Gonzales-Barron, U.; Cadavez, V.; De Oliveira Mota, J.; Guillier, L.; Sanaa, M. A Critical Review of Risk Assessment Models for Listeria monocytogenes in Produce. Foods2024, 13, 1111.
Gonzales-Barron, U.; Cadavez, V.; De Oliveira Mota, J.; Guillier, L.; Sanaa, M. A Critical Review of Risk Assessment Models for Listeria monocytogenes in Produce. Foods 2024, 13, 1111.
Gonzales-Barron, U.; Cadavez, V.; De Oliveira Mota, J.; Guillier, L.; Sanaa, M. A Critical Review of Risk Assessment Models for Listeria monocytogenes in Produce. Foods2024, 13, 1111.
Gonzales-Barron, U.; Cadavez, V.; De Oliveira Mota, J.; Guillier, L.; Sanaa, M. A Critical Review of Risk Assessment Models for Listeria monocytogenes in Produce. Foods 2024, 13, 1111.
Abstract
A review of quantitative risk assessment (QRA) models of L. monocytogenes in produce was carried out, with the objective of appraising and contrasting the effectiveness of the control strategies placed along the food chains. Despite nine of the thirteen QRA models recovered focused on fresh or RTE leafy greens, none of them represented important factors or sources of contamination in the primary production, such as type of cultivation, water, fertilisers or irrigation method/practices. Cross-contamination at processing and during consumer’s handling was modelled using transfer rates, which were shown to moderately drive the final risk of listeriosis; highlighting therefore the importance of accurately representing the transfer coefficient parameters. Many QRA models coincided in the fact that temperature fluctuations at retail or temperature abuse at home were key factors contributing to increasing the risk of listeriosis. In addition to a primary module that could help assess current on-farm practices and potential control measures, future QRA models for minimally-processed produce should also contain a refined sanitisation module able to estimate the effectiveness of various sanitisers as a function of type, concentration and exposure time. Finally, L. monocytogenes growth in the products down the supply chain should be estimated by using realistic time-temperature trajectories, and validated microbial kinetic parameters, both of them currently available in the literature.
Biology and Life Sciences, Agricultural Science and Agronomy
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