Gompertz fuzzy model for plant disease evolution

Abstract

Plant disease experimental data have been shown to fit better with a crisp Gompertz model rather than a logistic model. A fuzzy approach based on Zadeh's Extension Principle, which leads to four systems of two parameter dependent autonomous differential equations, is applied to this subject. The solution is monitored from the initial fuzzy conditions through to the three different domains and two sub-domains. While results show properties of the crisp Gompertz model being kept and then lost, this is still an appropriate generalized way to deal with uncertainty in plant disease evolution.