Theoretical investigations into the accuracy of sampling shelled peanuts for aflatoxin

Within a population of shelled peanuts, aflatoxin may be concentrated in less than 0.5% of the peanuts. Those peanuts containing aflatoxin might have concentrations up to 1,000,000 μg of aflatoxin per kilogram of peanuts. Because of the distribution pattern, sample means vary widely, and the true average level of aflatoxin in the population is difficult to estimate. The objective of this study was to determine the effect of sample size, N, on sampling accuracy. The negative binomial distribution of aflatoxin since it allowed for a high probability of zero counts along with small probabilities of large counts. Using both the Monte Carlo technique and a direct computation method, the effect of sample size on sampling accuracy was quantitatively described. Journal Paper No. 2775, North Carolina State University Agricultural Experiment Station, Raleigh, N.C.     

Comparison of the observed distribution of aflatoxin in shelled peanuts to the negative binomial distribution

Suitability of the negative binomial distribution for use in estimating the probabilities associated with sampling lots of shelled peanuts for aflatoxin analysis has been studied. Large samples, called “minilots,” were drawn from 29 lots of shelled peanuts contaminated with aflatoxin. These minilots were subdivided into ca. 12 lb samples which were analyzed for aflatoxin. The mean and variance of these aflatoxin determinations for each minilot were determined. The shape parameterk and the mean aflatoxin concentrationm were estimated for each minilot. A regression analysis indicated the functional relationship betweenk andm to be:k=(2.0866+2.3898m) × 10⁻⁶. The observed distribution of sample concentrations from each of the 29 minilots was compared to the negative binomial distribution by means of the Kolmogorov-Smirnov test. The null hypothesis that each of the true unknown distribution functions was negative binomial was not rejected at the 5% significance level for all 29 comparisons. Journal Series Paper of the North Carolina State University Agricultural Experiment Station, Raleigh, N.C.     

Sampling diced almonds for aflatoxin

To ensure that diced almonds meet the current FDA guideline limit for total aflatoxin, it is necessary to have a sampling plant that will allow representative sampling with defined precision-i.e., with confidence limits on the average aflatoxin found. A sequential sampling plan using 4.54-kg samples of diced almonds or 150-g samples of meal by-product (fines screened from diced nuts during production) was constructed with data from a study of aflatoxin distribution among samples of 2 selected lots of almonds. These 2 lots of whole nuts, estimated to have 400 and 25 ppb aflatoxin, were diced and boxed with normal processing equipment and procedures to approximate the distribution of aflatoxin in the product during commercial production. With a square root trans-formation of the data from 4.54-kg samples of diced nuts, the aflatoxin in samples of both lots approximated a normal distribu-tion and the within-lot variances were not significantly different, which allowed the statistical plan described. A supplemental study was made of aflatoxin distribution in the meal by-product. The lack of a significant difference between the results for diced nuts and those for the corresponding meal suggests that diced almonds can be monitored for aflatoxin indirectly by sampling the meal, which will allow the use of fewer analyses of 150-g samples of less expen-sive product to reach a decision.     

Aflatoxin control program for Peanuts

Under provisions of a USDA Marketing Agreement, an aflatoxin control program for peanuts produced in the United States is administered by the Peanut Administrative Committee composed of peanut growers and shellers. Regulations of this committee contain provisions about the quality of peanuts acquired from farmers, storage of unshelled peanuts, aflatoxin testing, quality and disposition of processed lots, and indemnification of handlers for losses caused by lots which test over 25 parts-perbillion aflatoxin. Effects of the control program on aflatoxin concentrations in peanut products are discussed. Paper number 4978 of the Journal Series of the North Carolina Agricultural Experiment Station, Raleigh, NC 27607.     

Aflatoxin content of peanut hulls

The degree of aflatoxin contamination in peanut hulls was determined by analyzing inoculated hand-shelled hulls and hulls from peanuts known to contain aflatoxin. Hulls adjusted to 20% moisture, inoculated withAspergillus flavus, and incubated 7 days at 25 C supported growth ofA. flavus but not aflatoxin production. Peanuts from 20 selected Segregation III (visibleA. flavus) lots contained 13–353 ppb of aflatoxin. The machine-shelled hulls from these lots were analyzed and 3 lots contained no detectable aflatoxin, 13 lots contained 4–88 ppb and 4 lots contained >116 ppb. Aflatoxin concentrations of 53–87 ppb were detected in hulls when peanuts containing relatively high levels of aflatoxin (up to 26.8 ppm in damaged kernels) were carefully machine-shelled. Hulls from the same samples obtained by hand-shelling contained no detectable aflatoxin. When machine-shelled hulls were screened through successively smaller screens, the aflatoxin concentration of the smallest fraction (<3.18 mm) was always highest and indicated that small peanut kernels and peanut parts in the hulls actually contained the aflatoxin. Separating hulls over a 4.76 mm round-hole screen appeared to provide a means of removal of most aflatoxin in peanut hulls. No aflatoxin was found in hulls from uncontaminated peanuts.     

The relationship of peanut maturity to 2-methylpropanal in headspace volatiles

Headspace volatiles from peanuts of five consecutive maturity classes from three soil temperatures were determined to evaluate the relationship of peanut maturity and 2-methylpropanal. Cured, ground peanuts were held in closed vials for 30 min at 150 C before headspace sampling. Quantitation as percent of total volatiles and ppm in the peanuts revealed a decrease in 2-methylpropanal as peanuts matured regardless of seed size within maturity class. From peanut lots in which maturity-size relationships had been determined, headspace analysis of commercial sized lots indicated that the concentration of 2-methylpropanal was related to the maturity distribution (percent of each maturity class) within each sized lot. These data/techniques may have application in estimating lot-to-lot maturity-related peanut flavor/quality potential. Presented at the AOCS meeting in Honolulu, HI in May 1986.     

Sampling cottonseed lots for aflatoxin contamination

Large samples called “sublots” were drawn from 41 commercial lots of contaminated cottonseed. Each sublot was subdivided into twenty 5 lb samples which were analyzed for aflatoxin. The mean, median, variance, coefficient of variation, and the estimated range among the sample concentrations were computed. The results indicated that: (A) the variance among sample concentrations was large and was found to be a function of sample concentration and (B) the distribution of sample concentrations was skewed; the density of sample values was greater below the sublot concentration.     

Bright greenish-yellow fluorescence and aflatoxin in recently harvested yellow corn marketed in north carolina

Corn kernels that exhibited bright greenish-yellow fluorescence (BGYF) under long-wave ultraviolet light were hand-picked from samples of yellow corn produced in eastern North Carolina. The BGYF kernels from 113 4-kg samples contained an average of 8665 parts per billion (ppb) aflatoxin compared to an average of 46 ppb in the non-BGYF kernels. A regression analysis between the ppb aflatoxin concentration and the wt % BGYF kernels in 2,304 4.5-kg samples produced the regression equation: ppb in sample =197 (wt % BGYF). The correlation coefficient for the analysis was 0.90. Testing programs to reduce aflatoxin concentrations in purchased lots of corn based on either the BGYF method or the AOAC chemical assay method were compared. The average aflatoxin concentration in lots accepted by the AOAC method was 4 ppb, 10 ppb or 18 ppb when an acceptance level of < 20 ppb, < 50 ppb or < 100 ppb, respectively, was used. For the BGYF method, the average aflatoxin concentration in accepted lots was 10 ppb, 16 ppb or 22 ppb when an acceptance level of < 0.10% BGYF, < 0.25% BGYF or < 0.50% BGYF, respectively, was used. Approximately the same percentage of lots were accepted by both methods when either the low, medium or high acceptance level was used. Paper no. 6930 of the Journal Series of the North Carolina Agriculture Research Service (NCARS), Raleigh, NC.     

Designing of two mixed variable lot-size sampling plans using repetitive sampling and resampling based on the process capability index

In this article, we propose two types mixed variable lot-size sampling plans using the process capability index. The first one is the mixed variable lot-size repetitive sampling plan and the other is the mixed variable lot-size sampling plan for resubmitted lots. The design methodology of the proposed mixed sampling plans for symmetric and asymmetric fraction nonconforming cases is presented. Tables are constructed to determine the optimal parameters for practical applications. The industrial applications of the proposed mixed sampling plans are explained with illustrative examples. Comparison of the proposed sampling plans with other existing sampling plans is also made.     

A study of the variability associated with sampling peanuts for aflatoxin

One lot of peanuts known to contain aflatoxin was extensively sampled to study the sources of variability. A nested design was used where sections (50 bag units), subsamples and analytical variation were the variables studied. Sample size was the most critical factor in characterizing this lot. Variability from section to section was not significant indicating random distribution of the contaminant. Three 20 lb samples were taken on a number of lots from the 1968 crop, each of which was subdivided into two equivalent subsamples. The aflatoxin was determined on each of these subsamples. The results indicated that all the significant variation came from the subsamples, further enforcing the thesis that sample size is the critical factor in variability, and not lot inhomogeneity. Analysis of 550 lots from the 1967 crop where triples and analysis were available indicates that the magnitude of the variability is a little greater than was found on the experimental lot. Using the pooled standard deviation of the 1967 crop data, operating characteristic curves were plotted to demonstrate the improvement that can be expected by increasing the sample size.     

Variability associated with testing corn for aflatoxin

The sampling, subsampling (both coarse and fine ground meal), and analytical variances associated with testing shelled corn for aflatoxin were estimated by the use of 500 g samples, 50 g subsamples, and the CB method of analysis. The magnitudes of the variance components increased with an increase in the aflatoxin concentration. Functional relationships were developed to predict the variance for a given aflatoxin concentration and any size sample, subsample, and number of analyses. At 20 ppb total aflatoxin, the coefficient of variantion associated with a 4.54 kg sample, 1 kg subsample of coarsely ground meal (passes a #14 screen), a 50 g subsample of finely ground meal (passes a #20 screen) and one analysis were 21, 8, 11, and 26%, respectively.     

Measurements of High Oleic Purity in Peanut Lots Using Rapid,Single Kernel Near-Infrared Reflectance Spectroscopy

High oleic peanuts have improved shelf life vs. conventional peanuts. Purity (percentage of high oleic peanuts within a lot) is critical to ingredient performance and final lot value. Contamination can result from unintentional mix-ups at the breeder/seed level, improper production handling, or due to physiologically immature high oleic kernels. Therefore, industry groups have established unofficial sampling plans to monitor purity. Assuming equivalent measurement performance and simple random sampling, increasing the sample size decreases variance among replicated sample test results and increases the precision of estimated lot purity. A novel instrument (QSorter Explorer by QualySense AG) using near-infrared reflectance spectroscopy was evaluated for high speed (20 kernels per second) high oleic purity measurements. The study objectives were to assess instrument performance in: (1) measuring oleic acid (%) in runner peanuts and (2) estimating the true high oleic purity of artificially mixed peanut lots. Three grades (Jumbo, Medium, and No 1) of US Runner mini-lots each at seven different contamination levels (0, 5, 10, 20, 30, 50, and 100%) were prepared. Oleic acid (%) of individual kernels was measured by scanning replicated samples of 10, 50, 100, and 500 kernels using the QSorter Explorer. The variance associated with each sample size and lot contamination level on returned purity values is discussed in the context of binomial sampling. Overall, the demonstrated measurement performance and capacity of the QSorter Explorer to process much larger sample sizes suggest this instrument can better identify true high oleic peanut lot purity vs. other currently available technologies.     

Designing of multiple deferred state sampling plan for generalized inverted exponential distribution

In this article, we propose a sampling plan called a multiple deferred state sampling plan for sentencing a lot based on the information of current and successive lot samples. Based on this sampling plan, the median life of the product is assured based on a time-truncated life test where the lifetime of the product follows the generalized inverted exponential distribution. The quality of the product is measured by its median life. The optimal parameters of the proposed plan are obtained by using the approach of two points on the operating characteristic curve. Tables are also constructed for determining the optimal parameters with various shape parameters. The implementation of the proposed plan is illustrated with examples. The performance of the proposed plan is compared with the performance of existing sampling plans under the generalized inverted exponential distribution.     

Sample preparation for aflatoxin assay: The nature of the problem and approaches to a solution

Cases have been reported of individual peanuts, cottonseeds or Brazil nuts so highly contaminated with aflatoxin that, for a 50 g portion to be representative of the whole, the sample preparation procedures should grind each unit to a large number of particles and distribute them uniformly throughout the sample. Assuming uniform contamination of the individual kernel, each 50 g sample should contain 1/100 of that kernel. Even though these extreme cases may be encountered only infrequently, the more usual situation still presents difficulties because of great variability in individual kernel contamination. However, if the extreme can be handled, one can expect to handle the more usual situation. Equipment and procedures to achieve this distribution goal are described. The equipment studied includes a food chopper (Hobart), a nut mill (Thomas Mills), a disc mill (Bauer), a hammer mill (Fitzpatrick Model D comminuting machine), a hammer mill designed specifically for peanut samples (Dicken’s subsampling mill), a Polytron homogenizer (Bronwill Scientific), a vertical cutter-mixer (Hobart), and a sample splitter (Jones riffle). Commodities examined were shelled peanuts and in-shell Brazil nuts, walnuts, pecans and almonds. Comminution and mixing effectiveness were determined by particle size analysis, by distribution of kernels made radioactive by neutron activation and by aflatoxin analysis of naturally contaminated products. From the results we conclude that the ultimate in sample uniformity can be achieved with a disc mill, solvent addition to obtain a fluid system and mixing and grinding of the fluid with a dispersion mixer-grinder. A practical uniformity can be achieved in a vertical cutter-mixer with less expenditure of time and effort for the commodities studied. Presented in part at the AOCS-AACC Joint Meeting, Washington, D.C., April 1968.     

Effect of carbon dioxide,temperature, and relative humidity on production of aflatoxin in peanuts

Effects of carbon dioxide (CO₂) in combination with reduced relative humidities (RH) and temperatures on growth and aflatoxin production byAspergillus flavus in peanuts were investigated. Sound mature kernels of Early Runner peanuts were surface disinfested, inoculated withA. flavus, and incubated at various temperatures, RH, and CO₂ concentrations. Visible growth, aflatoxin production, and free fatty acid (FFA) formation byA. flavus was inhibited at approximately 86% RH by 20% CO₂ at 17C and by 60 and 40% CO₂ at 25C. Aflatoxin and FFA levels decreased as RH decreased from approximately 99% to 92% to 86%. At a constant temperature, an increase in CO₂ concentration caused a decrease in aflatoxin and percentage FFA; and, at a given CO₂ concentration, lowering the temperature resulted in a decrease in aflatoxin and percentage FFA.     

Unavoidable low level aflatoxin contamination of peanuts

A major portion of aflatoxin contamination of peanuts probably occurs when decayed or discolored peanuts are incompletely removed by sorting. Quality control measures have been instituted in the United States to insure that unavoidable aflatoxins in consumer peanuts and peanut products do not exceed 20 μg/kg. However, low level aflatoxin contamination, from trace amounts to about 50 μg/kg in sound mature unblemished peanuts, can occur before peanuts are dug. This low level contamination is not related to high levels of Aspergillus flavus infection or to current production practices. Low level aflatoxin contamination of peanuts may be endemic, and current sorting procedures may not be effective in removing unblemished contaminated peanuts.     

A method for determining kernel moisture content and aflatoxin concentrations in peanuts

A method was developed to determine kernel moisture content (KMC) and aflatoxin concentration in discrete peanut samples. Shelled peanuts were weighed to the nearest 0.01 g, and a water slurry was made by blending the peanuts for 2 min with 2.2 ml of water per g of peanuts. The slurry (10 g) was withdrawn and dried at 130°C for 3 h to determine KMC. Methanol was added to the remaining slurry and blended for an additional 1 min, and aflatoxins were quantitated with high-performance liquid chromatography. Comparison of the slurry method with an official peanut moisture method showed good agreement between the two over a range of moisture levels. Recovery of aflatoxin B₁ from spiked samples averaged 97% with an average coefficient of variation of 3.6%. The method enables determination of both KMC and aflatoxin content in peanut samples without degradation of aflatoxin that would occur when using the official moisture method.     

Absence of aflatoxin from refined vegetable oils

The present investigation is the first definitive study of the fate of the aflatoxins in vegetable oils undergoing processing. Crude oils, obtained by solvent extraction or by hydraulic pressing of ground moldy peanuts (not suitable for human consumption), contained only small fractions of the aflatoxin originally present in the peanuts; the meals retained the bulk of the aflatoxin. Conventional alkali refining and washing of the oils reduced aflatoxin content to a range of 10 to 14 ppb. The subsequent bleaching operation essentially eliminated aflatoxin from the oils; the concentrations were now less than 1 ppb. The above results were confirmed using corn oils obtained from corn germ deliberately contaminated in the laboratory withAspergillus flavus. The nonfluorescing forms of aflatoxins, capable of being produced during the alkali refining operations, are also absent from the refined vegetable oils; these aflatoxin derivatives are readily converted to their original form on acidification and thereby measurable by fluorescence, if present. Presented in part at the AOCS Meeting, Los Angeles, April 1966.     

An investigation of oven methods for determining the moisture content of shelled peanuts

Air-oven methods, using ground, sliced, and whele shelled peanuts, were investigated. The use of ground samples was found to be unsatisfactory. Slightly more accurate results were obtained with whole nuts than with sliced nuts. The method of heating 50-g. samples of whole shelled peanuts for 3 hrs. at 130°C. in a foreed-draft oven gave results agreeing closely with those obtained by the Karl Fischer method for samples of low moisture content.     

Determination of optimal quick switching system with varying sample size for assuring mean life under Weibull distribution

Conventional sampling plans are applied to dispose an individual lot or isolated lot that requires a large sample size. Consequently, the inspection time and cost needed to make a decision under conventional plans are high. In order to reduce the sample size and to inspect the series of lots with minimum cost and time, special purpose plans are utilized. In this article, we propose one of the special purpose plans, namely, a quick switching sampling system that is also known as a two-plan sampling system. Through this sampling system, the Weibull-distributed mean life of the product is ensured based on time-truncated life tests. The proposed system is designed with the intention of minimizing the average sample number using two points on the operating characteristic curve approach. The optimal parameters of the proposed system are determined for different combinations of producer’s risk and consumer’s risk. Implementation of the proposed system is also explained and the performance of the proposed system is compared with other existing plans. In addition, the effects of misspecification of shape parameters on optimal parameters and the probability of acceptance are discussed.