Variability Associated with Sampling, Sample Preparation, and Chemical Testing for Aflatoxin in Farmers' Stock Peanuts

1994 ◽  
Vol 77 (1) ◽  
pp. 107-116 ◽  
Author(s):  
Thomas B Whitaker ◽  
Floyd E Dowell ◽  
Winston M Hagler ◽  
Francis G Giesbrecht ◽  
Jeremy Wu
Keyword(s):  
Sample Preparation ◽  
Variance Component ◽  
Analytical Techniques ◽  
State Inspection ◽  
Total Variance ◽  
Federal State ◽  
Inspection Method ◽  
Aflatoxin Concentration ◽  
Total Variability ◽  
Inspection Service

Abstract Forty farmers’ stock lots of runner peanuts suspected of containing aflatoxin were identified by the Federal State Inspection Service by using the visual Aspergillus flavus inspection method. A 900 kg portion was removed from each lot and divided into 50 samples each of 2.27 kg (5 lb), 4.54 kg (10 lb), and 6.81 kg (15 lb) weights. For each sample, foreign material was removed, pods were shelled, and all kernels were comminuted for 7 min in a vertical cutter mixer. A100 g subsample was removed from each comminuted sample for aflatoxin analysis by liquid chromatography (LC). The total variance associated with each sample size was estimated. The total variance was also partitioned into sampling, sample preparation, and analytical variance components. Each variance component was shown to be a function of aflatoxin concentration. By using regression techniques, the relationship between variance and aflatoxin concentration was developed for each variance component. The total, sampling, sample preparation, and analytical variances associated with testing a lot at 100 ppb with a 2.27 kg sample, 100 g subsample, and using LC analytical techniques are 25 378,23 533,1830, and 15, respectively. Sampling, sample preparation, and analysis account for 92.7, 7.2, and 0.1% of the total variability, respectively.

Variability Associated with Chemically Testing Screened Farmers Stock Peanuts For Aflatoxin1

1992 ◽  
Vol 19 (2) ◽  
pp. 88-91 ◽  
Author(s):  
T. B. Whitaker ◽  
J. W. Dorner ◽  
F. E. Dowell ◽  
F. G. Giesbrecht
Keyword(s):  
Variance Components ◽  
Functional Relationship ◽  
State Inspection ◽  
Federal State ◽  
Test Results ◽  
Aflatoxin Concentration ◽  
Total Variability ◽  
Regression Techniques ◽  
Inspection Service ◽  
Screening Device

Abstract Forty farmers stock lots of runner peanuts suspected of containing aflatoxin were identified by the Federal State Inspection Service using the visual Aspergillus flavus method. A 227-kg portion was removed from each of the 40 lots. Each 227-kg portion was screened over a belt screening device with 0.953-cm (24/64 inch) spacing to remove loose shelled kernels, foreign material, and small pods. Each screened portion was divided into ten 9.5-kg samples. Each sample was shelled, all kernels in the sample were comminuted in the Federal State subsampling mill, and the aflatoxin in duplicate 356-g subsamples per sample was extracted and quantified using HPLC methods. The total variability among the 10 aflatoxin test results was determined for each lot. The total variability was partitioned into sampling, subsampling, and analytical variability components for each lot. All variance components were shown to be functions of the aflatoxin concentration. Using regression techniques the functional relationship for each variance components and aflatoxin concentration was developed. The total variance associated with a 9.5-kg sample, 356-g subsample, and HPLC quantification when testing a screened farmers stock lot at 20 ppb is 295.2 and the CV is 89.5%.

Comparison of Visual, Enzyme-Linked Immunosorbent Assay Screening, and HPLC Methods in Detecting Aflatoxin in Farmers Stock Peanut Grade Samples

1988 ◽  
Vol 15 (2) ◽  
pp. 61-63 ◽  
Author(s):  
R. J. Cole ◽  
J. W. Dorner ◽  
J. W. Kirksey ◽  
F. E. Dowell
Keyword(s):  
Immunosorbent Assay ◽  
Screening Test ◽  
High Performance ◽  
State Inspection ◽  
Rapid Screening ◽  
Federal State ◽  
Enzyme Linked Immunosorbent Assay ◽  
Inspection Method ◽  
Rapid Screening Test ◽  
Inspection Service

Abstract Grade samples from 152 lots of farmers stock peanuts were analyzed for aflatoxin by both an Enzyme-Linked Immunosorbent Assay (ELISA) rapid screening test and high performance liquid chromatography (HPLC). Results from HPLC and ELISA were compared to the results of the visual inspection method used by the Federal State Inspection Service (FSIS). The results showed 41% of the grade samples with visible Aspergillus flavus (Segregation 3) contained less than 20 ppb aflatoxin when analyzed by both ELISA and HPLC methods; 18.7% of Segregation 1 peanuts actually contained aflatoxin with a range of 26-2542 ppb. The results of ELISA and HPLC agreed in 98.6% of the composite lot analyses with the detection of 20 ppb or greater. However, the ELISA rapid screening test failed to give positive tests 12 of 13 times when the aflatoxin content was between 20-43 ppb in the component samples.

scholarly journals Sampling, Sample Preparation, and Analytical Variability Associated with Testing Wheat for Deoxynivalenol

2000 ◽  
Vol 83 (5) ◽  
pp. 1285-1292 ◽  
Author(s):  
Thomas B Whitaker ◽  
Winston M Hagler ◽  
Francis G Giesbrecht ◽  
Anders S Johansson
Keyword(s):  
Sample Preparation ◽  
Sample Size ◽  
Variance Component ◽  
Small Sample Size ◽  
Test Procedure ◽  
Small Sample ◽  
Test Procedures ◽  
Analytical Variability ◽  
Total Variability ◽  
Regression Techniques

Abstract The variability associated with testing wheat for deoxynivalenol (DON) was measured using a 0.454 kg sample, Romer mill, 25 g comminuted subsample, and the Romer Fluoroquant analytical method. The total variability was partitioned into sampling, sample preparation, and analytical variability components. Each variance component was a function of the DON concentration and equations were developed to predict each variance component using regression techniques. The effect of sample size, subsample size, and number of aliquots on reducing the variability of the DON test procedure was also determined. For the test procedure, the coefficient of variation (CV) associated with testing wheat at 5 ppm was 13.4%. The CVs associated with sampling, sample preparation, and analysis were 6.3, 10.0, and 6.3%, respectively. For the sample variation, a 0.454 kg sample was used; for the sample preparation variation, a Romer mill and a 25 g subsample were used; for the analytical variation, the Romer Fluoroquant method was used. The CVs associated with testing wheat are relatively small compared to the CV associated with testing other commodities for other mycotoxins, such as aflatoxin in peanuts. Even when the small sample size of 0.454 kg was used, the sampling variation was not the largest source of error as found in other mycotoxin test procedures.

scholarly journals Sampling Hazelnuts for Aflatoxin: Uncertainty Associated with Sampling, Sample Preparation, and Analysis

2006 ◽  
Vol 89 (4) ◽  
pp. 1004-1011 ◽  
Author(s):  
Guner Ozay ◽  
Ferda Seyhan ◽  
Aysun Yilmaz ◽  
Thomas B Whitaker ◽  
Andrew B Slate ◽  
...  
Keyword(s):  
Sample Preparation ◽  
Test Procedure ◽  
Aflatoxin Contamination ◽  
Aflatoxin Level ◽  
Mathematical Expressions ◽  
Aflatoxin Concentration ◽  
Total Variability ◽  
Subsample Size ◽  
Liquid Chromatographic ◽  
The Relationship

Abstract The variability associated with the aflatoxin test procedure used to estimate aflatoxin levels in bulk shipments of hazelnuts was investigated. Sixteen 10 kg samples of shelled hazelnuts were taken from each of 20 lots that were suspected of aflatoxin contamination. The total variance associated with testing shelled hazelnuts was estimated and partitioned into sampling, sample preparation, and analytical variance components. Each variance component increased as aflatoxin concentration (either B1 or total) increased. With the use of 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. The sampling, sample preparation, and analytical variances associated with estimating aflatoxin in a hazelnut lot at a total aflatoxin level of 10 ng/g and using a 10 kg sample, a 50 g subsample, dry comminution with a Robot Coupe mill, and a highperformance liquid chromatographic analytical method are 174.40, 0.74, and 0.27, respectively. The sampling, sample preparation, and analytical steps of the aflatoxin test procedure accounted for 99.4, 0.4, and 0.2% of the total variability, respectively.

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.

Peanut Foliar Fungicides: Relationships Between Leafspot Control and Kernel Quality

1976 ◽  
Vol 3 (2) ◽  
pp. 70-72 ◽  
Author(s):  
J. M. Hammond ◽  
P. A. Backman ◽  
J. A. Lyle
Keyword(s):  
Leaf Spot ◽  
Untreated Control ◽  
State Inspection ◽  
Federal State ◽  
Peanut Kernel ◽  
Cercospora Arachidicola ◽  
Copper Hydroxide ◽  
Fungicide Treatment ◽  
Kernel Quality ◽  
Inspection Service

Abstract The effectiveness of foliar fungicides for control of peanut leafspot caused by Cercospora arachidicola Hori and Cercosporidium personatum (Berk. & Curt.) Deight, was evaluated from 1971–1974. Benomyl, chlorothalonil, triphenyl-tin-hydroxide and copper hydroxide were applied at recommended rates by conventional ground sprayer at 14-day intervals. Leaf-spot severity was rated by determining percent defoliation and infection. All fungicide-treated plots had less defoliation and infection than the untreated control plots. Kernel quality was determined using Federal-State Inspection Service procedures. Plots sprayed with chlorothalonil had better quality kernels than those from any other fungicide treatment. However, kernels harvested from the untreated control plots had significantly better quality than those from the chlorothalonil-treatment. Kernels harvested from the benomyl and copper hydroxide treatments were slightly inferior in quality than the chlorothalonil treatment. Kernels from the triphenyl-tin-hydroxide treated plots were significantly inferior in quality than those from plots treated with other fungicides. These data indicate that while kernel quality is not related to leafspot control, certain foliar fungicides adversely affect peanut kernel quality probably by altering the ecology of the geocarposphere.

scholarly journals Testing Shelled Corn for Aflatoxin, Part I: Estimation of Variance Components

2000 ◽  
Vol 83 (5) ◽  
pp. 1264-1269 ◽  
Author(s):  
Anders S Johansson ◽  
Thomas B Whitaker ◽  
Winston M Hagler ◽  
Francis G Giesbrecht ◽  
James H Young ◽  
...  
Keyword(s):  
Sample Preparation ◽  
Aflatoxin Contamination ◽  
Total Variance ◽  
Mathematical Expressions ◽  
Aflatoxin Concentration ◽  
Concentration Test ◽  
Liquid Chromatographic Analysis ◽  
Subsample Size ◽  
Liquid Chromatographic ◽  
Estimation Of Variance

Abstract The variability associated with testing lots of shelled corn for aflatoxin was investigated. Eighteen lots of shelled corn were tested for aflatoxin contamination. The total variance associated with testing shelled corn was estimated and partitioned into sampling, sample preparation, and analytical variances. All variances increased as aflatoxin concentration increased. With the use of 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. Test results on a lot with 20 parts per billion aflatoxin using a 1.13 kg sample, a Romer mill, 50 g subsamples, and liquid chromatographic analysis showed that the total, sampling, sample preparation, and analytical variances were 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 was 77.8, 20.5, and 1.7, respectively.

scholarly journals Sampling Almonds for Aflatoxin, Part I: Estimation of Uncertainty Associated with Sampling, Sample Preparation, and Analysis

2006 ◽  
Vol 89 (4) ◽  
pp. 1027-1034 ◽  
Author(s):  
Thomas B Whitaker ◽  
Andrew B Slate ◽  
Merle Jacobs ◽  
J Michael Hurley ◽  
Julie G Adams ◽  
...  
Keyword(s):  
Sample Preparation ◽  
High Performance ◽  
Test Procedure ◽  
Aflatoxin Contamination ◽  
Total Variance ◽  
Concentration Variance ◽  
Chromatography Analysis ◽  
Aflatoxin Concentration ◽  
Variance Estimates ◽  
Mathematical Relationships

Abstract Domestic and international regulatory limits have been established for aflatoxin in almonds and other tree nuts. It is difficult to obtain an accurate and precise estimate of the true aflatoxin concentration in a bulk lot because of the uncertainty associated with the sampling, sample preparation, and analytical steps of the aflatoxin test procedure. To evaluate the performance of aflatoxin sampling plans, the uncertainty associated with sampling lots of shelled almonds for aflatoxin was investigated. Twenty lots of shelled almonds were sampled for aflatoxin contamination. The total variance associated with measuring B1 and total aflatoxins in bulk almond lots was estimated and partitioned into sampling, sample preparation, and analytical variance components. All variances were found to increase with an increase in aflatoxin concentration (both B1 and total). By using regression analysis, mathematical expressions were developed to predict the relationship between each variance component (total, sampling, sample preparation, and analysis variances) and aflatoxin concentration. Variance estimates were the same for B1 and total aflatoxins. The mathematical relationships can be used to estimate each variance for a given sample size, subsample size, and number of analyses other than that measured in the study. When a lot with total aflatoxins at 15 ng/g was tested by using a 10 kg sample, a vertical cutter mixer type of mill, a 100 g subsample, and high-performance liquid chromatography analysis, the sampling, sample preparation, analytical, and total variances (coefficient of variation, CV) were 394.7 (CV, 132.4%), 14.7 (CV, 25.5%), 0.8 (CV, 6.1%), and 410.2 (CV, 135.0%), respectively. The percentages of the total variance associated with sampling, sample preparation, and analytical steps were 96.2, 3.6, and 0.2, respectively.

A Laboratory Colorimeter Method to Measure Pod Brightness in Virginia-Type Peanuts

1997 ◽  
Vol 24 (2) ◽  
pp. 81-84 ◽  
Author(s):  
T. G. Isleib ◽  
H. E. Pattee ◽  
P. W. Rice
Keyword(s):  
Optical Sensor ◽  
State Inspection ◽  
Federal State ◽  
Strongly Correlated ◽  
Visual Aesthetics ◽  
Sample Area ◽  
Optical Aperture ◽  
Color Measurements ◽  
Highly Correlated ◽  
Inspection Service

Abstract Pod brightness is an important characteristic that influences consumers to purchase in-shell peanuts. A method is needed to quantitate pod brightness. Studies were conducted to determine whether pod color measurements were related to visual aesthetics rated by a panel representing seven virginia peanut shelling companies and to determine the effect of the optical aperture of the colorimeter on the measurements obtained. Forty-eight virginia-type pod lots were separated into fancy and jumbo fractions using a standard Federal-State Inspection Service grading peanut sizer. Pod color was measured for three subsamples of each fraction using a Hunterlab D25-PC2 colorimeter equipped with the D25-2RAL Reduced Area Viewing for L optical sensor (51-mm diameter sample area). The 96 samples also were rated by 11 Virginia-Carolina area shellers for pod color and size. Sheller ratings for the two traits were highly correlated (r > 0.6, P ≤ 0.01). Hunter L and b scores were strongly correlated with sheller color ratings. The colorimeter is a useful tool for measuring pod brightness as an adjunct to breeding for improved pod brightness. Use of a 95 mm aperture resulted in greater average Hunter L, a, and b scores and significantly reduced the variance among subsamples. The larger aperture should be used when the quantity of pods available for measurement permits.

scholarly journals Variability Associated with Determining Grade Factors and Support Price of Farmers Stock Peanuts1

1991 ◽  
Vol 18 (2) ◽  
pp. 122-126
Author(s):  
Thomas B. Whitaker ◽  
James W. Dickens ◽  
Francis G. Giesbrecht
Keyword(s):  
State Inspection ◽  
Federal State ◽  
Foreign Material ◽  
True Value ◽  
Coefficients Of Variation ◽  
Support Price ◽  
Inspection Service

Abstract Replicated grade samples were taken from runner, Spanish, and virginia-type farmers stock peanut lots. Each sample was graded according to the procedures of the Federal State Inspection Service. The variability of % foreign material (%FM) and % loose shelled kernels (%LSK) associated with a 1800-g sample was measured. The variability of % sound mature kernels (%SMK), % sound splits (%SS), % other kernels (%OK), % damage (%DAM), and % extra large kernels (%ELK) associated with a 500-g sample was also measured. The variance was shown to be a function of the magnitude of the grade determination and was described by a relationship derived from binomial theory. From the measured grade factors, the support price per gross ton was calculated for each grade sample using the 1988 USDA loan schedule. The variance of the price per gross ton was also estimated and appeared to be independent of the price per gross ton. The coefficients of variation averaged across all lots tested were 21.1, 18.7, 2.6, 21.2, 14.0, 55.3, 7.8, and 2.4% for %FM, %LSK, %SMK, %SS, %OK, %DAM, %ELK, and price per gross ton, respectively. The computed price per gross ton of a farmers lot that has a true value of $600 was estimated to vary from $573 to $627 95% of the time when using the 500 and 1800 g grade sample to measure each grade factor.

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