|Emma Hartnett, Ph.D., Risk Sciences
Dr. Hartnett is the modeling and simulation practice lead with Risk Sciences International in Ottawa, Canada. Joining her as co-principal investigator on the project is Donald Schaffner, Ph.D., a Distinguished Professor at Rutgers University, focusing on quantitative microbial risk assessment and predictive food microbiology.
Some of the variables involved in the project are sample size or mass, the number of samples, and lot size. A few of the questions the researchers sought to answer were: 1) If I increase the size of each sample, how does it affect risk? 2) If I change my sampling location within the supply chain and sample at point X rather than point Y, is there a risk-reduction benefit to consumers?
Linked to the sampling model is a supply chain model that predicts the concentration and prevalence of microbial hazards post-sampling
Breaks in the cold chain and abusive product handling, for example, are known to happen, and they can promote microbial growth that pose a consumer risk. The supply chain model allows the researchers to gauge the magnitude of risk reduction should sampling be moved or added later in the supply chain.
"The question is, should you try to sample later if you're able to catch it?" Hartnett said. "That's what we're able to look at with the model. If you have a reduction step, such as a wash, and you sample at harvest and compared to sampling after the wash, you lower the (pathogen risk) levels."
But will that wash provide sufficient risk reduction throughout the supply chain until the product reaches the consumer?
"Those are the kinds of relationships we're trying to tease out. We're looking at the chain as a whole and not just looking at harvest," she said.
The researchers also conducted analyses that apply to a range of produce including baby greens, whole head greens, cole crops, tomatoes, onions, peppers, celery, pome fruit, stone fruit and tropical fruit.
As part of the project, Hartnett formed a stakeholder group comprising producers and representatives from academia and produce trade associations. Members provided input about the risk-reduction measures they currently use.
During an online workshop, they were asked to review the project's draft results to ensure it was useful since much of the material was complex.
From their initial response it was clear the work was a bit too academic for their audiences.
"One of the questions they asked was about the differences between two-class and three-class sampling types" Hartnett said. "I had assumed that people would know this already because it's always talked about in academic situations. What I learned is I need to back off on the technical parts and focus more on the useful message that comes out of this."
In the end, the group recommended a report that contains a series of stories or case studies filled with tables and charts as well as real-life scenarios.
Hartnett admits the she can't offer examples of every situation that occurs in the produce supply chain. What she hopes the document will do is spark interest in producers and processors who see similarities to their operation and prompt them to further explore their options.
"If you do sampling in this location, you're getting a risk reduction," Hartnett said. "If you change to a different location, your benefit in terms of the consumer risk will be X percent. This really gives a tangible value to what they can do."