CROP GROWTH MODELS: THEIR USEFULNESS AND LIMITATIONS

Two main types of crop growth models are discussed: (a) regression models, describing the growth course with some empirical function (e.g.
Richards function, polynomials), and (b) mechanistic models, explaining the growth course from the underlying physiological processes in relation to the environment.
The structure of these eco-physiological models is discussed by describing two general crop models, a simple and a more detailed one.
The simple model (LINTUL) describes growth on the basis of light interception and utilization, and dry matter distribution on the basis of a harvest index.
The more detailed model (SUCROS) describes growth from photosynthesis and respiration, and allocates the daily dry matter increments to various groups of organs according to partitioning factors introduced as a function of the development stage of the crop.
Parameterization is illustrated for potato.
It is demonstrated that the use of an average efficiency of light utilization is, in general, a valid simplification when simulating crop growth.

Management asks for predictive models, whereas research demands explanatory models.
It is argued that for predictive purposes, well-parameterized regression or simple physiological models are the most promising way.
To assist in research, however, the physiological models are usually superior as they combine explanation and integration of the underlying principles.
The model should fit the particular objectives of the experiment.
A promising strategy is, therefore, to develop a series of submodels of varying complexity for the different processes, while putting emphasis on simple approaches.

VI Symposium on the Timing of Field Production of Vegetables

C.J.T. Spitters

https://doi.org/10.17660/ActaHortic.1990.267.42