Abstract
Within microblological risk assessments there is large varlabllity and uncertainty because of three important biologica! entities, mîcroorganisms, food products and human beings. All three result in difficult to predlct behaviour. But Hke in
ether domains this is a fact of !ife, and still interventions and decisions need to be taken that are effective. In many cases variability is presented trom the specîfic research done, but should be put in perspective to ether variabîlities
within the assessment to rate the factors that are overall the most important. We all look from the perspective of the things we are investigating, but we should also look overarching. Meta-analysis can be helpful in this respect. Biological
variability is governed by physiological variability, genetïc variability, strain variability. Detailed assessment of the physiological variabi!ity can be determined experimentally, needing large replicated datasets. Furthermore detailed investigations in genetic heterogeneity within microbial populations can be carried out. But on the other hand also the conditions in the chain can be largely variable due to large variations for example in temperature and time. Then overall it is not easy to see the wood for the trees. Within quantitative risk assessment, either if they are on microbiology, toxicology, or financial risks, there are large variabilities and large uncertainties.
ether domains this is a fact of !ife, and still interventions and decisions need to be taken that are effective. In many cases variability is presented trom the specîfic research done, but should be put in perspective to ether variabîlities
within the assessment to rate the factors that are overall the most important. We all look from the perspective of the things we are investigating, but we should also look overarching. Meta-analysis can be helpful in this respect. Biological
variability is governed by physiological variability, genetïc variability, strain variability. Detailed assessment of the physiological variabi!ity can be determined experimentally, needing large replicated datasets. Furthermore detailed investigations in genetic heterogeneity within microbial populations can be carried out. But on the other hand also the conditions in the chain can be largely variable due to large variations for example in temperature and time. Then overall it is not easy to see the wood for the trees. Within quantitative risk assessment, either if they are on microbiology, toxicology, or financial risks, there are large variabilities and large uncertainties.
Original language | English |
---|---|
Pages | KYN10 |
Publication status | Published - 2015 |
Event | ICPMF9, International Conference on Predictive Modelling in Food, Rio de Janeiro (Brazil) - Rio de Janeiro, Brazil Duration: 8 Sept 2015 → 12 Sept 2015 |
Conference/symposium
Conference/symposium | ICPMF9, International Conference on Predictive Modelling in Food, Rio de Janeiro (Brazil) |
---|---|
Country/Territory | Brazil |
City | Rio de Janeiro |
Period | 8/09/15 → 12/09/15 |