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

• Growth and spread of a postharvest fungal pathogen on stored apples was modelled.
• The model predicts disease incidence given initial infection and apple susceptibility.
• Variation in disease levels increase with apple susceptibility and storage duration.
• Spread patterns were dendritic or circular, and similar in 2D and 3D simulations.
• The model is a first step towards a tool for optimizing commercial fruit storage times.

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.