CROPSIM-WHEAT - A MODEL DESCRIBING THE GROWTH AND DEVELOPMENT OF WHEAT

Crop simulation models consolidate mathematical representations of the various physiological processes underlying crop growth and development into an entity that can be used to predict the outcome of various crop, soil and weather scenarios. For wheat, a number of simulation models are already available, but most of these do not appear to be set-up to facilitate easy comparison of model outputs with experimental data, to allow easy modification for new cultivars, and to facilitate the addition of disease routines, an aspect necessary for models to be useful in the general field situation. Cropsim-wheat was developed to help overcome some of these deficiencies. The model assumes that a crop consists of a collection of uniform plants, and performs calculations on a daily basis. It is driven by daily weather data dealing with solar radiation receipt, maximum and minimum temperatures, and precipitation. Water and nitrogen balance subroutines are included, and the rate of various crop processes is modulated through the use of multipliers that reflect the water and nitrogen states of the crop. Developmental processes are simulated using the concept of ''biological days'', a time measure that equates to chronological days under optimum conditions. The phases into which the life-cycle is broken relate closely to those in the widely used ''Zadoks'' scale. Dry matter accumulation is calculated from intercepted radiation, and distributed largely on the basis of demand. A minimum fraction of daily assimilate, however, is reserved for root growth. Leaf area is computed on the basis of potential leaf size and available dry matter, whereas stem and spike areas are calculated from the stem and spike weights. Both leaf and stem area are used in calculating radiation interception. Critical stresses, water saturation during early seedling growth and low temperature during the winter period, can result in plant death. Low temperatures, when they occur around heading, can also result in sterility and reduced grain number. The model performance has been compared with datasets from North America and Europe, and results of these comparisons will be conveyed in companion publications. The model has been set-up, however, on the premise that model development should be a continuing process as new datasets become available and new applications are contemplated. With this in mind, it has been built to use file structures that facilitate the handling and storage of field data, and the easy comparison of field and simulated data. It should thus be useable by experimenters as a tool to help in the analysis of field studies.