Develop Methods To Evaluate the Performance of Aflatoxin Sampling Plans for Shelled Corn.

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Title: Develop Methods To Evaluate the Performance of Aflatoxin Sampling Plans for Shelled Corn.
Author: Johansson, Anders Sture
Advisors: Thomas B. Whitaker, Chair
Francis G. Giesbrecht, Member
Winston M. Hagler, Jr., Member
James H. Young, Member
Abstract: Eighteen lots of shelled corn were tested for aflatoxin contamination. The variability and distributional characteristics associated with the aflatoxin testing procedure were investigated. The total variance associated with testing shelled corn was estimated and partitioned into sampling, sample preparation, and analytical variances. All variances were found to increase with an increase in aflatoxin concentration. Using regression analysis, mathematical expressions were developed to model the relationship between aflatoxin concentration and the total, sampling, sample preparation, and analytical variances. The expressions for these relationships were used to estimate the variance for any sample size, subsample size, and number of analyses for a specific aflatoxin concentration. For example, testing a lot with 20 parts per billion (ppb) aflatoxin using a 2.5 lb sample, Romer mill and 50 g subsample, and HPLC analysis, the total, sampling, sample preparation, and analytical variances are 274.9 (CV=82.9%), 214.0 (CV=73.1%), 56.3 (CV=37.5%), and 4.6 (CV=10.7%), respectively. The percentage of the total variance for sampling, sample preparation, and analytical is 77.8, 20.5, and 1.7 %, respectively. Next, fifteen positively skewed distributions were each fitted to 18 empirical distributions of aflatoxin test results for shelled corn. The compound gamma distribution was selected to model the sample aflatoxin test results for shelled corn. The method of moments technique was chosen to estimate the parameters of the compound gamma distribution. Mathematical expressions were developed to calculate the parameters of the compound gamma distribution for any lot aflatoxin concentration and test procedure. Observed acceptance probabilities were compared to operating characteristic curves predicted from the compound gamma distribution and all 18 distributions of sample aflatoxin test results were found to lie within a 95% confidence band. Using the mean and variance relationships to compute the parameters of the compound gamma distribution, 16 sampling plans, based on four sample sizes and four sample acceptance levels were created and analyzed. For a given sample size, decreasing the sample acceptance level, using a sample acceptance level equal to the regulatory guideline: (a) decreases the percentage of lots accepted while increasing the percentage of lots rejected at all aflatoxin concentrations; (b) increases misclassification of lots (both false positives and false negatives) while decreasing the percentage of correct decisions; and (c) decreases the average aflatoxin concentration in the lots accepted and lots rejected. For a given sample size where the sample acceptance level is less than the regulatory guideline, the number of false positives increases and the number of false negatives decreases when compared to the situation where the sample acceptance level equals the regulatory guideline. For a given sample size, where the sample acceptance level is greater than the regulatory guideline, the number of false positives decreases and the number of false negatives increases when compared to the situation where the sample acceptance level equals the regulatory guideline. Increasing the sample size for a given sample acceptance level, where the legal limit equals the sample acceptance level: (a) increases the percentage of lots accepted at lower concentrations while increasing the percentage of lots rejected at higher concentrations; (b) decreases misclassification of lots (both false positives and false negatives) while increasing the percentage of correct decisions; and (c) decreases the average aflatoxin concentration in the lots accepted while increasing the average aflatoxin concentration in the rejected lots.
Date: 1998-12-29
Degree: PhD
Discipline: Biological and Agricultural Engineering
URI: http://www.lib.ncsu.edu/resolver/1840.16/5937


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