Submitted to: Journal of Association of Official Analytical Chemists International
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/1/2001
Publication Date: 12/1/2002
Citation: VANDEVEN, M., WHITAKER, T.B., SLATE, A.B. STATISTICAL APPROACH FOR RISK ASSESSMENT OF AFLATOXIN SAMPLING PLAN USED BY MANUFACTURERS FOR RAW SHELLED PEANUTS. JOURNAL OF ASSOCIATION OF OFFICIAL ANALYTICAL CHEMISTS INTERNATIONAL. 2002. v. 85. p. 925-932.
Interpretive Summary: Aflatoxin is a carcinogenic compound produced by fungi that grow on agricultural commodities under certain environmental conditions. The Food and Drug Administration inspects finish products for aflatoxin to determine if the product exceeds the U.S. guideline of 20 parts per billion. To minimize contaminated product from reaching the grocery shelf, food manufacturers inspect raw product coming into the plant for aflatoxin and remove product that may exceed their aflatoxin limit which is usually less than the FDA guideline. Because of the uncertainty associated with the aflatoxin test procedure, it is possible for some bad product (exceeds the manufacturer's aflatoxin limit) to be accepted as good product(consumer's risk) and some good product to be rejected as bad product (manufacturer's risk) by the aflatoxin control program. An evaluation method was developed to predict the consumer's and manufacturer's risks associated with various aflatoxin control strategies used by manufacturer's to reduce contaminated product from reaching consumers. The method was illustrated by evaluating the performance of an aflatoxin control program used by a leading manufacturer of consumer peanut products and demonstrating how various parameters of the control program can be changed to reduce both the consumer's and manufacturer's risks.
Technical Abstract: Processed food manufacturers often use acceptance-sampling plans to screen out lots with unacceptable levels of contamination from incoming raw material streams. Sampling plan designs are determined by specifying sample sizes, sample preparation methods, analytical test methods, and accept/reject criteria. Sampling plan performance can be indicated by plotting acceptance probability versus contamination level as an operating characteristic (OC) curve. In practice, actual plan performance depends on the level of contamination in the incoming lot stream. This level can vary considerably over time, among different crop varieties, and locales. To better gauge plan performance, a method of coupling an OC curve and crop distributions is proposed. The method provides a precise probabilistic statement about risk and can be easily carried out using commercial spreadsheet software.