Author
ROSS, THOMAS - University Of Tasmania | |
Fratamico, Pina | |
JAYKUS, LEEANN - North Carolina State University | |
ZWEITERING, MARCEL - University Of Wageningen |
Submitted to: Rapid Detection, Characterization, and Enumeration of Food-Borne Pathogens
Publication Type: Book / Chapter Publication Acceptance Date: 3/11/2011 Publication Date: 6/11/2011 Citation: Ross, T., Fratamico, P.M., Jaykus, L., Zweitering, M. 2011. Statistics of sampling for microbiological testing of foodborne pathogens. In: Hoorfar, J., editor. Rapid Detection, Characterization, and Enumeration of Food-Borne Pathogens. Danvers, MA: ASM Press. p. 103-120. Interpretive Summary: Technical Abstract: Despite the many recent advances in protocols for testing for pathogens in foods, a number of challenges still exist. For example, the microbiological safety of food cannot be completely ensured by testing because microorganisms are not evenly distributed throughout the food. Therefore, since it is not possible to test the entire food lot, a statistical sampling plan must be developed to determine how many samples must be tested to have some confidence that the whole lot is free of the target pathogen. Understanding the reliability of sampling plans is, therefore, important for food safety management. When the level of the target pathogen is high, the sampling error is relatively small; however, when the contamination level is low, the error based on presence/absence tests can be large and affect the interpretation of results. Advances in the analysis of microbiological sampling plans have presented analytical approaches to accommodate the influence of sampling errors. However, although a well-designed sampling plan improves the probability of detecting microorganisms in food, no sampling plan can completely ensure the absence of a particular organism in a particular lot of food. This chapter describes the basic concepts of sampling plan nomenclature, design, and interpretation, complementing the other chapters in this text, which cover rapid detection, identification, and enumeration technologies. |