Simulation of aflatoxin testing plans for shelled peanuts in the United States and in the export market.

The 1987 United States aflatoxin testing plan for shelled peanuts was designed with a final accept level of 25 parts per billion (ppb) total aflatoxin. Some of the importers of U.S. peanuts use aflatoxin testing plans with accept levels lower than 25 ppb. For example, the accept level of a testing plan used in The Netherlands is 5 ppb B1 or 10 ppb total aflatoxin. Whenever export lots are re-tested for aflatoxin by an importing country, some lots accepted in the United States will be rejected by the importing country's aflatoxin testing plan. Computer models were developed to determine the effects of decreasing the final accept level of the U.S. testing plan on the number of lots accepted and rejected in the United States and the number of exported lots accepted and rejected by The Netherlands testing plan. Decreasing the final accept level of the U.S. testing plan from 25 to 5 ppb increased the number of lots rejected in the United States by 371% while reducing the number of exported lots rejected by 51%. For every additional 8.3 lots rejected in the United States, one less export lot will be rejected.

Optimum methanol concentration and solvent/peanut ratio for extraction of aflatoxin from raw peanuts by modified AOAC method II.

The amount of aflatoxin extracted from raw peanuts by using the water-slurry modification of AOAC Method II was determined for 49 different combinations of methanol concentrations and solvent/peanut ratio. Results indicate that the amount of aflatoxins B1 and B2 extracted from raw peanuts is a function of both methanol concentration and solvent/peanut ratio, and a cubic equation was developed, using regression techniques, to describe the combined effects. From the functional relationship, the predicted methanol concentration and solvent/peanut ratio that extracts the most aflatoxin B1 was computed to be 60.0% and 10.8 mL solvent/g peanuts, respectively. This combination extracted 12.1% more aflatoxin than did AOAC Method II.

Effects of methanol concentration and solvent:peanut ratio on extraction of aflatoxin from raw peanuts.

Aflatoxin B1 was extracted by a water slurry process using methanol concentrations of 55, 60, 65, and 70% in water and solvent:peanut ratios of 3, 4, 5, and 6 mL/g. Results failed to show that methanol concentration had an effect on amount of B1 extracted; however, the amount of B1 extracted increased with an increase in solvent:peanut ratio. Aflatoxin B1 was also extracted by the official AOAC method II, using methanol concentrations of 55, 60, 65, and 70% in water and solvent:peanut ratios of 2, 3, 4, and 5 mL/g. Results showed that the amount of B1 extracted increased with percent methanol at low solvent:peanut ratios but not at high ratios. Also, the amount of B1 extracted increased with solvent:peanut ratios at all methanol concentrations.

Evaluation of a testing program for aflatoxin in corn.

A computer model that accounts for sampling and analytical variability was developed to simulate the aflatoxin testing program administered by the North Carolina Department of Agriculture (NCDA) to regulate aflatoxin in corn meal. Monte Carlo solution techniques were employed to account for conditional probabilities that rise from multiple samples being used in the testing program. The NCDA testing program was then evaluated by applying the computer model to a hypothetical group of 1000 corn meal lots with the same distribution of aflatoxin concentrations as was observed among aflatoxin assays made by NCDA on commercial lots of corn meal from 1977 to 1980. The average of the 1000 lots assayed was 17.7 parts per billion (ppb). The model predicted that 79.5% of the lots would be accepted and 20.5% of the lots would be rejected by the NCDA testing program. The accepted and rejected lots contained an average of 5.7 and 64.2 ppb aflatoxin, respectively. The testing program accepted 7.3% of the lots with more than 20 ppb aflatoxin (consumers' risk) and rejected 1.0% of the lots with 20 ppb or less (processors' risk). A correct decision was made 94% of the time.

Dilution errors in aflatoxin determinations caused by compounds extracted from peanuts.

Several methods have been developed to analyze peanuts for aflatoxin by using thin layer chromatography (TLC). These methods depend on solvent extraction of aflatoxin from a sample of the product. Unfortunately, solvent solutions used to extract aflatoxin from peanuts also extract measurable quantities of other compounds such as oils, fats, sugars, and protein. The volume of these extracted compounds causes error in measuring the proportion of the solvent solution analyzed for aflatoxin. Also, because the cleanup procedures for some methods are inadequate, the volume of some of these extracted compounds also causes error in measuring the proportion of the extracted aflatoxin placed on TLC plates. These 2 errors cause underestimation of aflatoxin concentrations by approximately 11, 14, and 5% for the CB method, the modified version of the BF method generally used for raw peanuts, and a water slurry method, respectively. The correction specified by the CB method for fats in the extraction solvent reduces the approximate error for the CB method from 11 to 1%.

Protocols for surveys, sampling, post-collection handling, and analysis of grain samples involved in mycotoxin problems.

This report examines and summarizes current knowledge regarding mycotoxin surveys, sampling techniques, conditions conducive to post-collection production of mycotoxins in grain samples, and analytical methods for mycotoxin analysis. Priority attention is given to samples of corn suspected of containing aflatoxin. The report includes recommendations where deems appropriate by the Ad Hoc Work Group.

On testing normality using several samples: an analysis of peanut aflatoxin data.

Eight samples of size 16 and three samples of size 15 consisting of replicate determinations of aflatoxin in peanut subsamples were considered. These data were analyzed to decide whether the samples could have arisen from two-parameter normal or lognormal parents. The method of analysis consisted of first transforming the individual samples in such a way that the transformed values had uniform distributions on the unit interval under the null hypothesis. The transformed values were then pooled and tested for uniformity. Results of the analysis indicated that the normal model fitted the data quite well and definitely better than the lognormal model.