Predicting the spread of postharvest disease in stored fruit, with application to apples

Abstract

Postharvest diseases can cause considerable damage to harvested fruit in controlled atmosphere storage. Since there is a large cost associated with opening the storage rooms, regular assessment of damage levels is not feasible, and many experts agree on the need for a reliable predictive model. Presented here is a simulation model that predicts the overall incidence of disease in a bin of stored fruit as a function of initial infection levels and the fruit's susceptibility to fungal attack. Uninfected fruit tissue, infected fruit tissue, and fungal growth are modelled by a system of three ordinary differential equations. Simulations of the growth and spread of the pathogen in storage were conducted, with disease incidence measured monthly. The model provides insight into the dynamics of postharvest fungal disease, and forms the basis of a predictive model that could be used by packinghouses to determine how long a given crop of fruit can be stored before the infection risk rises above a predetermined tolerable level.