Estimating pest mortality in cold supply chains

Our team is working to develop methods to assess the contribution of commercial cold supply chains to reducing phytosanitary risks.

Cold treatment is a phytosanitary method that is commonly applied to manage cold sensitive, quarantine pests that may be carried via the trade of agricultural commodities.

Currently, phytosanitary cold treatment schedules do not take into account the contribution commercial supply chains may make to the cold-induced mortality of pests – yet, most fruit and vegetables are kept chilled to maintain freshness and quality from harvest through to retail markets .

Cold treatment schedules typically aim to achieve at least 99.99% mortality rate for the target pest and require horticulture consignments to be held at a set temperature for a specified duration. Development of a cold treatment protocol requires technical data from rigorous, large-scale laboratory experiments that must be repeated for each pest and fruit combination.

To enable a more flexible approach, we are collaborating with university partners, regulators and industry on a diverse program of research to tackle different aspects of the challenge:

• Modelling pest fly mortality using publicly available data to predict how mortality is affected by temperature, exposure time, host fruit and developmental stage
• Quantifying the relationship between air temperature fluctuations and fruit pulp temperature. This will enable accurate prediction of pulp temperature of fruit in the cold supply chain using air temperature loggers. Our partners for this work are SuperCool and Escavox
• Creating a dashboard tool that allows supply chain partners to track in-transit cold mortality predictions through the commercial cool chain – in collaboration with Escavox
• Empirically quantifying the effect of cold temperature exposure on Queensland fruit fly egg mortality. This research is in partnership with the Queensland University of Technology (QUT), Queensland Department of Agriculture and Fisheries (QDAF), and the Fresh and Secure Trade Alliance (FASTA). Key collaborators are Professor Peter Prentis and Kirra Sadzius (PhD student).
• Empirically quantifying critical thermal minimum of different insect pests. Our research collaborators are Dr Leigh Boardman at the University of Memphis, and United States Department of Agriculture (USDA).

Modelling time-temperature dependent pest mortality in fruit

We created a model that quantifies the relationship between pest mortality and temperature, exposure time, pest, pest life stage and host. We hope that results from this work will help shift cold treatment practices from rigid, fixed temperature protocols with strict mortality targets to a more adaptable approach that accounts for existing commercial supply chain practices and infestation likelihood in produce.

To inform our model, we analysed 28 publicly available cold treatment studies for cold-sensitive pests. The model predicts the mortality of different pests over time, depending on key factors, including the type of pest (10 pest flies species), their developmental stage (eggs or larvae stage), exposed temperature (0-7 °C), and host fruit (13 fruit types). We can readily extend the model with new data.

To learn more about the model, read our paper in the Journal of Pest Science:

Our model predictions suggest that some existing treatment schedules may be overly conservative. Longer, and colder, treatment schedules can add substantial cost and complexity to trade. It can also reduce fruit quality.

Potential applications of our model include:

• Estimating pest mortality during commercial storage and transit
• Estimating the treatment time needed to achieve a target mortality rate at a given temperature for new pest-host-temperature combinations. These estimates can subsequently be empirically validated. This could greatly reduce the cost of undertaking studies to support treatment protocols. It may also be the only option for some pests that are difficult to culture.
• Supporting the use of treatment protocols already developed for other pest-host combinations without the need for undertaking a completely new empirical study.

Looking ahead, this model could be adapted to guide phytosanitary risk management in a wider range of cold-sensitive pests in diverse hosts and commodities.  Please contact us if you have datasets that you would like included.