Сравнение методов

	Модель SEIR для болезней растений	Компартментная эпидемическая модель SIR
Область	Агрономия	Эпидемиология
Семейство	Process / pipeline	Regression model
Год появления	1963 (Van der Plank); SEIR plant adaptation developed through 1970s–1990s	1927
Автор метода	Multiple contributors (Van der Plank foundational; Kermack-McKendrick SIR adapted to plant pathology)	Kermack & McKendrick
Тип	Deterministic compartmental epidemic model	Deterministic compartmental ODE model
Основополагающий источник	Van der Plank, J. E. (1963). Plant Diseases: Epidemics and Control. Academic Press, New York.	Kermack, W. O., & McKendrick, A. G. (1927). A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society A, 115(772), 700–721.
Другие названия	plant SEIR epidemic model, botanical SEIR model, plant disease compartmental model, SEIR phytopathological model	Kermack–McKendrick Model, Susceptible-Infectious-Recovered Model, Compartmental Epidemic Model, SIR Epidemiyoloji Modeli
Связанные	1	3
Сводка	The Plant Disease SEIR Model is a deterministic compartmental modelling framework adapted from human epidemiology to describe how a pathogen spreads through a host plant population. Rooted in the foundational work of J. E. Van der Plank and the Kermack-McKendrick tradition, it partitions all plants into four states — Susceptible, Exposed (latently infected), Infectious, and Removed — and tracks their transitions over time using a system of ordinary differential equations. It is a core tool in quantitative plant pathology and crop protection research.	The SIR model is a foundational mathematical framework for describing the spread of infectious diseases through a population. Introduced by William Ogilvy Kermack and Anderson Gray McKendrick in 1927, it partitions a closed population of size N into three mutually exclusive compartments: Susceptible (S), Infectious (I), and Recovered (R). A system of ordinary differential equations governs the flow of individuals between compartments, capturing epidemic dynamics with two key parameters — the transmission rate β and the recovery rate γ.