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Trends In Food Science & Technology

Publication date: 2021-08-28
Volume: 126 13
Publisher: Elsevier Trends Journals

Author:

Katsini, Lydia
Bhonsale, Satyajeet Sheetal ; Akkermans, Simen ; Roufou, Stylliani ; Griffin, Sholeem ; Valdramidis, Vasilis ; Ourania, Misiou ; Konstantinos, Koutsoumanis ; Muñoz Lopéz, Carlos Andre ; Polanska, Monika ; Van Impe, Jan

Keywords:

Science & Technology, Life Sciences & Biomedicine, Food Science & Technology, Climate change, Food safety, Predictive microbiology, Impact modelling, MICROBIOLOGICAL RISK-ASSESSMENT, NEXT-GENERATION, BIAS CORRECTION, SCENARIO DATA, LEAFY GREENS, GROWTH-RATE, IMPACTS, MODEL, PROJECTIONS, UNCERTAINTY, 1224620N#55267578, 0908 Food Sciences, Food Science, 3006 Food sciences, 4004 Chemical engineering

Abstract:

Food systems are both affecting and being affected by climate change. Anticipated effects of climate change on microbial food safety are both direct (e.g., on microbial prevalence) and indirect (e.g., increased risk of floods on water microbial contamination). This paper highlights the necessity to build a quantitative framework to evaluate the effects of climate change on microbial food safety. The tools available from the fields of climate modelling and predictive microbiology are analysed, knowledge gaps and data needs are identified. Moreover, key sources of uncertainty are underlined by emphasising on the importance of an integrated study of the uncertainties involved. Due to the high complexity of both climate change and microbial dynamics, a multidisciplinary research approach is essential. After selecting one food product and location to focus on, the appropriate climate change projections relative to microbial dynamics need to be determined and generated. The development of the impact model is based on the relationship between environmental pathogen prevalence and dispersal and climatic factors. This is linked with the impact of climatic factors on microbial dynamics. These mechanisms remain poorly understood. The knowledge gap of the mechanisms regarding food microbial contamination and the role of climatic variables remains unexplored. Since controlled experiments on the climate system are challenging, international collaboration is imperative to gather the appropriate observational datasets. Moreover, identifying and evaluating the sources of uncertainty is critical to build reliable models.