Variability and distribution among sample test results when sampling unprocessed wheat lots for ochratoxin A

2016 ◽  
Vol 9 (2) ◽  
pp. 163-178 ◽  
Author(s):  
T.B. Whitaker ◽  
A.B. Slate ◽  
T.W. Nowicki ◽  
F.G. Giesbrecht
Keyword(s):  
Liquid Chromatography ◽  
Sample Preparation ◽  
Ochratoxin A ◽  
Test Procedure ◽  
Test Results ◽  
Laboratory Sample ◽  
Sampling Step ◽  
Test Portion ◽  
Sample Test ◽  
Sampling Statistics

In 2008, Health Canada announced it was considering the establishment of maximum levels for ochratoxin A (OTA) in unprocessed wheat, oats, and their products. The Canada Grains Council and Canadian National Millers Association initiated two studies to measure the variability and distribution among sample test results for unprocessed wheat and oats so that scientifically based OTA sampling plans could be designed to meet regulatory and industry requirements. Sampling statistics related to detecting OTA in oats has been published. 54 OTA contaminated wheat lots representing three wheat classes were identified for the sampling study. Each lot was sampled according to a nested experimental protocol where sixteen 2-kg laboratory samples were taken from each lot, multiple 5-g test portions were taken from each comminuted 2-kg laboratory sample, and multiple OTA measurements were made on each test portion using liquid chromatography. The sampling, sample preparation, and analytical variances associated with each step of the OTA test procedure were found to be a function of OTA concentration and regression equations were developed to predict the functional relationships between variance and OTA concentration. When sampling a wheat lot containing 5 µg/kg OTA with an OTA test procedure consisting of a sampling step employing a single 2-kg laboratory sample, sample preparation step employing a single 100-g test portion, and an analytical step that used liquid chromatography to quantify OTA, the sampling step accounted for 95.3% of the total variability. The observed OTA distribution among the 16 OTA sample results was found to be positively skewed and the negative binomial distribution was selected to model the OTA distribution among sample test results. The sampling statistics were incorporated into the FAO Mycotoxin Sampling Tool and the chances of rejecting good lots and accepting bad lots were calculated for various sampling plan designs.

Variability and distribution among sample test results when sampling unprocessed oat lots for ochratoxin A

2015 ◽  
Vol 8 (4) ◽  
pp. 511-524 ◽  
Author(s):  
T.B. Whitaker ◽  
A.B. Slate ◽  
T.W. Nowicki ◽  
F.G. Giesbrecht
Keyword(s):  
Ochratoxin A ◽  
Negative Binomial ◽  
Test Procedure ◽  
Regression Equations ◽  
Test Results ◽  
Sampling Step ◽  
Test Portion ◽  
Sample Test ◽  
Total Variability ◽  
Sampling Statistics

In 2008, Health Canada announced it was considering the establishment of maximum levels for ochratoxin A (OTA) in a number of foods, including unprocessed wheat and oats and their products. The Canada Grains Council and Canadian National Millers Association initiated a study to measure the variability and distribution among sample test results so that scientifically based sampling plans could be designed to meet regulatory and industry requirements. Twenty lots of oats naturally contaminated with OTA were identified and sampled according to a nested experimental protocol where 16-two kg laboratory samples were taken from each lot, two 100 g test portions were taken from each comminuted laboratory sample, and two aliquots of the extract from each test portion were analysed for OTA by LC. The variance associated with each step of the OTA test procedure were found to be a function of OTA concentration and regression equations were developed to predict the functional relationship. When using the above OTA test procedure on an oat lot at 5 μg/kg, the sampling, sample preparation, analytical, and total variances were 11.26, 0.10, 0.13 and 11.49, respectively. The 2 kg sampling step accounted for 98.0% (11.26/11.49) of the total variability. The observed OTA distribution among the 16 OTA sample results was found to be positively skewed and the negative binomial distribution was selected to model the OTA distribution among sample test results. The sampling statistics were incorporated into the FAO Mycotoxin Sampling Tool where operating characteristic curves were calculated to predict the chances of rejecting good lots (seller’s risk) and accepting bad lots (buyer’s risk) for various sampling plan designs.

Comparing the USDA/AMS Subsampling Mill to a Vertical Cutter Mixer Type Mill Used to Comminute Shelled Peanut Samples for Aflatoxin Analysis1

2012 ◽  
Vol 39 (1) ◽  
pp. 69-81 ◽  
Author(s):  
Thomas B. Whitaker ◽  
Andrew B. Slate
Keyword(s):  
Operating Characteristic ◽  
Test Procedure ◽  
Sampling Plan ◽  
Test Results ◽  
Test Portion ◽  
Two Samples ◽  
The Us ◽  
Sample Test ◽  
Total Variability ◽  
Very High

Abstract The US peanut industry can use up to three 21.8 kg samples per lot to determine if shelled peanut lots are acceptable or unacceptable due to aflatoxin content. If a lot is accepted by the first 21.8 kg sample (1AB≤8 ng/g) prepared with the USDA/AMS Subsampling mill (DM), then some peanut buyers request that the sheller prepare the second sample (2AB) and in some cases the 3AB sample (called special samples in the trade) with a vertical cutter mixer (VCM) type mill. These requests to specifically use the VCM instead of the DM to prepare official (1AB) and special (2AB or 3AB) samples is based in part on a perception that analytical results associated with a test portion taken from the 21.8 kg sample comminuted with a DM does not detect the full magnitude of aflatoxin in the 21.8 kg sample and that negative aflatoxin certificates (lot acceptance) are more likely to occur when samples are prepared with a DM than a VCM. Analysis of aflatoxin test results from two shellers along with Monte Carlo simulation indicate that differences between the 1AB and special sample test results are due to the use of a cut-off limit (≤ 8 ng/g associated with the 1AB) requested by the buyer as part of the acceptance criteria and not due to any bias associated with the DM. Operating characteristic curves were used to demonstrate that the performance of the USDA/AMS aflatoxin sampling plan is about the same regardless of the use of a DM or a VCM for sample preparation. The performances are similar because the DM, with an 1100 g test portion, account for only 8% of the total variability of the aflatoxin test procedure (sampling and analysis account for about 92%). A sampling plan that requires two 21.8 kg samples to test less than a limit, regardless of mill used to prepare the two samples, has a very low risk of accepting bad lots above the FDA limit of 20 ng/g, but has a very high risk of rejecting good lots, which makes for an extremely high economic burden on the sheller.

Sampling dried figs for aflatoxin – Part 1: variability associated with sampling, sample preparation, and analysis

2017 ◽  
Vol 10 (1) ◽  
pp. 31-40 ◽  
Author(s):  
H. Ozer ◽  
H.I. Oktay Basegmez ◽  
T.B. Whitaker ◽  
A.B. Slate ◽  
F.G. Giesbrecht
Keyword(s):  
Sample Preparation ◽  
Test Procedure ◽  
Portion Size ◽  
Total Variance ◽  
Sampling Variance ◽  
Regression Equations ◽  
Sampling Step ◽  
Test Portion ◽  
Analytical Variance ◽  
Aflatoxin Concentration

The variability associated with the aflatoxin test procedure used to estimate aflatoxins in bulk shipments of dried figs was investigated. Sixteen 10 kg laboratory samples were taken from each of twenty commercial bulk lots of dried figs suspected of aflatoxin contamination. Two 55 g test portions were taken from each comminuted laboratory sample using water-slurry comminution methods. Finally, two aliquots from the test portion/solvent blend were analysed for both aflatoxin B1 and total aflatoxins. The total variance associated with testing dried figs for aflatoxins was measured and partitioned into sampling, sample preparation and analytical variance components (total variance is equal to the sum of the sampling variance, sample preparation variance, and analytical variance). Each variance component increased as aflatoxin concentration increased. Using regression analysis, mathematical expressions were developed to model the relationship between aflatoxin concentration and the total, sampling, sample preparation and analytical variances when testing dried figs for aflatoxins. The regression equations were modified to estimate the variances for any sample size, test portion size, and number of analyses for a specific lot aflatoxin concentration. When using the above aflatoxin test procedure to sample a fig lot at 10 μg/kg total aflatoxins, the sampling, sample preparation, analytical, and total variances were 47.20, 0.29, 0.13, and 47.62, respectively. The sampling, sample preparation, and analytical steps accounted for 99.1, 0.6, and 0.3% of the total variance, respectively. For the aflatoxin test procedure used in this study, the sampling step is the largest source of variability.

Revisiting the sampling, sample preparation, and analytical variability associated with testing wheat for deoxynivalenol

2019 ◽  
Vol 12 (4) ◽  
pp. 319-332
Author(s):  
S.A. Tittlemier ◽  
J. Chan ◽  
D. Gaba ◽  
K. Pleskach ◽  
J. Osborne ◽  
...  
Keyword(s):  
Experimental Design ◽  
Sample Preparation ◽  
Normal Distribution ◽  
Total Variance ◽  
Design Parameters ◽  
Test Results ◽  
Operating Characteristics ◽  
Test Portion ◽  
Decision Limit ◽  
Sample Test

Fifteen lots of wheat were sampled to characterise the total variance and distribution among sample test results associated with measuring deoxynivalenol (DON) in bulk wheat lots. An unbalanced nested experimental design based on past research was used to determine contributions to the total variance from sampling, sample preparation, and analysis. The wheat lots used in the study contained average DON concentrations that ranged from 0.17 to 24.5 mg/kg. Sampling was determined to be the largest contributor to the total variance of measuring DON at low mg/kg concentrations, which are relevant to existing maximum levels. With the experimental design parameters of 1 kg laboratory samples, sub-division of whole and ground grain using rotary sample division, sample comminution using a commercial-grade coffee grinder, extraction of 100 g test portions, and making one measurement of DON in the test portion by gas chromatography-mass spectrometry, the total variance of DON measurement at 2 mg/kg was 0.046 mg2/kg2 (coefficient of variation=10.7%). At this concentration, sampling contributed 67% to the total variance, followed by sample preparation (18%) and analysis (15%). The DON distribution among sample test results was accurately described by the normal distribution. The mathematical model of variance was used with the normal distribution of DON measurement results to construct operating characteristics curves to model the likelihood of mischaracterising a wheat lot as (non) compliant with a certain decision limit. With realistic laboratory sample and test portion sizes, as well as a practicable decision limit of 1.5 mg/kg, the estimated probability of mischaracterising a wheat lot containing 2 mg/kg DON as less than this concentration was reduced to 1%.

scholarly journals Testing Green Coffee for Ochratoxin A, Part III: Performance of Ochratoxin A Sampling Plan

2006 ◽  
Vol 89 (4) ◽  
pp. 1021-1026
Author(s):  
Eugenia A Vargas ◽  
Thomas B Whitaker ◽  
Eliene A Santos ◽  
Andrew B Slate ◽  
Francisco B Lima ◽  
...  
Keyword(s):  
Sample Preparation ◽  
Sample Size ◽  
Ochratoxin A ◽  
Test Procedure ◽  
Sampling Plan ◽  
Green Coffee ◽  
Sampling Step ◽  
Sampling Plans

Abstract Green coffee shipments are often inspected for ochratoxin A (OTA) and classified into good or bad categories depending on whether the OTA estimates are above or below a defined regulatory limit. Because of the uncertainty associated with the sampling, sample preparation, and analytical steps of an OTA test procedure, some shipments of green coffee will be misclassified. The misclassification of lots leads to some good lots being rejected (sellers' risk) and some bad lots being accepted (buyers' risk) by an OTA sampling plan. Reducing the uncertainty of an OTA test procedure and using an accept/reject limit less than the regulatory limit can reduce the magnitude of one or both risks. The uncertainty of the OTA test procedure is most effectively reduced by increasing sample size (or increasing the number of samples analyzed), because the sampling step is the largest source of uncertainty in the OTA test procedure. The effects of increasing sample size and changing the sample accept/reject limit relative to the regulatory limit on the performance of OTA sampling plans for green coffee were investigated. For a given accept/reject limit of 5 μg/kg, increasing sample size increased the percentage of lots accepted at concentrations below the regulatory limit and increased the percentage of lots rejected at concentrations above the regulatory limit. As a result, increasing sample size reduced both the number of good lots rejected (sellers' risk) and the number of bad lots accepted (buyers' risk). For a given sample size (1 kg), decreasing the sample accept/reject limit from 5 to 2 μg/kg relative to a fixed regulatory limit of 5 μg/kg decreased the percentage of lots accepted and increased the percentage of lots rejected at all OTA concentrations. As a result, decreasing the accept/reject limit below the regulatory limit increased the number of good lots rejected (sellers' risk), but decreased the number of bad lots accepted (buyers' risk).

Considerations in the preparation of laboratory samples for the analysis of ochratoxin A in wheat

2012 ◽  
Vol 5 (2) ◽  
pp. 107-116 ◽  
Author(s):  
S.A. Tittlemier ◽  
M. Roscoe ◽  
C. Kobialka ◽  
R. Blagden
Keyword(s):  
Ochratoxin A ◽  
Whole Grain ◽  
Laboratory Sample ◽  
Test Portion ◽  
Homogeneous Sample ◽  
Ambient Temperatures ◽  
Accuracy And Precision ◽  
Relative Standard ◽  
The Mean ◽  
Ground Wheat

A process used to prepare the test portion of ground wheat from the whole grain laboratory sample for ochratoxin A (OTA) analysis using dry comminution with homogenisation and sub-sampling via a rotary sample divider was developed and evaluated. With respect to OTA content, the developed process produced a homogeneous sample of ground wheat from 10 kg of whole grain. Relative standard deviations of the mean OTA concentration for five naturally contaminated wheat samples processed using the developed method ranged from 9% to 19% over a relevant concentration range of 1.7 to 7.6 mg/kg. Additional studies demonstrated that OTA was stable in ground wheat with moisture content between 12 to 13% for at least a year when stored at ambient temperatures. Further examination of the developed comminution and dividing procedure demonstrated that higher concentrations were measured in smaller sized particles, indicating that the accuracy and precision of OTA analyses could be affected by the particle size of ground wheat.

scholarly journals Combined Phenyl Silane and Immunoaffinity Column Cleanup with Liquid Chromatography for Determination of Ochratoxin A in Roasted Coffee: Collaborative Study

2001 ◽  
Vol 84 (2) ◽  
pp. 444-450 ◽  
Author(s):  
A Catherine Entwisle ◽  
Alison C Williams ◽  
Peter J Mann ◽  
Joanne Russell ◽  
Philip T Slack ◽  
...  
Keyword(s):  
Liquid Chromatography ◽  
Standard Deviation ◽  
Ochratoxin A ◽  
Relative Standard Deviation ◽  
Collaborative Study ◽  
Immunoaffinity Column ◽  
Roasted Coffee ◽  
Test Portion ◽  
Low Level ◽  
Relative Standard

Abstract A collaborative study was conducted to evaluate a liquid chromatography (LC) method for ochratoxin A using sequential phenyl silane and immunoaffinity column cleanup. The method was tested at 3 different levels of ochratoxin A in roasted coffee, which spanned the range of possible future European regulatory limits. The test portion was extracted with methanol and sodium bicarbonate by shaking for 30 min. The extract was filtered, centrifuged, and then cleaned up on a phenyl silane column before being eluted from the washed column with methanol–water. The eluate was diluted with phosphate-buffered saline (PBS) and applied to an ochratoxin A immunoaffinity column, which was washed with water. The ochratoxin A was eluted with methanol, the solvent was evaporated, and the residue was redissolved in injection solvent. After injection of this solution onto a reversed-phase LC apparatus, ochratoxin A was measured by fluorescence detection. Eight laboratory samples of low-level naturally contaminated roasted coffee and 2 laboratory samples of blank coffee (< 0.2 ng/g ochratoxin A at the signal-to-noise ratio of 3:1), along with ampules of ochratoxin A calibrant and spiking solutions, were sent to 15 laboratories in 13 different European countries. Test portions of the laboratory samples were spiked at levels of 4 ng/g ochratoxin A, and recoveries ranged from 65 to 97%. Based on results for spiked blank material (blind duplicates) and naturally contaminated material (blind duplicates at 3 levels), the relative standard deviation for repeatability (RSDr) ranged from 2 to 22% and the relative standard deviation for reproducibility (RSDR) ranged from 14 to 26%. The method showed acceptable within- and between-laboratory precision, as evidenced by HORRAT values, at the low level of determination for ochratoxin A in roasted coffee.

An alternative to slurry mixing to minimise sample preparation variance for determination of ochratoxin A in wheat

2010 ◽  
Vol 3 (2) ◽  
pp. 147-156 ◽  
Author(s):  
T. Nowicki ◽  
M. Roscoe
Keyword(s):  
Sample Preparation ◽  
Ochratoxin A ◽  
Mixing Time ◽  
Test Sample ◽  
Laboratory Sample ◽  
Analytical Process ◽  
Accuracy And Precision ◽  
Primary Sample ◽  
Surveillance Programs ◽  
Ground Wheat

Many countries have established maximum limits for ochratoxin A (OTA) in cereal grains and implemented surveillance programs for OTA in wheat shipments. For shipment to some countries, certification for OTA content is mandatory. These control activities require the capability to measure OTA in bulk grain shipments with accuracy and precision. It is known that the nugget effect caused by the heterogeneous nature of mycotoxin contamination in agricultural commodities creates major challenges for generating representative test results due to the potential for high variances in the sampling / sample preparation phases of the analytical process. The water-slurry mixing approach to sample preparation has greatly minimises variances associated with this phase of the analytical process, but this is not a practical technique for all laboratories. The potential magnitude of variances for subsampling raw and ground grain for the dry-milling approach to sample preparation and the means for reducing variances to acceptable levels is not fully understood. We investigated the repeatability of OTA measurements in 2 kg laboratory samples subsampled from 20 kg samples of raw wheat and in 100 g test portions subsampled from 2 kg of ground wheat. In addition, the effect of mixing time on the repeatability of OTA results was investigated prior to subsampling to obtain test portions for analysis. Results show that for subsampling of a primary sample of raw wheat using a conventional sample divider the variability of OTA results decreases with increasing weight of the laboratory sample relative to the weight of the primary sample. In order to improve repeatability, the proportion of primary sample separated out to produce a laboratory sample should be as large as operationally feasible and ideally about 50% of the weight of the primary sample. Four factors are identified for separating out a test sample from a raw wheat laboratory sample.

scholarly journals Maize meal slurry mixing: an economical recipe for precise aflatoxin quantitation

2019 ◽  
Vol 12 (3) ◽  
pp. 203-212 ◽  
Author(s):  
J. Kumphanda ◽  
L. Matumba ◽  
T.B. Whitaker ◽  
W. Kasapila ◽  
J. Sandahl
Keyword(s):  
Sample Preparation ◽  
Analytical Methods ◽  
Laboratory Sample ◽  
Test Portion ◽  
Sampling Plans ◽  
Dry Grind ◽  
Water Matrix ◽  
Analytical Variance ◽  
Aflatoxin Concentration ◽  
Maize Meal

The laboratory sample preparation for mycotoxin determination in cereals, often overlooked among sampling plans and analytical methods, was further studied. The precision of aflatoxin analysis in comminuted maize samples using 25 g slurry (prepared from 250 g test portion of comminuted maize, water/matrix (1+1, v/w)) and 12.5 g dry grind test portion were compared against the conventional 50 g dry grind test portion through replicated (10) Aflatest® immunoaffinity fluorometric tests of naturally contaminated samples with aflatoxin concentration ranging from 4.9 to 81.7 μg/kg. The overall mean aflatoxin concentration obtained from the 10 different samples tested using 12.5 g and 50.0 g dry grind procedures was 12% significantly (P<0.05) lower (poorer) compared to 25 g slurry. The sample preparation plus analytical variance associated with testing 25.0 g slurry, 50.0 g dry grind and 12.5 g dry grind test portions were in the ratio of 1:5:15, respectively.

scholarly journals Evaluating the Performance of Sampling Plans to Detect Fumonisin B1 in Maize Lots Marketed in Nigeria

2007 ◽  
Vol 90 (4) ◽  
pp. 1050-1059 ◽  
Author(s):  
Thomas B Whitaker ◽  
M Bruno Doko ◽  
Britt M Maestroni ◽  
Andrew B Slate ◽  
Bosede F Ogunbanwo
Keyword(s):  
Negative Binomial ◽  
Test Procedure ◽  
Fumonisin B1 ◽  
Sampling Plan ◽  
Regression Equations ◽  
Test Results ◽  
Energy Agency ◽  
Sampling Plans ◽  
Sample Test ◽  
Total Variability

Abstract Fumonisins are toxic and carcinogenic compounds produced by fungi that can be readily found in maize. The establishment of maximum limits for fumonisins requires the development of scientifically based sampling plans to detect fumonisin in maize. As part of an International Atomic Energy Agency effort to assist developing countries to control mycotoxin contamination, a study was conducted to design sampling plans to detect fumonisin in maize produced and marketed in Nigeria. Eighty-six maize lots were sampled according to an experimental protocol in which an average of 17 test samples, 100 g each, were taken from each lot and analyzed for fumonisin B1 by using liquid chromatography. The total variability associated with the fumonisin test procedure was measured for each lot. Regression equations were developed to predict the total variance as a function of fumonisin concentration. The observed fumonisin distribution among the replicated-sample test results was compared with several theoretical distributions, and the negative binomial distribution was selected to model the fumonisin distribution among test results. A computer model was developed by using the variance and distribution information to predict the performance of sampling plan designs to detect fumonisin in maize shipments. The performance of several sampling plan designs was evaluated to demonstrate how to manipulate sample size and accept/reject limits to reduce misclassification of maize lots.

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