| Autor: |
Butler, Francis, Hunt, Kevin, Redmond, Grainne, dOnofrio, Federica, Barron, Ursula Gonzales, Fernandes, Sara, Cadavez, Vasco, Iannetti, Luigi, Centorotola, Gabriella, Pomilio, Francesco, Diaz, Antonio Valero, Rodríguez, Fernando Pérez, Luque, Olga Mª Bonilla |
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| Zdroj: |
EFSA Supporting Publications; Dec2023, Vol. 20 Issue 12, p1-66, 66p |
| Abstrakt: |
This report summarises the outcomes from the EFSA funded ListeriaPredict Partnering Project based on the consortium's proposal of "Application of novel predictive microbiology techniques to shelf‐life studies on Listeria monocytogenes in ready‐to‐eat foods (ListeriaPredict)" submitted under EFSA open call for partnering grant projects. The consortium consisted of four partners, University College Dublin (Coordinator), Instituto Politécnico de Bragança, Istituto Zooprofilattico Sperimentale di Abruzzo e Molise and Universidad de Córdoba. Listeria monocytogenes is a major hazard of concern in the broad ready‐to‐eat (RTE) food sector both at EU level and globally. Its ability to grow at refrigerated temperatures causes particular food safety concerns for RTE foods. There has been substantial activity within the European Union to provide guidance on how to conduct laboratory shelf‐life studies on L. monocytogenes in RTE foods to assure product safety. Shelf‐life studies, by their nature, are expensive and pose considerable resourcing challenges to small and medium sized companies that dominate the food sector across Europe. Predictive microbiology has a critical role in interpreting the results of experimental challenge tests and extending their application under varying environmental conditions. This project worked to substantially enhance capacity in the four partner institutions across Europe in applying predictive microbiology techniques to shelf‐life studies on L. monocytogenes in RTE foods. Knowledge transfer activities included workshops, online webinars and short scientific visits. Knowledge exchange activities targeted the broad area of predictive dynamic modelling. Static and dynamic growth experiments undertaken by one of the project partners was used as input to collectively develop a series of dynamic modelling approaches to obtain the optimum growth rates and cardinal parameters governing the growth of L. monocytogenes. To ensure continuity, the project disseminated the expertise and knowledge accumulated within the consortium to a wider audience through archiving training materials in the EFSA Knowledge Junction repository to allow the resources generated by the project to be available beyond the lifetime of the project. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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