Abstract
Modeling induced resistance to plant disease using a dynamical systems approach
Highlights
Standard epidemiological models describe that Susceptible plants (S) will become infected and develop Disease (D) after inoculation with a compatible pathogen under appropriate environmental conditions
Various disease risk prediction models have been developed as decision support tools to facilitate more efficient use of management options; these are generally based on the rationale that pest and disease development follow predictable life cycles and that by monitoring key epidemiological parameters it is possible to target more accurately events critical for management (Gent et al, 2011)
Disease risk prediction models may prove critical for coordination of elicitor application in crop production systems because of the importance of early intervention when relying on induced resistance (IR) for disease control
Summary
Standard epidemiological models describe that Susceptible plants (S) will become infected and develop Disease (D) after inoculation with a compatible pathogen under appropriate environmental conditions. Disease development on the MeJA-treated seedlings was compared to that on a cohort of untreated plants. Because the expression of IR can only be detected after pathogen challenge, the model is formulated with the treated plants divided into two regimes: (1) preinoculation and (2) post-inoculation.
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