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Related Experiment Videos

Testing shelled corn for aflatoxin, Part I: estimation of variance components.

A S Johansson1, T B Whitaker, W M Hagler

  • 1US Department of Agriculture, Agricultural Research Service, North Carolina State University, Raleigh 27695-7625, USA.

Journal of AOAC International
|October 26, 2000
PubMed
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Testing shelled corn for aflatoxin contamination shows that total variance increases with concentration. Sampling variance is the largest contributor, highlighting the need for optimized testing methods to ensure accurate aflatoxin detection.

Area of Science:

  • Agricultural Science
  • Food Safety
  • Analytical Chemistry

Background:

  • Aflatoxins are toxic secondary metabolites produced by certain fungi, posing significant health risks in food commodities.
  • Accurate quantification of aflatoxins in shelled corn is crucial for regulatory compliance and consumer protection.
  • Variability in testing procedures can impact the reliability of aflatoxin measurements.

Purpose of the Study:

  • To investigate and quantify the sources of variability in testing shelled corn for aflatoxin contamination.
  • To develop mathematical models to predict testing variance based on aflatoxin concentration and testing parameters.
  • To partition the total variance into sampling, sample preparation, and analytical components.

Main Methods:

  • Tested eighteen lots of shelled corn for aflatoxin contamination.

Related Experiment Videos

  • Estimated and partitioned total variance into sampling, sample preparation, and analytical variances.
  • Utilized regression analysis to model the relationship between aflatoxin concentration and different variance components.

    • Main Results:

    • All variance components (total, sampling, sample preparation, analytical) increased with higher aflatoxin concentrations.
    • Developed mathematical expressions to model these relationships, enabling variance estimation for various testing parameters.
    • For a sample with 20 ppb aflatoxin, sampling variance constituted 77.8% of the total variance.

    Conclusions:

    • Sampling is the predominant source of variability in shelled corn aflatoxin testing, especially at higher concentrations.
    • The developed models can guide the optimization of sample size, subsample size, and analytical methods for improved accuracy.
    • Understanding and controlling variance sources are essential for reliable aflatoxin testing in agricultural products.