Crop models as research and interpretative tools

Mechanistic (eco-physiological), or process-oriented, approach to simulation modeling of the production process of plants assumes considering the essences of processes and cause-effect relationships in the agroecosystem with a description of their dynamics based on physically interpreted dependencies (as opposed to logically interpreted dependencies at the empirical approach) (A. Di Paola et al., 2016; R.A. Poluektov, 2010). The analysis of the possible use of dynamic simulation models of agro-ecosystems in the mechanistic nature of applied and theoretical research of agricultural biology is presented. The current practice of the development and usage of these models shows their highest suitability for research purposes in comparison to the potential usefulness and relevance to the practical problems of agronomy. Specific examples of model applications demonstrate the possibility of computer-based model experiments to get nontrivial results, which are not directly incorporated into the logic of the model algorithms (V. Badenko et al., 2014; S. Medvedev et al., 2015). The role of simulation model as a tool of obtaining new knowledge and interpretation of the empirically observed phenomena has been showed. To demonstrate the potentials of simulation models for agricultural biology, some results of authors' studies have been reviewed, including analyze of the appearance of a non-monotonic response function of crop yield on the doses of nitrogen fertilizer, the results of computer experiments on interpretation of the effect of the time delay during management of nitrogen feeding «on the leaf», and the joint impact of combined water and nitrogen stresses. Based on analysis of recent publications, conclusions of perspectives of models application to accelerate the plant breeding process were justified. It is concluded, i) further «biologization» of existing models is a prerequisite for a successful development of the dynamic crop growth modeling, and ii) it is necessary to increase the level of scientific validity of model approaches, which are used to describe the biotic processes in the soil-plant-atmosphere system