Jamieson, P. D., Semenov, M. A., Brooking, I. R. & Francis, G. S. Sirius: a mechanistic model of wheat response to environmental variation.
Currently available crop simulation models of wheat production perform poorly in this region, presumably due to their inability to account for subsoil limitations, mainly salinity.
Our focus is on optimizing wheat phenology, integrating simulations from a modified version of the ARCWHEAT model of wheat growth stages with available knowledge on the genetic control of wheat phenology obtained via molecular markers.
The structural time series models of wheat and rice are estimated by maximum likelihood.
A model of wheat, baking powder, and water volcano can be created to explore different magma viscosities (Acknowledgement to James Cowlyn and Ben Kennedy-University of Canterbury, New Zealand) Ana Gabriela Mar Sarabia.
An existing simulation model of wheat growth and development, Sirius, was evaluated through a systematic model reduction procedure.
Wheat (T. aestivum) mock-ups were obtained from a dynamic but non-plastic 3D architectural model of wheat development (Fournier et al. 2003).
A 3-D structural model of wheat flavone OMT, TaOMT2, was generated based on the crystal structure of caffeic acid/5-hydroxyferulic acid MsCOMT [ 16].
Moreover, recent simulation of wheat yields by the multi-model ensemble of wheat models showed that global wheat production is estimated to fall by 6% for each oC of temperature increase and become more variable over space and time18.
Tables 3, 4, 5, and 6 present the regression results for the acreage response models of corn, wheat, soybeans, and rice, respectively.
