Submitted to: Journal of Association of Official Analytical Chemists International
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/24/2001
Publication Date: 11/15/2001
Citation: WHITAKER, T.B., FREESE, L., GIESBRECHT, F.G., SLATE, A.B. SAMPLING GRAIN SHIPMENTS TO DETECT GENETICALLY MODIFIED SEED. JOURNAL OF ASSOCIATION OF OFFICIAL ANALYTICAL CHEMISTS INTERNATIONAL. 2001. v. 84. p. 1941-1946.
Interpretive Summary: Some genetically modified (GM) grains are approved for animal feed only and cannot be used for human consumption. Some European and Asian countries have placed regulatory tolerances or maximum limits on the percentage of GM seed that can be found in a lot entering their country. Regulatory agencies, such as the FDA, work with the grain industry to inspect grain lots in the consumer market to identify lots containing prohibited GM seed Exporters and importers inspect grain shipments to determine if the percentage of GM seed in a lot is below trading specifications or national tolerances. However, it is difficult to determine the exact percentage of GM seed in large shipments or lots because of the natural variation among sample GM values taken from a contaminated lot. Analyzing many samples taken from the same contaminated lot will produce a wide range of percent GM seed values. As a result, all inspected lots cannot be classified with 100% accuracy into acceptable and unacceptable categories based upon some regulatory tolerance. Some good lots will be rejected (seller's risk) by the sampling plan and some bad lots will be accepted (buyer's risk) by the sampling plan. Methods were developed, using statistical theory, to show how to design sampling plans to reduce the number of grain lots misclassified by a sample design. This will reduce risks to the consumer and economic losses to the seller and buyer of grain shipments.
Technical Abstract: Using the binomial distribution, the effect of sample size on the variability among sample test results when sampling a lot with 1.0% genetically modified (GM) or biotech seed was evaluated. The coefficient of variation, cv, among 500 seed sample test results taken from a lot with truly 1.0% was computed to be 44.5%. Increasing sample size to 1000 seed reduced the cv among sample test results to 31.5%. The effects of sample size and accept/reject limits on the buyer's risk (bad lots accepted) and the seller's risk (good lots rejected) were also evaluated assuming a tolerance of 1.0% GM seed. Increasing sample size decreases both the buyer's and seller's risks at the same time. Using an accept/reject limit below the regulatory tolerance decreases the buyer's risk, but increases the seller's risk. Using an accept/reject limit above the regulatory tolerance decreases the seller's risk but increases the buyer's risk.