Predicting the Distribution of Aflatoxin Test Results from Farmers’ Stock Peanuts

1994 ◽  
Vol 77 (3) ◽  
pp. 659-666 ◽  
Author(s):  
Thomas B Whitaker ◽  
Francis G Giesbrecht ◽  
Jeremy Wu ◽  
Winston M Hagler ◽  
Floyd E Dowell
Keyword(s):  
Negative Binomial ◽  
Accurate Estimate ◽  
Test Results ◽  
Sample Sizes ◽  
Significance Level ◽  
Sample Test ◽  
Unknown Distribution Function ◽  
Acceptance Levels ◽  
Ks Test ◽  
Binomial Function

Abstract Suitability of the negative binomial function for use in estimating the distribution of sample aflatoxin test results associated with testing farmers1 stock peanuts for aflatoxin was studied. A 900 kg portion of peanut pods was removed from each of 40 contaminated farmers1 stock lots. The lots averaged about 4100 kg. Each 900 kg portion was divided into fifty 2.26 kg samples, fifty 4.21 kg samples, and fifty 6.91 kg samples. The aflatoxin in each sample was quantified by liquid chromatography. An observed distribution of sample aflatoxin test results consisted of 50 aflatoxin test results for each lot and each sample size. The mean aflatoxin concentration, m; the variance, s2xamong the 50 sample aflatoxin test results; and the shape parameter, k, for the negative binomial function were determined for each of the 120 observed distributions (40 lots times 3 sample sizes). Regression analysis indicated the functional relationship between k and m to be k = 0.000006425m0.8047. The 120 observed distributions of sample aflatoxin test results were compared to the negative binomial function by using the Kolmogorov–Smirnov (KS) test. The null hypothesis that the true unknown distribution function was negative binomial was not rejected at the 5% significance level for 114 of the 120 distributions. The negative binomial function failed the KS test at a sample concentration of 0 ng/g in all 6 of the distributions where the negative binomial function was rejected. The negative binomial function always predicted a smaller percentage of samples testing 0 ng/g than was actually observed. However, the negative binomial function did fit the observed distribution for sample test results at a concentration greater than 0 in 4 of the 6 cases. As a result, the negative binomial function provides an accurate estimate of the acceptance probabilities associated with accepting contaminated lots of farmers' stock peanuts for various sample sizes and various sample acceptance levels greater than 0 ng/g.

scholarly journals Sampling Hazelnuts for Aflatoxin: Effect of Sample Size and Accept/Reject Limit on Reducing the Risk of Misclassifying Lots

2007 ◽  
Vol 90 (4) ◽  
pp. 1028-1035 ◽  
Author(s):  
Guner Ozay ◽  
Ferda Seyhan ◽  
Aysun Yilmaz ◽  
Thomas B Whitaker ◽  
Andrew B Slate ◽  
...  
Keyword(s):  
Sample Size ◽  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Negative Binomial ◽  
Food Additives ◽  
Sampling Plan ◽  
Test Results ◽  
Sampling Plans ◽  
Wide Range ◽  
Sample Test

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.

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.

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.

scholarly journals The TED Talks Application as a Learning Tool in Teaching Spaking

2021 ◽  
Vol 6 (1) ◽  
pp. 45-52
Author(s):  
Mutiara Indah Sari ◽  
M. Sofian Hadi ◽  
Mutiarani Mutiarani
Keyword(s):  
Test Score ◽  
Alternative Hypothesis ◽  
T Test ◽  
Test Results ◽  
Significance Level ◽  
Design Culture ◽  
Post Test ◽  
Sample Test ◽  
Quasi Experimental ◽  
Ted Talks

The aim of this study is to improve the learning of English with a speech variable using the TED Talks Application. The quantitative approach is the technique used in this research. The design used in this quantitative study is a quasi-experimental design, which utilizes a pre-test and post-test design culture. The population in this study was 20 grade XII students of SMK Muhammadiyah Parung, Bogor in the academic year 2020/2021. Pre-test and post-test data were analyzed using SPSS 25 version. The results of the study showed that the students pre-test score was 64.70 and after treatment, the students post-test score was 87.60. The results of this study also clarified that the t-test in the paired sample test in which tobtained was 28.56 and the crucial tvalue at significance level (p)=0.05 was 2.093, which means that t-test in which the null hypothesis (Ho) was rejected and the alternative hypothesis (H1) accepted. The writer finding might summarize that the student’s post-test results are higher than the student’s pre-test results. In other words, the use of TED Talks is useful in the 12th grade of vocational high school for students who speak English.

scholarly journals Distribution among Sample Test Results when Testing Shelled Corn Lots for Fumonisin

2001 ◽  
Vol 84 (3) ◽  
pp. 770-776 ◽  
Author(s):  
Thomas B Whitaker ◽  
Winston M Hagler ◽  
Anders S Johansson ◽  
Francis G Giesbrecht ◽  
Mary W Trucksess
Keyword(s):  
Gamma Distribution ◽  
Gamma Function ◽  
Characteristic Curve ◽  
Test Procedure ◽  
Test Results ◽  
Significance Level ◽  
Gamma Distributions ◽  
Sample Test ◽  
The Mean ◽  
Power Divergence

Abstract The statistical distribution known as the compound gamma function was studied for suitability in describing the distribution of sample test results associated with testing lots of shelled corn for fumonisin. Thirty-two 1.1 kg test samples were taken from each of 16 contaminated lots of shelled corn. An observed distribution consisted of 32 sample fumonisin test results for each lot. The mean fumonisin concentration, c, and the variance, s2, among the 32 sample fumonisin test results along with the parameters for the compound gamma function were determined for each of the 16 observed distributions. The 16 observed distributions of sample fumonisin test results were compared with the compound gamma function using the Power Divergence test. The null hypothesis that the observed distribution could have resulted from sampling a family of compound gamma distributions was not rejected at the 5% significance level for 15 of the 16 lots studied. Parameters of the compound gamma distribution were calculated from the 32-fumonisin sample test results using the method of moments. Using regression analysis, equations were developed that related the parameters of the compound gamma distribution to fumonisin concentration and the variance associated with a fumonisin test procedure. An operating characteristic curve was developed for a fumonisin sampling plan to demonstrate the use of the compound gamma function.

Sampling dried figs for aflatoxin - Part II: effect of sampling plan design on reducing the risk of misclassifying lots

2017 ◽  
Vol 10 (2) ◽  
pp. 99-109 ◽  
Author(s):  
H. Ozer ◽  
H.I. Oktay Basegmez ◽  
T.B. Whitaker ◽  
A.B. Slate ◽  
F.G. Giesbrecht
Keyword(s):  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Negative Binomial ◽  
Sampling Plan ◽  
Export Market ◽  
Test Results ◽  
Sampling Plans ◽  
Binomial Distributions ◽  
Sample Test ◽  
Codex Standard

Because aflatoxin limits vary widely among regulating countries, the Codex Committee on Contaminants in Foods (CCCF) began work in 2006 to harmonise maximum levels (MLs) and sampling plans for aflatoxin in dried figs. Studies were developed to measure the variability and distribution among replicated sample aflatoxin test results taken from the same aflatoxin contaminated lot of dried figs so that a model could be developed to evaluate the risk of misclassifying lots of dried figs by aflatoxin sampling plan designs. The model was then be used by the CCCF electronic working group (eWG) to recommend MLs and aflatoxin sampling plan designs to the full CCCF membership for lots traded in the export market. Sixteen 10 kg samples were taken from each of 20 dried fig lots with varying levels of contamination. The observed aflatoxin distribution among the 16-aflatoxin sample test results was compared to the normal, 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 aflatoxin distributions among sample test results taken from the same contaminated lot. Using the negative binomial distribution, a computer model was developed to show the effect of the number and size of samples and the accept/reject limits on the chances of rejecting good lots (seller's risk) and accepting bad lots (buyer's risk). The information was shared with the CCCF eWG and in March 2012, the 6th session of CCCF adopted at step 5/8 an aflatoxin sampling plan where three 10 kg samples must all test less than an ML of 10 µg/kg total aflatoxins to accept a dried fig lot. The 35th Session of the Codex Alimentarius Commission met in July 2012 and adopted the CCCF recommendations for the ML and the sampling plan as an official Codex standard.

Effects of Sample Size and Sample Acceptance Level on the Number of Aflatoxin-Contaminated Farmers’ Stock Lots Accepted and Rejected at the Buying Point

1994 ◽  
Vol 77 (6) ◽  
pp. 1672-1680 ◽  
Author(s):  
Thomas B Whitaker ◽  
Jeremy Wu ◽  
Floyd E Dowell ◽  
Winston M Hagler ◽  
Francis G Giesbrecht
Keyword(s):  
Sample Size ◽  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Negative Binomial ◽  
Single Sample ◽  
Sample Sizes ◽  
Acceptance Level ◽  
Aflatoxin Concentration ◽  
Acceptance Levels

Abstract Sixteen different aflatoxin sampling plan designs were evaluated using the negative-binomial distribution. Evaluations were used to predict the effects of 4 different sample sizes and 4 different sample acceptance levels on the classification of farmers’ stock lots according to the lot aflatoxin concentration. The 4 sample sizes evaluated were 2.27 kg (5 lb), 4.54 kg (10 lb), 9.08 kg (20 lb), and 18.16 kg (40 lb). The 4 sample acceptance levels evaluated were 5,50,100, and 180 ng/g. A decrease in the sample acceptance level from 180 to 5 ng/g decreased the number of lots accepted at all lot concentrations, increased the number of lots rejected at all lot concentrations, and decreased the average aflatoxin concentrations among all lots accepted. At the highest sample acceptance level, 180 ng/g, increase in sample size from 2.27 to 18.16 kg decreased the percent of lots accepted at concentrations above the sample acceptance level and increased the percent of lots accepted at concentrations below the sample acceptance level. At the lowest sample acceptance level investigated, 5 ng/g, an increase in sample size from 2.27 to 18.16 kg decreased the percent of lots accepted at all concentrations. The effect of using sampling designs with 2 sample acceptance levels to classify lots into 3 categories was investigated. The advantages of using dual sample acceptance levels over a single sample acceptance level was demonstrated for 2.27 and 9.08 kg samples.

Problematic Internet Use digunakan Ketika Kesepian pada Remaja

2020 ◽  
Vol 14 (1) ◽  
pp. 45-60
Author(s):  
Yashinta Yashinta ◽  
Dwi Hurriyati
Keyword(s):  
Internet Use ◽  
Hypothesis Test ◽  
Problematic Internet Use ◽  
Coefficient Of Determination ◽  
Test Results ◽  
Research Subjects ◽  
Significance Level ◽  
Relationship Of ◽  
The Relationship ◽  
Effective Contribution

This study aims to determine the relationship of loneliness with problematic internet use on boarding students on Silaberanti street in Siantan jaya Opposite Ulu 1 Palembang city. Research subjects numbered 220 people using random sampling methods. Data was collected using a 60 item problematic internet use scale and a 60 item loneliness. Realibility is generated on scale of problematic internet use of 0,955 and loneliness of 0,946.Hypothesis testing uses product moment correlation analysis techniques. Hypothesis test results showed a positive relationshif between loneliness with problematic internet use on boarding students on Silaberanti street in Siantan jaya Opposite Ulu 1 Palembang city r= 0,684 with a significance level of 0,000 (p<0,01). Loneliness in this study made an effective contribution of 46,8% to problematic internet use which can be seen from the coefficient of determination (r²) that is equel to 0,468.

Kemampuan Komunikasi Matematika: Studi Komparasi Pembelajaran Number Head Together (NHT) dan Media Power Point (PPT)

2020 ◽  
Vol 3 (1) ◽  
pp. 39-50
Author(s):  
Bernadeta Ritawati ◽  
Sri Wahyuni
Keyword(s):  
Communication Skills ◽  
Hypothesis Test ◽  
Test Results ◽  
Mathematical Communication ◽  
Cluster Technique ◽  
Significance Level ◽  
Quasi Experimental ◽  
Power Point ◽  
Media Power ◽  
Better Than

This research is a quasi-experimental study that aims to determine the comparison of students' mathematical communication abilities with the cooperative learning model of the NHT and PPT media in class VII SMP Negeri 02 Ngabang. The population in this study were all students of class VII SMP 02 Ngabang consisting of 3 classes. The sample in this study was taken by using the Random Sampling Cluster technique. Class VII A as class I experimental class with 24 students and class VII B as a experimental class II with 24 students. The instruments used were pretest and posttest in the form of description. Data analysis uses the t test with a significance level of 5%. The results showed the average posttest for the NHT class was 72.5 and the average posttest for the PP class was 66.666. From the posttest hypothesis test results obtained t hitung> t tabel (1.9522> 1,667). Because t_hitung> t_tabel, H_0 is rejected and H_a is accepted. This means that students' mathematical communication skills taught with the NHT are better than using Power point media.

Bike Count Forecast Model with Multimodal Network Connectivity Measures

2021 ◽  
pp. 036119812110218
Author(s):  
Bingqing Liu ◽  
Divya Bade ◽  
Joseph Y. J. Chow
Keyword(s):  
New York ◽  
Negative Binomial ◽  
Network Connectivity ◽  
Negative Binomial Regression ◽  
Forecast Model ◽  
Negative Binomial Regression Model ◽  
Significance Level ◽  
Commute Time ◽  
Improve Model ◽  
Subway Stations

With the rise of cycling as a mode choice for commuting and short-distance delivery, as well as policy objectives encouraging this trend, bike count models are increasingly critical to transportation planning and investment. Studies have found that network connectivity plays a role in such models, but there remains a lack of measure for the connectivity of a link in a multimodal trip context. This study proposes a connectivity measure that captures the importance of a link in connecting the origins of cyclists and nearby subway stations, and incorporates it in a negative binomial regression model to forecast bike counts at links. Representative bike trips are generated with regard to bike-friendliness using the New York City transit trip planner and used to determine the deviation from the shortest path via the designated link. The measure is shown to improve model fitness with a significance level within 10%. Insights are also drawn for income levels, bike lanes, subway station availability, and average commute time of travelers.

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