Aplicação do modelo CERES-maize na análise de estratégias de irrigação para milho "safrinha" em Londrina-PR

Usando-se a capacidade do modelo CERES-maize de simular o crescimento do milho sob várias condições de ambiente e manejo, foram analisadas estratégias de irrigação para o milho "safrinha", em diferentes épocas de semeadura, em Londrina - PR. Os tratamentos simulados constituíram-se no cultivo da cultivar de milho XL-520, em 12 épocas de semeaduras, no período de janeiro a abril, adotando-se cinco critérios para aplicação de irrigação, além de um nível sem irrigação e outro de produção potencial. Para as simulações, foram utilizados os dados meteorológicos da série histórica disponível para o local, características do solo predominante da região e manejo, seguindo as recomendações técnicas regionais para o cultivo. Os resultados revelaram que a irrigação foi uma alternativa viável, pois elevou notoriamente o rendimento em todas as épocas de semeadura, variando, em média, entre 5.800 e 8.000 kg ha-1, reduzindo os riscos de estabelecimento e frustração de safra para essa cultivar. Em todos os níveis, a irrigação resultou em rendimentos mais estáveis ao longo de todo o período de análise, em relação à condição sem irrigação, exceto no primeiro decêndio de janeiro.

Simulação do rendimento e riscos climáticos para o milho safrinha em Londrina - PR, utilizando o modelo CERES-Maize

Modelos matemáticos possibilitam simular realisticamente o crescimento e o desenvolvimento fenológico de culturas sob ampla gama de condições ambientais e de manejo, a um baixo custo. O objetivo deste trabalho foi investigar os efeitos da época de semeadura no estabelecimento e rendimento do milho safrinha para Londrina - PR, mediante simulações de longo período com o modelo CERES. Os tratamentos consistiram na combinação de 12 épocas de semeadura, uma em cada decêndio, de janeiro a abril, sob dois cenários: sem limitação hídrica (produção potencial) e com limitação hídrica, considerando-se uma cultivar de ciclo precoce, XL-520, durante 24 anos. Os resultados mostraram decréscimos de rendimentos de até 38% da produtividade potencial e de 44% da produtividade sob restrição hídrica à medida que se atrasou a semeadura, devido à coincidência dos períodos críticos de desenvolvimento com condições subótimas de radiação solar, temperatura e disponibilidade hídrica. Observaram-se aumentos na duração do ciclo de 120 a 140 dias quando o milho foi semeado em janeiro e de 160 a 170 dias para semeadura em abril. O ciclo mais longo influiu na seqüência de cultivos e semeaduras após o terceiro decêndio de março, só permitindo o cultivo da cultura de verão após outubro. Também houve tendência de aumento de falhas no estabelecimento do cultivo, devido à deficiência hídrica, à medida que se atrasou a semeadura. Há risco de geadas de 4% para os cultivos semeados em final de março e 8% para os semeados em abril.

Simulation of within field variability of corn yield with Ceres-Maize model

The CERES-Maize model was used to estimate the spatial variability in corn (Zea mays L.) yield for 1995 and 1996 using data measured on soil profiles located on a 30.5 m grid within a 3.9 ha field in Michigan. The model was calibrated for one grid profile for the 1995 and then used to simulate corn yield for all grid points for the 2 yrs. For the calibration for 1995, the model predicted corn yield within 2%. For 1995, the model predicted yield variability very well (r(2) = 0.85), producing similar yield maps with differences generally within +/- 300 kg ha(-1). For 1996, the model predicted low grain yields (1167 kg ha(-1)) compared with measured (8928 kg ha(-1)) because the model does not account for horizontal water movement within the landscape or water contributions from a water table. Under nonlimiting water conditions, the model performed well (average of 8717 vs. 8948 kg ha(-1)) but under-estimated the measured yield variability.

Parametrização e avaliação do modelo CSM-Ceres-Maize para cultivares de milho recomendadas para a microrregião de Pelotas, RS.

Os objetivos deste trabalho foram parametrizar o modelo CSM-CERES-Maize para diferentes cultivares e avaliar o desempenho das simulações do modelo. Para a parametrização do modelo, foi conduzido ensaio irrigado, na estação experimental da Embrapa Clima Temperado, localizada no município de Pelotas, RS, onde foram utilizadas as cultivares Amarelão, AL 30, AG 5011 e AG 122. Um segundo ensaio, em regime de sequeiro, com as cultivares Amarelão e AL 30, foi conduzido para se avaliar a capacidade preditiva do modelo em Canguçu, RS. A qualidade das simulações foi avaliada estatisticamente empregando-se o índice ?d? de concordância e o quadrado médio do erro, RMSE. Valores de RMSE e de ?d? indicaram simulações de boa qualidade e adequado índice de concordância para a simulação da produtividade de grãos nos ensaios de parametrização e avaliação do modelo. Os melhores valores de RMSE e de ?d? para a fitomassa seca da parte aérea foram observados para a cultivar AG 5011 no ensaio de parametrização e para a variedade AL 30 no ensaio de avaliação do modelo. Nos ensaios, para todas as cultivares, as simulações do número de folhas foram consideradas excelentes.

Parametrização do modelo CSM-CERES-Maize para uma cultivar de alta produtividade.

2016

The impact of El Nino Southern Oscillation phases on off-season maize yield for a subtropical region of Brazil

In recent years, maize has become one of the main alternative crops for the autumn winter growing season in the central-western and southeastern regions of Brazil. However, water deficits, sub-optimal temperatures and low solar radiation levels are common problems that are experienced during this growing season by local farmers. One methodology to assess the impact of variable weather conditions on crop production is the use of crop simulation models. The goal of this study was to evaluate the effect of climate variability on maize yield for a subtropical region of Brazil. Specific objectives for this study were (1) to analyse the effect of El Nino Southern Oscillation (ENSO) on precipitation and air temperature for four locations in the state of Sao Paulo and (2) to analyse the impact of ENSO on maize grown off-season for the same four locations using a crop simulation model. For each site, historical weather data were categorised as belonging to one of three phases of ENSO: El Nino (warm sea surface temperature anomalies in the Pacific), La Nina (cool sea surface temperature anomalies) or neutral, based on an index derived from observed sea surface temperature anomalies. During El Nino, there is a tendency for an increase in the rainfall amount during May for the four selected locations, and also during April, mainly in three of the locations, resulting in an increase in simulated maize yield planted between February 15 and March 15. In general, there was a decrease in the simulated yield for maize grown off-season during neutral years. This study showed how a crop model can be used to assess the impact of climate variability on the yield of maize grown off-season in a subtropical region of Brazil. The outcomes of this study can be very useful for both policy makers and local farmers for agricultural planning and decision making. Copyright (C) 2009 Royal Meteorological Society

Improved methods for predicting individual leaf area and leaf senescence in maize (Zea mays)

The ability to predict leaf area and leaf area index is crucial in crop simulation models that predict crop growth and yield. Previous studies have shown existing methods of predicting leaf area to be inadequate when applied to a broad range of cultivars with different numbers of leaves. The objectives of the study were to (i) develop generalised methods of modelling individual and total plant leaf area, and leaf senescence, that do not require constants that are specific to environments and/or genotypes, (ii) re-examine the base, optimum, and maximum temperatures for calculation of thermal time for leaf senescence, and (iii) assess the method of calculation of individual leaf area from leaf length and leaf width in experimental work. Five cultivars of maize differing widely in maturity and adaptation were planted in October 1994 in south-eastern Queensland, and grown under non-limiting conditions of water and plant nutrient supplies. Additional data for maize plants with low total leaf number (12-17) grown at Katumani Research Centre, Kenya, were included to extend the range in the total leaf number per plant. The equation for the modified (slightly skewed) bell curve could be generalised for modelling individual leaf area, as all coefficients in it were related to total leaf number. Use of coefficients for individual genotypes can be avoided, and individual and total plant leaf area can be calculated from total leaf number. A single, logistic equation, relying on maximum plant leaf area and thermal time from emergence, was developed to predict leaf senescence. The base, optimum, and maximum temperatures for calculation of thermal time for leaf senescence were 8, 34, and 40 degrees C, and apply for the whole crop-cycle when used in modelling of leaf senescence. Thus, the modelling of leaf production and senescence is simplified, improved, and generalised. Consequently, the modelling of leaf area index (LAI) and variables that rely on LAI will be improved. For experimental purposes, we found that the calculation of leaf area from leaf length and leaf width remains appropriate, though the relationship differed slightly from previously published equations.

CSM-IXIM: A New Maize Simulation Model for DSSAT Version 4.5

Th e CERES-Maize model is the most widely used maize (Zea mays L.) model and is a recognized reference for comparing new developments in maize growth, development, and yield simulation. Th e objective of this study was to present and evaluate CSMIXIM, a new maize simulation model for DSSAT version 4.5. Code from CSM-CERES-Maize, the modular version of the model, was modifi ed to include a number of model improvements. Model enhancements included the simulation of leaf area, C assimilation and partitioning, ear growth, kernel number, grain yield, and plant N acquisition and distribution. Th e addition of two genetic coeffi cients to simulate per-leaf foliar surface produced 32% smaller root mean square error (RMSE) values estimating leaf area index than did CSM-CERES. Grain yield and total shoot biomass were correctly simulated by both models. Carbon partitioning, however, showed diff erences. Th e CSM-IXIM model simulated leaf mass more accurately, reducing the CSM-CERES error by 44%, but overestimated stem mass, especially aft er stress, resulting in similar average RMSE values as CSM-CERES. Excessive N uptake aft er fertilization events as simulated by CSM-CERES was also corrected, reducing the error by 16%. Th e accuracy of N distribution to stems was improved by 68%. Th ese improvements in CSM-IXIM provided a stable basis for more precise simulation of maize canopy growth and yield and a framework for continuing future model developments

Strategies for adapting maize to climate change and extreme temperatures in Andalusia, Spain

Climate projections indicate that rising temperatures will affect summer crops in the southern Iberian Peninsula. The aim of this study was to obtain projections of the impacts of rising temperatures, and of higher frequency of extreme events on irrigated maize, and to evaluate some adaptation strategies. The study was conducted at several locations in Andalusia using the CERES-Maize crop model, previously calibrated/validated with local experimental datasets. The simulated climate consisted of projections from regional climate models from the ENSEMBLES project; these were corrected for daily temperature and precipitation with regard to the E-OBS observational dataset. These bias-corrected projections were used with the CERES-Maize model to generate future impacts. Crop model results showed a decrease in maize yield by the end of the 21st century from 6 to 20%, a decrease of up to 25% in irrigation water requirements, and an increase in irrigation water productivity of up to 22%, due to earlier maturity dates and stomatal closure caused by CO2 increase. When adaptation strategies combining earlier sowing dates and cultivar changes were considered, impacts were compensated, and maize yield increased up to 14%, compared with the baseline period (1981-2010), with similar reductions in crop irrigation water requirements. Effects of extreme maximum temperatures rose to 40% at the end of the 21st century, compared with the baseline. Adaptation resulted in an overall reduction in extreme Tmax damages in all locations, with the exception of Granada, where losses were limited to 8%.

Response of tropical maize to supplemental irrigation strategies.

Water is one of the most important factors influencing crop production in rainfed cropping systems. In tropical regions, supplemental irrigation reduces the risk of yield losses associated to water deficit due to insufficient rainfall. Water deficit in regions with irregularities in rainfall may be overcome with the use of supplemental irrigation, a technique based on the application of water at amounts below the crop?s evapotranspiration (ETc). We investigated the potential of supplemental irrigation as a strategy to increase yield of maize grown under tropical conditions. We used the CSM-CERES-Maize model of the Decision Support System for Agrotechnology Transfer (DSSAT) to simulate irrigation strategies of maize in six counties in the state of Minas Gerais, Brazil. Our results indicate significant differences on simulated crop yield in response to supplemental irrigation. As a consequence, water productivity was improved with reductions of 10% and 15% of full irrigation depths in one of the six counties while in two the water productivity was higher when full irrigation was applied.

Évaluation de la vulnérabilité des fermes productrices de maïs-grain du Québec aux variabilités et changements climatiques : les cas de Montérégie-Ouest et du Lac-Saint-Jean-Est

Réalisées aux échelles internationales et nationales, les études de vulnérabilité aux changements et à la variabilité climatiques sont peu pertinentes dans un processus de prise de décisions à des échelles géographiques plus petites qui représentent les lieux d’implantation des stratégies de réponses envisagées. Les études de vulnérabilité aux changements et à la variabilité climatiques à des échelles géographiques relativement petites dans le secteur agricole sont généralement rares, voire inexistantes au Canada, notamment au Québec. Dans le souci de combler ce vide et de favoriser un processus décisionnel plus éclairé à l’échelle de la ferme, cette étude cherchait principalement à dresser un portrait de l’évolution de la vulnérabilité des fermes productrices de maïs-grain des régions de Montérégie-Ouest et du Lac-St-Jean-Est aux changements et à la variabilité climatiques dans un contexte de multiples sources de pression. Une méthodologie générale constituée d'une évaluation de la vulnérabilité globale à partir d’une combinaison de profils de vulnérabilité aux conditions climatiques et socio-économiques a été adoptée. Pour la période de référence (1985-2005), les profils de vulnérabilité ont été dressés à l’aide d’analyses des coefficients de variation des séries temporelles de rendements et de superficies en maïs-grain. Au moyen de méthodes ethnographiques associées à une technique d’analyse multicritère, le Processus d’analyse hiérarchique (PAH), des scénarios d’indicateurs de capacité adaptative du secteur agricole susmentionné ont été développés pour la période de référence. Ceux-ci ont ensuite servi de point de départ dans l’élaboration des indicateurs de capacité de réponses des producteurs agricoles pour la période future 2010-2039. Pour celle-ci, les deux profils de vulnérabilité sont issus d’une simplification du cadre théorique de « Intergovernmental Panel on Climate Change » (IPCC) relatif aux principales composantes du concept de vulnérabilité. Pour la dimension « sensibilité » du secteur des fermes productrices de maïs-grain des deux régions agricoles aux conditions climatiques, une série de données de rendements a été simulée pour la période future. Ces simulations ont été réalisées à l’aide d’un couplage de cinq scénarios climatiques et du modèle de culture CERES-Maize de « Decision Support System for Agrotechnology Transfer » (DSSAT), version 4.0.2.0. En ce qui concerne l’évaluation de la « capacité adaptative » au cours de la période future, la construction des scénarios d’indicateurs de cette composante a été effectuée selon l’influence potentielle des grandes orientations économiques et environnementales considérées dans l’élaboration des lignes directrices des deux familles d’émissions de gaz à effet de serre (GES) A2 et A1B. L’application de la démarche méthodologique préalablement mentionnée a conduit aux principaux résultats suivants. Au cours de la période de référence, la région agricole du Lac-St-Jean-Est semblait être plus vulnérable aux conditions climatiques que celle de Montérégie-Ouest. En effet, le coefficient de variation des rendements du maïs-grain pour la région du Lac-St-Jean-Est était évalué à 0,35; tandis que celui pour la région de Montérégie-Ouest n’était que de 0,23. Toutefois, par rapport aux conditions socio-économiques, la région de Montérégie-Ouest affichait une vulnérabilité plus élevée que celle du Lac-St-Jean-Est. Les valeurs des coefficients de variation pour les superficies en maïs-grain au cours de la période de référence pour la Montérégie-Ouest et le Lac-St-Jean-Est étaient de 0,66 et 0,48, respectivement. Au cours de la période future 2010-2039, la région du Lac-St-Jean-Est serait, dans l’ensemble, toujours plus vulnérable aux conditions climatiques que celle de Montérégie-Ouest. Les valeurs moyennes des coefficients de variation pour les rendements agricoles anticipés fluctuent entre 0,21 et 0,25 pour la région de Montérégie-Ouest et entre 0,31 et 0,50 pour la région du Lac-St-Jean-Est. Néanmoins, en matière de vulnérabilité future aux conditions socio-économiques, la position relative des deux régions serait fonction du scénario de capacité adaptative considéré. Avec les orientations économiques et environnementales considérées dans l’élaboration des lignes directrices de la famille d’émission de GES A2, les indicateurs de capacité adaptative du secteur à l’étude seraient respectivement de 0,13 et 0,08 pour la Montérégie-Ouest et le Lac-St-Jean-Est. D’autre part, en considérant les lignes directrices de la famille d’émission de GES A1B, la région agricole du Lac-St-Jean-Est aurait une capacité adaptative légèrement supérieure (0,07) à celle de la Montérégie-Ouest (0,06). De façon générale, au cours de la période future, la région du Lac-St-Jean-Est devrait posséder une vulnérabilité globale plus élevée que la région de Montérégie-Ouest. Cette situation s’expliquerait principalement par une plus grande vulnérabilité de la région du Lac-St-Jean-Est aux conditions climatiques. Les résultats de cette étude doivent être appréciés dans le contexte des postulats considérés, de la méthodologie suivie et des spécificités des deux régions agricoles examinées. Essentiellement, avec l’adoption d’une démarche méthodologique simple, cette étude a révélé les caractéristiques « dynamique et relative » du concept de vulnérabilité, l’importance de l’échelle géographique et de la prise en compte d’autres sources de pression et surtout de la considération d’une approche contraire à celle du « agriculteur réfractaire aux changements » dans les travaux d’évaluation de ce concept dans le secteur agricole. Finalement, elle a aussi présenté plusieurs pistes de recherche susceptibles de contribuer à une meilleure évaluation de la vulnérabilité des agriculteurs aux changements climatiques dans un contexte de multiples sources de pression.

The impact of large-scale circulation patterns on summer crop in Iberian Peninsula

Large-scale circulations patterns (ENSO, NAO) have been shown to have a significant impact on seasonal weather, and therefore on crop yield over many parts of the world(Garnett and Khandekar, 1992; Aasa et al., 2004; Rozas and Garcia-Gonzalez, 2012). In this study, we analyze the influence of large-scale circulation patterns and regional climate on the principal components of maize yield variability in Iberian Peninsula (IP) using reanalysis datasets. Additionally, we investigate the modulation of these relationships by multidecadal patterns. This study is performed analyzing long time series of maize yield, only climate dependent, computed with the crop model CERES-maize (Jones and Kiniry, 1986) included in Decision Support System for Agrotechnology Transfer (DSSAT v.4.5).

Simulação da janela de semeadura para o milho irrigado no Estado de Minas Gerais.

2016

Initial growth of maize in response to application of rock phosphate, vermicompost and endophytic bacteria

Due to the high energy requirement and demand for non-renewable resources for the production of chemical fertilizers, added also to the environmental impact caused by the use of such products, it is important to intensify research on bio-based agricultural inputs. The use of nitrogen-fixing endophytic and phosphate solubilizing bacteria can provide these nutrients to the plants from the air and poorly soluble phosphorus sources, such as phosphate rock. The objective of this study was to evaluate the nutrition and initial growth of maize (Zea mays L.) in response to the inoculation of nitrogen-fixing and rock phosphate solubilizing endophytic bacteria, in single or mixed formulation, applied with vermicompost. The treatments containing bacteria, both diazotrophic and phosphate solubilizing, when compared to controls, showed higher levels of leaf nitrogen and phosphorus in maize, as well as higher growth characteristics. The application of vermicompost showed synergistic effect when combined with endophytic bacteria. Thus, the innovation of the combination of the studied factors may contribute to the early development of maize.