As a result of the ongoing Coronavirus pandemic, the 11th Annual CPS Research Symposium is being conducted virtually over the course of five consecutive weeks. In the first session, the focus was on the creation of modeling tools to help the produce industry address key issues around persistence and growth of Listeria monocytogenes on whole produce commodities and the development of science and risk-based microbial sampling programs. An executive summary and the key learnings from these outstanding presentations and the discussions that followed are here:
Executive Summary:
- Computer-based modeling. Computer-based modeling tools and simulations based off industry produce safety data can advance our understanding of key industry challenges, identify knowledge gaps and lead to the development of improved preventive controls to improve the safety of our products.
- Partnership. Partnership and data sharing between researchers and industry experts is a requirement of developing models that essentially create a digital operation that simulates the real-world farms, packinghouses, processing plants and distribution facilities across our industry.
- Listeria growth and persistence on whole commodities. An important application of computer-based modeling is the determination of Listeria growth on whole, fresh fruits and vegetables. FSMA and customer requirements have focused industry attention on the potential for Listeria monocytogenes growth on intact fruits and vegetables if the product should encounter temperature abuse anywhere in the supply chain. pH, physical characteristics of the commodity and time at the elevated temperature are key variables for Listeria growth and persistence. A model has been developed based on growth media which can be used to predict Listeria growth and guide decisions on the safety of products stored temporarily outside of refrigerated temperatures.
- Improving models with laboratory data. Further laboratory-level investigation of Listeria growth and persistence on whole fruits and vegetables elucidated the impact of temperature abuse (as temperatures rise above 39°F up to 95°F Listeria growth rates increase), the role of relative humidity (lower relative humidity suppresses growth), and rapid changes in O2 and CO2 in produce storage (growth inhibiting). The surface topography also plays a role in Listeria persistence on whole produce with rougher surfaces supporting persistence. In general produce industry recommended storage is not a high risk for LM propagation
- Microbial sampling. A second application of computer-based modeling presented at Session 1 was directed at the development of operation-specific microbial sampling strategies. Microbial testing is used across the produce supply chain to detect pathogens or their indicators in agricultural inputs like irrigation water, for sanitation efficacy verification and environmental monitoring programs and raw and finished product acceptance. Sampling is currently problematic because we are essentially looking for a needle in a haystack; a sporadically occurring, low concentration, unevenly distributed contaminate in the vastness of our farms, facilities, and agricultural inputs. Model construction using industry produce safety data and the ability to conduct thousands of simulations where growth characteristics of pathogens, facility and equipment design parameters, production environment data, people and animal movement and other parameters can be factored in to inform development of risk- based sampling strategies.
- The end of “one size fits all”? The use of models and simulations to develop sampling strategies provides insights and creates opportunities to leverage testing results to identify gaps in historical data and focus future research efforts. It also means that “one size fits all” sampling strategies need to be supplanted with operation-specific protocols that enhance the chances of finding pathogens and providing the company with the opportunity to prevent contaminated products from entering commerce and performing root cause analysis to determine where the contamination originated and why it was there.