United States Agency for International Development

The definitions for the purpose of the Codex Alimentarius, as mentioned in the Procedural Manual, are applicable to the General Standard for Contaminants and Toxins in Food and Feed (GSCTFF) and only the most important ones are repeated here. Some new definitions are introduced, where this seems warranted to obtain optimal clarity. When reference is made to foods, this also applies to animal feed, in those cases where this is appropriate. 1.2.2 Contaminant Codex Alimentarius defines a contaminant as follows: “Any substance not intentionally added to food, which is present in such food as a result of the production (including operations carried out in crop husbandry, animal husbandry and veterinary medicine), manufacture, processing, preparation, treatment, packing, packaging, transport or holding of such food or as a result of environmental contamination. The term does not include insect fragments, rodent hairs and other extraneous matter”. This standard applies to any substance that meets the terms of the Codex definition for a contaminant, including contaminants in feed for food-producing animals, except:

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Codex general standard for contaminants and toxins in food and feed

An overview is presented of the analysis of mycotoxins by rapid methods such as: enzyme linked immunosorbent assay (ELISA); flow through membrane based immunoassay; immunochromatographic assay; fluorometric assay with immunoaffinity clean-up column or with a solid phase extraction clean-up column; and fluorescence polarization method. These methods are currently commercially available and are reliable, rapid methods. This review focuses on the basic principle of each rapid method as well as advantages and limitations of each method. Additionally, we address other emerging technologies of potential application in the analysis of mycotoxins.

A review of rapid methods for the analysis of mycotoxins.

Health and Trade Issues Mycotoxin Contamination and Toxigenic Fungi in Africa and the Mediterranean Basin Mycotoxin Detection Methods Mycotoxin Management Institutional Issues in Mycotoxin Management International Programs on Mycotoxins.

Mycotoxins: Detection Methods, Management, Public Health and Agricultural Trade

Mycotoxins are natural contaminants produced by a range of fungal species. Their common occurrence in food and feed poses a threat to the health of humans and animals. This threat is caused either by the direct contamination of agricultural commodities or by a “carry-over” of mycotoxins and their metabolites into animal tissues, milk, and eggs after feeding of contaminated hay or corn. As a consequence of their diverse chemical structures and varying physical properties, mycotoxins exhibit a wide range of biological effects. Individual mycotoxins can be genotoxic, mutagenic, carcinogenic, teratogenic, and oestrogenic. To protect consumer health and to reduce economic losses, surveillance and control of mycotoxins in food and feed has become a major objective for producers, regulatory authorities and researchers worldwide. However, the variety of chemical structures makes it impossible to use one single technique for mycotoxin analysis. Hence, a vast number of analytical methods has been developed and validated. The heterogeneity of food matrices combined with the demand for a fast, simultaneous and accurate determination of multiple mycotoxins creates enormous challenges for routine analysis. The most crucial issues will be discussed in this review. These are (1) the collection of representative samples, (2) the performance of classical and emerging analytical methods based on chromatographic or immunochemical techniques, (3) the validation of official methods for enforcement, and (4) the limitations and future prospects of the current methods.

Determination of mycotoxins in foods: current state of analytical methods and limitations

Using 12 lb samples, 280 g subsamples, the Waltking method of analysis, and densitometric procedures, the sampling, subsampling, and analytical variances associated with aflatoxin test procedures were estimated. Regression analysis indicated that each of the above variance components is a function of the concentration of aflatoxin in the population being tested. Results, for the test procedures given above, showed that sampling constitutes the greatest single source of error, followed by subsampling and analysis. Functional relationships are presented to determine the sampling, subsampling, and analytical variance for any size sample, subsample, and number of analyses.

Variability of aflatoxin test results.

Suitability of the negative binomial distribution for use in estimating the probabilities associated with sampling lots of shelled peanuts for aflatoxin analysis has been studied. Large samples, called “minilots,” were drawn from 29 lots of shelled peanuts contaminated with aflatoxin. These minilots were subdivided into ca. 12 lb samples which were analyzed for aflatoxin. The mean and variance of these aflatoxin determinations for each minilot were determined. The shape parameterk and the mean aflatoxin concentrationm were estimated for each minilot. A regression analysis indicated the functional relationship betweenk andm to be:k=(2.0866+2.3898m) × 10−6. The observed distribution of sample concentrations from each of the 29 minilots was compared to the negative binomial distribution by means of the Kolmogorov-Smirnov test. The null hypothesis that each of the true unknown distribution functions was negative binomial was not rejected at the 5% significance level for all 29 comparisons.

Comparison of the observed distribution of aflatoxin in shelled peanuts to the negative binomial distribution

The sampling, subsampling (both coarse and fine ground meal), and analytical variances associated with testing shelled corn for aflatoxin were estimated by the use of 500 g samples, 50 g subsamples, and the CB method of analysis. The magnitudes of the variance components increased with an increase in the aflatoxin concentration. Functional relationships were developed to predict the variance for a given aflatoxin concentration and any size sample, subsample, and number of analyses. At 20 ppb total aflatoxin, the coefficient of variantion associated with a 4.54 kg sample, 1 kg subsample of coarsely ground meal (passes a #14 screen), a 50 g subsample of finely ground meal (passes a #20 screen) and one analysis were 21, 8, 11, and 26%, respectively.

Variability associated with testing corn for aflatoxin

The sampling, subsampling, and analytical variance associated with testing cottonseed for aflatoxin were estimated by use of 4.54 kg samples, 100 g subsamples, and the Velasco method of analysis. Regression analysis indicated that each of the above variance components is a function of the concentration of aflatoxin in the populations tested. Functional relationships are presented to determine the sampling, subsampling, and analytical variance for any size sample, subsample, and number of analyses.

Variability associated with testing cottonseed for aflatoxin

A water slurry method in which 1100 g of comminuted peanuts was blended with 1500 ml of tap water for 3 min in a blender and the aflatoxin in a 130-g portion of the water slurry was extracted by solvent according to methods similar to those used in Method II of AOAC was compared to the method presently used by the Food Safety and Quality Service, USDA. The proposed water slurry method requires only 180 and 60 ml per sample, respectively, of methanol and hexane compared to the 1650 and 1000 ml, respectively, required by the FSQS method. Blending comminuted peanuts with water reduced the average particle size and distributed the contaminated particles throughout the slurry. Ninety-four percent of the blended particles passed a sieve with 149-μ openings compared to only 66% of the unblended product. Variance among analyses with the FSQS method did not differ significantly from the variance among analyses with the slurry method. However, analyses with the slurry method averaged 16% more aflatoxin than with the FSQS method.

R. J. Monroe

Papers

Variability of aflatoxin test results.

Comparison of the observed distribution of aflatoxin in shelled peanuts to the negative binomial distribution

Variability associated with testing corn for aflatoxin

Variability associated with testing cottonseed for aflatoxin

A water slurry method of extracting aflatoxin from peanuts.