Tuesday, November 14, 2006 - 9:10 AM
205-3

Modelling Water and N Uptake and Responses in Models of Wheat, Potatoes and Maize.

Peter D. Jamieson, Robert F. Zyskowski, and Frank Y. Li. NZ Institute For Crop & Food Research, Private Bag 4704, Christchurch, New Zealand

Simulation of uptake of water and N requires demand and supply functions for both.  Simulating crop response requires assessment of the stress associated with any shortage.  Demand for water is calculated from very well tested evapotranspiration formulae based on the physics of the process.  In day timestep models, stress is assessed using the ratio of the daily demand to daily supply, the latter based on consideration of the physics of water transport in soil and plant.  Stress occurs when the demand rate exceeds supply rate.  The use of a stress index that affects plant processes has been very successful in simulating the effects of water stress without considering the details involved.  Treatment of N in models has been very similar to their treatment of water, despite most water departing from the plant the same day it is taken up, while most N is retained.  Demand is set to meet minimum and maximum concentrations of N that change with ontogeny or biomass, with the optimum concentration being about midway between these.  N supply is calculated daily from soil processes.  N-stress occurs and affects other processes when the crop is at lower than optimum N concentration.  Calibration of such a model is data intensive and empirical.  We propose an alternative approach that is both more mechanistic and simpler to implement.  Plant N is assigned into three pools by priority.  First priority is to structure.  N in this pool is not translocatble elsewhere.  Second priority is to green tissue, and is assigned per unit green area.  Third priority is labile storage.  By assuming that specific leaf N concentration is constant, N effects are expressed through their effects on light interception with no effect on light use efficiency.  We describe implementation in models of wheat, potatoes and maize and compare simulations with independent data.