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United States Department of Agriculture

Agricultural Research Service

Related Topics

Research Project: IMPROVE THE DETECTION OF QUALITY ATTRIBUTES AND CHEMICAL AGENTS IN AGRICULTURAL COMMODITIES

Location: Market Quality and Handling Research

2008 Annual Report


1a.Objectives (from AD-416)
Objective 1 - Develop sampling plans that minimize buyers' risk (bad lots accepted) and sellers' risk (good lots rejected) when detecting quality attributes in agricultural commodities. Sampling plans will be developed to detect the following attributes in foods: aflatoxin in almonds, genetically modified (GM) proteins in grains, peanut proteins (allergens) in foods, foreign material (FM) in shelled peanuts, and TCK spores in wheat.

Objective 2 - Determine the percentage of total aflatoxin in farmers' stock peanuts that is partitioned into each milled peanut category (jumbo, medium, number one, splits, oil stock, loose shelled kernels, and discolored or damaged kernels) during the shelling process.

Objective 3 - Develop sampling plans for biosecurity purposes that maximize the chance of detecting various food matrices intentionally adulterated with biological and/or chemical agents.


1b.Approach (from AD-416)
Objective 1 - Experiments are designed to obtain variability and distributional data to construct operating characteristic (OC) curves which can be used to predict the performance of sampling plan designs to detect specific quality attributes in a food matrix. From the OC curve, the false positives (sellers' risk or good lots rejected) and false negatives (buyers' risk or bad lots accepted) for specific sampling plan can be determined.

Objective 2 - Forty 50-kg samples of farmers' stock (FS) peanuts, contaminated with varying levels of aflatoxin, will each be processed in an USDA, ARS pilot shelling plant. Each 50-kg sample will be divided into loose-shelled kernels (LSK) and in-shell peanuts. The in-shell peanuts will be shelled and the shelled kernels will be sized into five commercial peanut grades, jumbo, medium, number ones, splits, and oil stock. Shelled kernels in each grade will be color sorted into accepts and rejects components for a total of 10 categories (5 size grades x 2 accept/reject components). The LSK will also be sized in a like manner into the same five commercial grades and color sorted into accept/reject components or 10 categories. After the peanuts in each of the 20 categories are weighed, the aflatoxin in each of the 20 categories will be measured. From the weights and aflatoxin values in each category, a mass balance can be used to compute aflatoxin in all kernels before sorting by size and color. Then, the percentage of total aflatoxin in the FS peanuts before shelling, sizing, and color sorting that is partitioned into each of the 20 categories will be determined.

Objective 3 -The development of mathematical models requires the measurement of chemical or biological agents among replicate samples taken from contaminated lots, from which variability and distributional characteristics provide the basis for development of statistical models and prediction of validity, reliability, and feasibility (false positives and false negatives) associated with various sample plan designs.


3.Progress Report
Progress relates to National Program 306 Quality and Utilization of Agricultural Products, Component 1 Quality characterization, preservation, and enhancement, Problem Area 1b Methods to Evaluate and Predict Quality).

(1) As part of a Codex effort to develop aflatoxin limits and sampling plans for treenuts, the variability and distribution among aflatoxin sample test results was determined for Brazil nuts. A model was developed, using the variance equations and the negative binomial distribution to predict the effect of various samples size and maximum limits on the performance of sampling plan designs. (2) Determine which almond grade categories were aflatoxin risk categories. Almonds were partitioned into high quality kernels, insect damage, mold damage, mechanical damage, and other defects. The high quality kernels accounted for 83.6% of the total kernel mass and 3.6% of the total aflatoxin mass in the samples. All defects combined accounted for 16.4% of the total kernels mass and 96.4% of the total aflatoxin mass. (3) Studies determined the efficiency of electronic color sorting (ECS) and hand sorting (HS) methods at removing aflatoxin-contaminated kernels from lots of raw shelled almonds. Hand sorting method appeared to remove a higher percentage of aflatoxin mass from the input stream, have a higher aflatoxin concentration in the rejects, and reject fewer kernels than the ECS method. (4) The Food and Veterinary Office of the EC audited the US almond industry’s aflatoxin control program in 2006. After evaluation, the industry developed, with assistance from MQHR Unit, an industry wide aflatoxin-sampling program (VASP) for lots exported to the EU. The database was developed and analyzed to demonstrate the effectiveness of the VASP program. Results were shared with industry, USDA/FAS, AMS, and EC officials who formally requested the removal of the almond industry from EC Special Measures. (5) Because the EU is expected to revise their aflatoxin legislation for treenuts to be compatible with the limits and sampling plans adopted by Codex, predicted the performance of 5 aflatoxin-sampling plans for consideration by the almond industry. (6) Working with the American Peanut Council, assisted in the development of experimental design to determine the extent of salmonella in raw shelled peanuts.


4.Accomplishments
1. Development of Codex standard for aflatoxin limits and sampling plans for treenuts – Because over 100 countries have differing aflatoxin limits and sampling plans for foods, Codex Committee for Contaminants in Foods (CCCF) initiated a program to promote export trade and increase consumer safety by harmonizing aflatoxin limits and sampling plans for almonds, pistachios, hazelnuts, and Brazil nuts. Developed computer models for the US delegation to CCCF and designed draft-sampling plans with varying limits and sample sizes for CCCF consideration. Based upon performance curves computed with the model, CCCF agreed on specific aflatoxin limits and sampling plans for treenuts destined for further processing and ready-to-eat treenuts at their second meeting in The Hague in April 2008. The Codex Alimentarius Commission adopted CCCF recommendations in July 2008. Harmonized aflatoxin limits and sampling plans will result in less disruption in supply to the end-user, lower costs for exporter due to fewer lot rejections, and a safer food supply for the consumer.

This accomplishment relates to National Program 306 Quality and Utilization of Agricultural Products, Component 1 Quality characterization, preservation, and enhancement, Problem Area 1b Methods to Evaluate and Predict Quality.

2. Ratio of aflatoxin B1 to total aflatoxin – The European Union, the largest importer of US ground nut and treenut products, has dual aflatoxin regulatory limits of 2 ng/g B1 and 4 ng/g total aflatoxins (Total = B1 + B2 + G1 + G2). US exporters have noticed that more lots are rejected on B1 than total aflatoxin indicating the ratio of B1/Total must be greater than 50%. Studies were developed to determine the mean, median, and distribution among ratio values of B1/Total aflatoxin for US almonds, pistachios, and peanuts. Studies demonstrated that the mean ratios for peanuts, almonds, and pistachios were 79, 85, and 88%, respectively, and the distribution was negatively skewed for all three-nut products, which indicates that the median is a better parameter to use in setting B1 limits. These results have been shared with each commodity industry, USDA/FAS and AMS, and the European Commission who are currently revising EU aflatoxin legislations to be compatible with the newly adopted Codex aflatoxin standards for treenuts. These results have shown that setting B1 limits based upon the assumption that the B1/total ratio is 50% is incorrect, trade restrictive, and costly to US exporters.

This accomplishment relates to National Program 306 Quality and Utilization of Agricultural Products, Component 1 Quality characterization, preservation, and enhancement, Problem Area 1b Methods to Evaluate and Predict Quality.


5.Significant Activities that Support Special Target Populations
None.


6.Technology Transfer

Number of Newspaper Articles and Other Presentations for Non-Science Audiences6

Review Publications
Whitaker, T.B. 2005. Sampling foods for mycotoxins. Journal of Food Additives & Contaminants.

Park, D.L., Whitaker, T.B., Simonson, J., Morris, H.F., Durr, B., Njapau, H. 2007. Determining the variablity associated with testing shelled corn for aflatoxin using different analytical procedures in Louisiana in 1998. Journal of Association of Official Analytical Chemists International 68(6):1306-1313.

Whitaker, T.B., Doko, M.B., Maestroni, B.M., Slate, A.B., Ogunbanwo, B.F. 2007. Evaluating the performance of sampling plans to detect fumonisn B1 (FB1) in maize lots marketted in Nigeria. Journal of Association of Official Analytical Chemists International 90:1050-1059.

Whitaker, T.B., Saltsman, J.S., Ware, G.M., Slate, A.B. 2007. Evaluating the performance of sampling plans to detect hypoglycin A in ackee fruit shipments imported into the United States. Official Methods of Analysis of AOAC International 90:4.

Whitaker, T.B., Dorner, J.W., Lamb, M.C., Slate, A. 2007. The effect of sorting farmers' stock peanuts by size and color on partitioning aflatoxin into various shelled peanut grade sizes. Peanut Science 32:103-118.

Whitaker, T.B., Slate, A., Greene, J., Hendrix, K., Sanders, T.H. 2007. Uncertainty associated with sampling peanuts to determine fruity-fermented off flavor. Peanut Science 34:126-134.

Last Modified: 10/1/2014
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