Computer -based simulation models of changes occurring within crop populations when
subjected to agents of phenotypic change, have been developed for use on commonly
available personal computer equipment. As an underlying developmental principle, the
models have been designed as general -case, mechanistic, stochastic models, in contrast to
the predominantly empirically- derived, system -specific, deterministic (predictive) models
currently available. A modelling methodology has evolved, to develop portable simulation
models, written in high - level, general purpose code, allowing for use, modification and
continued development by biologists with little requirement for computer programming
expertise.The initial subject of these modelling activities was the simulation of the effects of selection
and other agents of genetic change in crop populations, resulting in the computer model,
PSELECT. Output from PSELECT, specifically phenotypic and genotypic response to
phenotypic truncation selection, conformed to expectation, as defined by results from
established analogue modelling work. Validation of the model by comparison of output
with the results from an experimental -scale plant breeding exercise was less conclusive,
and, owing to the fact that the genetic basis of the phenotypic characters used in the
selection programme was insufficiently defined, the validation exercise provided only broad
qualitative agreement with the model output. By virtue of the predominantly subjective
nature of plant breeding programmes, the development of PSELECT resulted in a model of
theoretical interest, but with little current practical application.Modelling techniques from the development of the PSELECT model were applied to the
simulation of plant disease epidemics, where the modelled system is well characterised, and
simulation modelling is an area of active research. The model SATSUMA, simulating the
spatial and temporal development of diseases within crop populations, was developed. The
model generates output which conforms to current epidemiological theory, and is
compatible with contemporary methods of temporal and spatial analysis of crop disease
epidemics. Temporal disease progress in the simulations was accurately described by
variations of a generalised logistic model. Analysis of the spatial pattern of simulated
epidemics by frequency distribution fitting or distance class methods was found to give
good qualitative agreement with observed biological systems.The mechanistic nature of SATSUMA and its deliberate design as a general case model
make it especially suitable for the investigation of component processes in a generalised
plant disease epidemic, and valuable as an educational tool. Subject to validation against
observational data, such models can be utilised as predictive tools by the incorporation of
information (concerning crop species, pathogen etc.) specifically relevant to the modelled
system. In addition to its educational use, SATSUMA has been used as research tool for the
examination of the effect of spatial pattern of disease and disease incidence on the
efficiency of sampling protocols and in parameterising a general theoretical model for
describing the spatio -temporal development of plant diseases
