A model of canopy development in winter wheat

Porter, John R.

doi:10.1017/s0021859600042714

Cited by 117 publications

(55 citation statements)

References 25 publications

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“…Short descriptions of the 5 wheat models used in these comparisons can be found in the report of this study (Wolf et al 1995). Further details can be found in the following literature: AFRCWHEAT2 (Porter 1984, Weir et al 1984; CERES (Ritchie & Otter 1985, Godwin et al 1990); NWHEAT (Groot 1987(Groot , 1993; SIRIUS (Jamieson & Wilson 1988, Jamieson 1989; and SOILN (Johnsson et al 1987, Eckersten & Jansson 1991, Eckersten et al 1994.…”

Section: Methodsmentioning

confidence: 99%

Comparison of wheat simulation models under climate change. I. Model calibration and sensitivity analyses

Wolf

1996

Clim. Res.

116

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A comparison of the performance of 5 wheat models was carried out for 2 sites in Europe with considerably different agroclimatic conditions: Rothamsted, UK, and Seville, Spain. The models were calibrated against field data sets from both sites. For Rothamsted the measured time courses of crop growth, evapo-transpiration and nitrogen uptake were reproduced reasonably well by the different models, except for leaf area index. For Seville, the experimental data set was insufficient for such a detailed comparison and mainly simulated results were compared. The sensitivity of the model results to stepwise changes In individual weather variables was then determined. In the different model runs a temperature rise generally resulted in lower yields, an increase in precipitation and atmospheric CO2 concentration resulted in higher ylelds, and increased variability of weather variables often resulted in lower yields with increased yleld varlab~lity.

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Section: Methodsmentioning

confidence: 99%

Comparison of wheat simulation models under climate change. I. Model calibration and sensitivity analyses

Wolf

1996

Clim. Res.

116

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“…To attain higher effectiveness of crop management practices, extensive research on cereal stand structure was conducted in the 1980s and 1990s (e.g. Porter 1984). The assessment of cereal stands and yield formation is usually based on the classical concept as reported by Heuser (1927/28) and later on by a number of other authors who divided grain yield into spike number per unit area, grain number per spike and grain weight.…”

mentioning

confidence: 99%

Yield and grain quality of spring barley as affected by biomass formation at early growth stages

Křen¹,

Klem²,

Svobodová³

et al. 2014

Plant Soil Environ.

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Timely and reliable prediction of grain yield and quality of spring barley represents a key prerequisite for effective crop management. Within this study we evaluated the relationships between yield components, grain quality, biomass production and the number of tillers in different growth stages. For this purpose, in three years (2011)(2012)(2013) multifactorial field trials focused on the combined effects of cultivar, sowing density and nitrogen nutrition were conducted. Based on ANOVA it was found that the formation of grain yield was affected by individual factors in the following order of importance: year, nitrogen, cultivar and sowing rate. The final grain yield significantly correlated both with the number of tillers and dry weight of above-ground biomass per unit area. The best estimation of yield provided both parameters at early growth stage (R = 0.83** and 0.81** for number of tillers and the above-ground biomass at BBCH 25). The grain protein content was inversely related to early growth parameters (R = -0.64** and -0.41** for number of tillers and above-ground biomass at BBCH 25). Based on the comparison of relationships between the years, it can be concluded that the early growth of barley and tiller differentiation is a key parameter for the formation of yield and grain quality.

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“…AFRCWHEAT2 is a complex model of wheat growth and development, describing the phenological development, dry matter production and dry matter distribution between the organs for various environmental parameters on a daily time scale [12,13,17]. The model includes a description of plant transpiration and soil evaporation, water and nitrogen movement in the soil, and their uptake by the plant in the course of growth.…”

Section: Modelsmentioning

confidence: 99%

Applicability of the Af Rcwheat2 Wheat Growth Simulation Model in Hungary

Harnos¹

2006

Appl Ecol Env Res

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Harnos: Applicability of the AFRCWHEAT2 wheat growth simulation model in Abstract. The aim of the present work was to determine the applicability of the AFRCWHEAT2 wheat growth model under Hungarian conditions. The Farquhar model, which, when properly calibrated, gives a satisfactory description of the net photosynthesis of Hungarian winter wheat varieties at various atmospheric CO 2 concentrations, temperatures and light conditions, was incorporated into the model. Both the original AFRCWHEAT2 model and the modified AF2MOD model were tested on long-term yield and climatic data series from Győr-Moson-Sopron County. It was observed that the average yield over the period 1980-1990 was well simulated by both models, but the AF2MOD simulated the annual fluctuations much better: the determination coefficients describing the correlation between the actual wheat yield in Győr-Moson-Sopron county over the whole period and the values generated using the models were r² = 0.32 for the AFRCWHEAT2 model and r² = 0.86 for AF2MOD.A comparison of the results simulated using the AFRCWHEAT2 and AF2MOD models demonstrated that detailed physiological submodels are required for the mathematical description of plant growth if yields are to be accurately estimated and the effects of environmental changes adequately described. A good example of this is the description of the effect of atmospheric CO 2 concentration on simulated yield figures, which depended on the climate of the given year in the AF2MOD model, but was described by a simple linear function in the AFRCWHEAT2 model.

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A model of canopy development in winter wheat

Cited by 117 publications

References 25 publications

Comparison of wheat simulation models under climate change. I. Model calibration and sensitivity analyses

Comparison of wheat simulation models under climate change. I. Model calibration and sensitivity analyses

Yield and grain quality of spring barley as affected by biomass formation at early growth stages

Applicability of the Af Rcwheat2 Wheat Growth Simulation Model in Hungary

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