S32 Tailoring Acceptance Sampling Theory for Enhanced Microbial Risk Management

Tuesday, August 2, 2016: 8:30 AM-12:00 PM
225-226 (America's Center - St. Louis)
Sponsored By:
Primary Contact: Vijay Juneja
Organizers: Vasco Cadavez , Ursula Gonzales-Barron and Vijay Juneja
Convenors: Ursula Gonzales-Barron and Vijay Juneja
Microbial sampling is a risk management strategy used to evaluate whether a food safety system is correctly implemented. Although microbiological sampling cannot guarantee with 100% certainty the safety of food products, still it is commonly accomplished to comply with regulatory microbiological criteria or to assess whether food production processes are under control. Sampling plans have been conventionally derived by borrowing concepts of acceptance sampling theory from classical quality statistics. However, the classical simplistic assumptions of data normality and homogenous contamination among production batches have been demonstrated to affect the efficacy of the sampling plans. Since within-batch testing regimes are critical in the sense that they aid in determining whether food safety targets are being achieved, sampling plans should be designed using sound statistical methods that ensure the desired level of protection. Thus, in the past few years, two phenomena known to strongly impact on the performance of a sampling plan have been studied: the spatial clustering of bacteria cells in foods and the heterogeneity in microbial contamination among batches. To address these issues, there have been some efforts in the investigation of other statistical distributions to better represent bacterial clustering, and a situation originated thereof, the high proportion of zero counts in samples, especially when contamination levels are low. Nevertheless, whatever the statistical distribution of microorganisms is chosen, considering the between-batch variability in microbial contamination is relevant for making some safety allowance for the effectiveness of sampling plans. In addition, some researchers have also proposed the use of past monitoring microbial data in order to establish realistic tolerance criteria, as well as the development of new methodologies, if possible Bayesian, for updating the sampling plans, as new sampling data are collected. Thus, the objective of this symposium is to discuss the weaknesses of traditional acceptance sampling. For the design of new-generation sampling plans, speakers will review new concepts and trends that are more informative, dynamic and amenable to be updated, and hence, more efficient in ensuring the achievement of food safety risk targets.


10:00 AM
10:30 AM
Shifting to Informative Variables Sampling Plans: Needs and Initiatives
Ursula Gonzales-Barron, CIMO Mountain Research Centre, School of Agriculture (ESA), Polytechnic Institute of Braganza (IPB)
11:00 AM
Using Quality Control Monitoring Microbial Data for the Design of Bayesian Control Charts
Vasco Cadavez, CIMO Mountain Research Centre, School of Agriculture (ESA), Polytechnic Institute of Braganza (IPB)
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