Understanding and modeling the effect of temperature and daylength on soybean phenology under high-yield conditions

Setiyono, T. D.; Weiss, Albert; Specht, James E.; Bastidas, A. M.; Cassman, Kenneth G.; Dobermann, A.

doi:10.1016/j.fcr.2006.07.011

Cited by 222 publications

(216 citation statements)

References 52 publications

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“…Soybean phenology was simulated as a function of temperature and photoperiod considering pre-induction and post-induction processes during the flowering phase (Setiyono et al, 2007). Leaf area index was simulated as a function of net leaf area per plant and population density (PD, Equation (1)).…”

Section: Model Developmentmentioning

confidence: 99%

“…An important goal of this effort was to develop a model for practical application, one with reduced complexity and less cultivar-specific parameters. (Adviento-Borbe et al, 2007;Bastidas et al, 2008;Setiyono et al, 2007). Management practices in the large research field at Mead (Grant et al, 2007;Verma et al, 2005) followed best management practices for irrigated soybean production in Nebraska, including monitoring excellent weed and pest control and irrigation scheduling based on soil moisture and ET.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Leaf area index simulation in soybean grown under near-optimal conditions

Setiyono

Weiss

Specht

et al. 2008

Field Crops Research

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Section: Model Developmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Leaf area index simulation in soybean grown under near-optimal conditions

Setiyono

Weiss

Specht

et al. 2008

Field Crops Research

Self Cite

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“…Briefly, Q integrates the effects of solar radiation and temperature on crop growth and development during critical stages for yield determination. For the calculation of Q, a T base = 0 °C was assumed for reproductive stages of soybean based on Setiyono et al (2007). A threshold of 34 °C was chosen for stressful high temperature, based on data reported by Rondanini et al (2003) and Cicchino et al (2010) for sunflower and maize, respectively.…”

Section: Assessment Of Explanatory Factors For Variation On Soybean Smentioning

confidence: 99%

Drivers of spatial and temporal variation in soybean yield and irrigation requirements in the western US Corn Belt

Grassini

Torrion

Cassman

et al. 2014

Field Crops Research

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“…A widely used approach in crop simulation models is to describe the effects of environmental variables such as solar radiation, temperature and photoperiod, on crop growth and development with adimensional response functions which vary from zero to one (Streck et al, 2003(Streck et al, , 2007Setiyono et al, 2007Setiyono et al, , 2010. The underlying hypothesis in the present study was that a similar approach can be used for developing a f(CO 2 ).…”

Section: Methodsmentioning

confidence: 82%

CO2-response function of radiation use efficiency in rice for climate change scenarios

Streck

Rosa

Walter

et al. 2012

Pesq. agropec. bras.

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-The objective of this work was to evaluate a generalized response function to the atmospheric CO 2 concentration [f(CO 2 )] by the radiation use efficiency (RUE) in rice. Experimental data on RUE at different CO 2 concentrations were collected from rice trials performed in several locations around the world. RUE data were then normalized, so that all RUE at current CO 2 concentration were equal to 1. The response function was obtained by fitting normalized RUE versus CO 2 concentration to a Morgan-Mercer-Flodin (MMF) function, and by using Marquardt's method to estimate the model coefficients. Goodness of fit was measured by the standard deviation of the estimated coefficients, the coefficient of determination (R 2 ), and the root mean square error (RMSE). The f(CO 2 ) describes a nonlinear sigmoidal response of RUE in rice, in function of the atmospheric CO 2 concentration, which has an ecophysiological background, and, therefore, renders a robust function that can be easily coupled to rice simulation models, besides covering the range of CO 2 emissions for the next generation of climate scenarios for the 21 st century.Index terms: Oryza sativa, global warming, modeling, photosynthesis. Função de resposta a CO 2 na eficiência de uso da radiação em arroz para cenários de mudanças climáticasResumo -O objetivo deste trabalho foi avaliar uma função de resposta generalizada à concentração de CO 2 atmosférico [f (CO 2 )] pela eficiência de uso de radiação (RUE) em arroz. Os dados experimentais de RUE, em diferentes concentrações de CO 2 , foram coletados de ensaios sobre o arroz realizados em diferentes locais do mundo. Os dados de RUE foram normalizados de modo que todos os valores de RUE, na atual concentração de CO 2 , foram iguais a 1. A função de resposta foi obtida pelos valores de RUE normalizados versus a concentração de CO 2 , ajustados à função de Morgan-Mercer-Flodin (MMF), com uso do método de Marquardt para estimar os coeficientes do modelo. O ajuste da função foi medido pelo desvio-padrão dos coeficientes estimados, o coeficiente de determinação (R²) e a raiz do quadrado médio do erro (RQME). A f(CO 2 ) descreve uma resposta não linear sigmoidal da RUE em arroz, em função da concentração do CO 2 atmosférico, o que tem significado ecofisiológico e, portanto, é uma função robusta que pode ser facilmente acoplada a modelos de simulação de arroz, além de abranger as emissões de CO 2 para a próxima geração de cenários climáticos para o século 21.Termos para indexação: Oryza sativa, aquecimento global, modelagem, fotossíntese.

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Understanding and modeling the effect of temperature and daylength on soybean phenology under high-yield conditions

Cited by 222 publications

References 52 publications

Leaf area index simulation in soybean grown under near-optimal conditions

Leaf area index simulation in soybean grown under near-optimal conditions

Drivers of spatial and temporal variation in soybean yield and irrigation requirements in the western US Corn Belt

CO2-response function of radiation use efficiency in rice for climate change scenarios

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