Sampling for biotech grain is no different than sampling for any other characteristic in grain. Whether the sample is taken to measure biotech kernels or to measure damaged kernels, a representative sample is necessary to apply probability to describe buyer and seller risks. GIPSA has instructions for taking samples from static lots - such as trucks, barges, and railcars - and for taking samples from grain streams.  GIPSA's Grain Inspection Handbook, Book 1, Grain Sampling and Rice Inspection Handbook, Chapter 2, Sampling, contain these instructions.

When the desired concentration of a specific trait is zero, a single qualitative test would be an adequate testing plan. These sample plans assume that a single kernel can be detected in a sample, regardless of the size of the sample. When sampling is used to estimate the concentration in a lot, sampling error will always be present. A negative result or test does not guarantee that some concentration doesn’t exist in the lot. Probability can be used to describe the risks associated with accepting lots with certain concentrations in the lot.

The sample plans assume that one biotech kernel in a sample can be detected, regardless of the size of the sample. In practice, however, analytical methods may have limits on the concentrations that are detectable. For example, an analytical method may only be able to reliably detect one biotech kernel in a sample of 400 kernels. Testing larger samples with this analytical method, as a single test, is not advisable. Large samples can be tested with this analytical method if the large sample is divided into subsamples of 400 kernels or less and then each subsample is tested.

The following table gives samples sizes for selected lot concentrations and probability of rejecting the specified concentrations. Sample sizes for other combinations can be computed with the formula:

n=log(1-(G/100))/log(1-(P/100))

n is the sample size (number of kernels),

G is the probability of rejecting a lot concentration, and

P is percent concentration in the lot.

Some analytical methods may not be able to accommodate large sample sizes. For example, a test kit manufacturer may recommend that the sample contain no more than 400 kernels. A marketer may decide that a 95% rejection rate on a 0.1 percent concentration is acceptable risk. The corresponding sample size is 2995 kernels. The test kit is not recommended for use with 2995 kernel samples. The same approximate risk can be obtained by testing eight samples of 400 kernels and requiring that all test results must be negative. (2995 kernels/400 kernels = 7.49 or 8 samples.) The false positive and false negative error rates for the test kit are assumed to be essentially zero with a 400 kernel sample.

The largest sample size in the preceding table is nearly 3 kg. Some applicants may desire even more stringent requirements. To insure that the sample is large enough to accommodate most applicants, a 5 kg sample is recommended for the original sample from the lot. The test sample can always be reduced in the laboratory to the appropriate size.

Sampling is only one source of error in measurements. Sample preparation and analytical method contribute to measurement variation. Grinding and subsampling are usually required as part of the sample preparation. Samples must be thoroughly ground and mixed before subsampling to minimize sample preparation errors. Particle size recommendations may be dependent on the analytical method being used or on the manufacturer recommendations. For DNA testing, a particle size of 200 m or smaller is generally recommended.

Carry over of materials from one sample to another takes on an even greater significance during sample preparation prior to analysis. Due to the sensitivity seen with many methods for detection of biotech grains, care must be taken to avoid transferring materials to subsequent samples. Whole grains, dust and residual matter must be removed from all equipment. Grinders should be cleaned through vacuuming of dust, washing with soap and water or solvents, or a combination of appropriate cleaning methods for the specific grinder in use. Sample dividers and mixers must also be thoroughly cleaned. Analysts should verify the equipment cleaning process is appropriate to prevent cross contamination. Many of the analytical techniques practiced for detection of biotech crops today can detect levels lower than 0.1%. Physical separation of sample preparation operations from analytical operations is also highly recommended to avoid contamination of sample extracts.

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