Abstract
A computer model that accounts for sampling, subsampling, and analytical variability was developed to simulate aflatoxin testing programs. Monte Carlo solution techniques were employed to account for conditional probabilities that arise from multiple samples, subsamples, and/or analyses being used in testing programs. The aflatoxin testing program to be used on the 1974 peanut crop was evaluated by use of the described model.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Whitaker, T.B., J.W. Dickens, and R.J. Monroe, JAOCS 51:214 (1974).
Whitaker, T.B., J.W. Dickens, R.J. Monroe, and E.H. Wiser, Ibid. 49:590 (1972).
Quesenberry, C.P., T.B. Whitaker, and J.W. Dickens, Biometrics (In press).
Naylor, T.H., J.L. Balintfy, D.S. Curdeck, and Kong Chu, “Computer Simulation Techniques,” John Wiley and Sons, New York, NY, 1967, pp. 43–67.
Hammersley, J.M., and D.C. Handscomb, “Monte Carlo Methods,” Associated Book Publishers Ltd., London, England, 1967, pp. 25–75.
Tocher, K.D., “The Art of Simulation,” England, The English University Press, London, England, 1963, pp. 6–71.
Buslenko, N.P., K.I. Golenko, Yu. A. Shrieder, I.M. Sobol, and V.G. Sragovich, “The Monte Carlo Method,” Pergamon Press, London, England, 1967, pp. 1–90.
Peanut Administrative Committee, Marketing Agreement, 1975.
Whitaker, T.B., J.W. Dickens, and E.H. Wiser, JAOCS 47:501 (1970).
Author information
Authors and Affiliations
Additional information
ARS, USDA, and Biological and Agricultural Engineering Department, North Carolina State University, Raleigh, NC 27607.
About this article
Cite this article
Whitaker, T.B., Dickens, J.W. & Wiser, E.H. Monte carlo technique to simulate aflatoxin testing programs for peanuts. J Am Oil Chem Soc 53, 545–547 (1976). https://doi.org/10.1007/BF02586257
Received:
Issue Date:
DOI: https://doi.org/10.1007/BF02586257