Some remarks on the design of three-class sampling plans.
Among the variety of sampling plans for the evaluation of bacterial counts the attributive three-class sampling plan has widely gained acceptance because of its simple application and its robust functionality. However, the performance characteristics of three-class sampling plans depend on lot heterogeneity and the distance between the microbiological limits m and M, which are the maximum level of target organisms under conditions of good manufacturing practice (GMP) and the level of target organisms that is considered as unacceptable or defective. The probability of lot rejection due to a single sample result above M increases with increasing lot heterogeneity and/or with decreasing distance between these limits. Especially for investigations on nonpathogenic microorganisms it is questionable whether a lot still meeting GMP conditions should be rejected solely because a single sample result lies above M. Taking the often used three-class sampling plan (n = 5; cm = 2, cm = 0) as an example, it is demonstrated how insight into the relationship between sample variability and an appropriate distance between m and M can be gained. These calculations are based on the assumptions that logarithmically transformed bacterial counts follow a normal distribution and that an indifference lot with a contamination level at m is to be evaluated. For this kind of lot the probability of acceptance or rejection is equally 0.5 according to the two-class sampling plan. Introducing a limit for the additional risk of rejection of an indifference lot with acceptable heterogeneity when the three-class sampling plan is applied, a criterion for choosing the distance between m and M is developed.
Dahms
S
S
Institut für Biometrie und Informationsverarbeitung, Freie Universität Berlin, Germany.
Hildebrandt
G
G
D001431:Bacteriological Techniques; D015169:Colony Count, Microbial / Q000379:methods*; D019649:Food Industry / Q000592:standards*; D005516:Food Microbiology; D008962:Models, Theoretical; D011786:Quality Control