A system approach to the modeling of fungal infections of the wheat leaf - S. V. Nikolaev; U. S. Zubairova; E. S. Skolotneva; E. A. Orlova; D. A. Afonnikov (Вавиловский журнал генетики и селекции)
Currently, studies on the mechanisms of the pathogenesis of plant diseases and their distribution in crops are intensively conducted in Russia and the world. First of all, this interest is associated with a significant effect of pathogens on the harvest. In Western Siberia, brown rust and powdery mildew are almost annually recorded in the crops of spring and winter wheat, reaching in some years up to the epiphytotic level. In this regard, methods for monitoring the condition of crops in order to predict their dynamics and plan agrotechnological events to control the state of plants in crops, including the development of fungal infection are developing. Models of fungal infections development on the wheat leaf (for example, brown rust) are used to monitor, predict and control the state of crops in order to optimize the growing process. Mathematical models allow computational experiments to make predictions about the risk dynamics of infections in different scenarios of global weather changes. Such designation of models assumes their hierarchical structure characteristic of multilevel modeling systems. This review presents models for the development of foliar fungal infections in crops, and formulates the methodological aspects of system modeling that can be used for adapting existing models and their units, and developing new models based on them. The article presents the structure of the hierarchical system for modeling the development of leafy infection, provides an overview of the units constituting the system, and discusses the issues of parametric adaptation of submodels. We demonstrated that, to date, plant growth and development models have been developed with varying degrees of detail. Currently, to develop a system for modeling the development of an infection in a crop, it is necessary to determine a large body of available experimental data and, by taking into account this data, we can put together a model as a system consisting of model modules, for which the models of basic processes have already been developed and described.