title: Sampling hazelnuts for aflatoxin: effect of sample size and accept/reject limit on reducing the risk of misclassifying lots.
abstract: About 100 countries have established regulatory limits for aflatoxin in food and feeds. Because these limits vary widely among regulating countries, the Codex Committee on Food Additives and Contaminants began work in 2004 to harmonize aflatoxin limits and sampling plans for aflatoxin in almonds, pistachios, hazelnuts, and Brazil nuts. Studies were developed to measure the uncertainty and distribution among replicated sample aflatoxin test results taken from aflatoxin-contaminated treenut lots. The uncertainty and distribution information is used to develop a model that can evaluate the performance (risk of misclassifying lots) of aflatoxin sampling plan designs for treenuts. Once the performance of aflatoxin sampling plans can be predicted, they can be designed to reduce the risks of misclassifying lots traded in either the domestic or export markets. A method was developed to evaluate the performance of sampling plans designed to detect aflatoxin in hazelnuts lots. Twenty hazelnut lots with varying levels of contamination were sampled according to an experimental protocol where 16 test samples were taken from each lot. The observed aflatoxin distribution among the 16 aflatoxin sample test results was compared to lognormal, compound gamma, and negative binomial distributions. The negative binomial distribution was selected to model aflatoxin distribution among sample test results because it gave acceptable fits to observed distributions among sample test results taken from a wide range of lot concentrations. Using the negative binomial distribution, computer models were developed to calculate operating characteristic curves for specific aflatoxin sampling plan designs. The effect of sample size and accept/reject limits on the chances of rejecting good lots (sellers' risk) and accepting bad lots (buyers' risk) was demonstrated for various sampling plan designs.
authors.affiliation: TUBITAK Marmara Research Center, Food Institute, PO Box 21, 41470 Gebze Kocaeli, Turkey.
authors.forename: Guner
authors.initials: G
authors.lastname: Ozay
authors.forename: Ferda
authors.initials: F
authors.lastname: Seyhan
authors.forename: Aysun
authors.initials: A
authors.lastname: Yilmaz
authors.forename: Thomas B
authors.initials: TB
authors.lastname: Whitaker
authors.forename: Andrew B
authors.initials: AB
authors.lastname: Slate
authors.forename: Francis G
authors.initials: FG
authors.lastname: Giesbrecht
mesh_terms: D000348:Aflatoxins / Q000032:analysis*; D002623:Chemistry Techniques, Analytical / Q000379:methods*; D002626:Chemistry, Pharmaceutical / Q000379:methods*; D002851:Chromatography, High Pressure Liquid; D031211:Corylus / Q000737:chemistry*; D005504:Food Analysis / Q000379:methods*; D005506:Food Contamination; D015233:Models, Statistical; D009793:Ochratoxins / Q000032:analysis; D015203:Reproducibility of Results; D012107:Research Design; D012306:Risk; D018401:Sample Size; D012680:Sensitivity and Specificity; D012984:Software
chemical_list: D000348:Aflatoxins; D009793:Ochratoxins