Aflatoxins In Samples Research Articles

Graphene coated optical microfiber for aflatoxin B1 detection

We proposed a graphene coated microfiber-based sensor for enhancing Aflatoxin B1 detection at room temperature. The heat-and-pull technique was used to fabricate the microfiber while the graphene layer was coated using a drop-casting technique. Aflatoxin samples are used as a sensor sensing area soaking solution, whereby the prepared graphene-coated microfiber was used as a sensor probe. The sensing is based on the modulation of transmission intensity and wavelength shift induced by the alteration of concentration of aflatoxin B1 from 0 ppm to 10 ppm. There is an increase in sensitivity from 0.129 dBm/ppm to 0.187 dBm/ppm and an increase in resolution from 0.17 ppm to 0.037 ppm by coating graphene on the microfiber sensor. For the graphene coated microfiber-based sensor, the wavelength shift from 1525.37 nm to 1525.19 nm was obtained when the aflatoxin B1 concentration was increased from 0 to 10 ppm. It reveals a sensitivity of 0.018 nm/ppm with a linearity of more than 90 %. This finding shows that the proposed sensor can be used to detect various concentration of Aflatoxin sample with the ability to offer real time measurement.

Fluorescent Selectivity-Enhanced FRET Based on 3D Photonic Crystals for Multianalyte Sensing.

Fluorescence resonance energy transfer (FRET) finds widespread utility in biochemical sensing, single-molecule experiments, cell physiology, and various other domains due to its inherent simplicity and high sensitivity. Nevertheless, the efficiency of energy transfer between the FRET donor and acceptor is significantly contingent on the local photonic environment, a factor that limits its application in complex systems or multianalyte detections. Here, a fluorescent selectivity-enhanced acridine orange (AO)-aflatoxins (AFs) FRET system based on a range of 3D topological photonic crystals (PCs) was developed with the aim of enhancing the selectivity and discrimination capabilities of FRET. By exploring the angle-dependent characteristics of the photonic stopband, the stopband distribution across different 3D topological PCs pixels was investigated. This approach led to selective fluorescence enhancement in PCs that matched the stopbands, enabling the successful discrimination of six distinct aflatoxins and facilitating complex multianalysis of moldy food samples. In particular, the stopband, which was strategically positioned within the blue-purple structural color range, exhibited a strong alignment with the fluorescence peaks of both the FRET donor and acceptor. This alignment allowed the 3D three-pointed star PCs to be effectively employed for the identification of mixed samples containing six distinct aflatoxins as well as the detection of real aflatoxin samples present in moldy potatoes, bread, oats, and peanuts. Impressively, this approach achieved a remarkable accuracy rate of 100%. This innovative strategy not only presents a novel avenue for developing a multitarget discrimination analysis system but also offers a convenient pretreatment method for the quantitative detection of various aflatoxins.

Development and validation of quantitative thin layer chromatographic technique for determination of total aflatoxins in poultry feed and food grains without sample clean-up.

Objective:The purpose of this work is to develop and validate an appropriate solvent solution and quantitative thin layer chromatography (TLC) method for determining the aflatoxins content of chicken feeds and dietary grains.Materials and Methods:To obtain the optimal mobile phase, samples were extracted with methanol/water (3:1) + 5% sodium chloride and partitioned using several solvent systems using preparative TLC. Camag TLC scanner 3 was used to scan the TLC plates at 366 nm and quantify them using JustTLC software. The method was tested for linearity, specificity, accuracy, precision, sensitivity, and robustness in accordance with ICH recommendations, and then utilized to screen 132 Nigerian poultry/food samples for total aflatoxins (TAFs).Results:The best separation of aflatoxins was achieved using acetonitrile and dichloromethane (3:17) mobile phase over an average run time of 45 min, resulting in linear calibration curves (R2 > 0.99) in the concentration range limit of quantitation (LoQ) to 50 ng/spot with a limit of detection of <2.0 ng/g and a LoQ of <4.0 ng/gm for all aflatoxins in all spiked samples. When the proposed TLC method was compared to an optimized high-performance liquid chromatography method, an excellent linear regression was obtained (R2 > 95%). Seventy seven (58.33%) of the 132 samples examined were positive for aflatoxins, with mean values ranging from 3.57 ± 2.55 to 37.31 ± 34.06 ng/gm for aflatoxin B1 and 6.67 ± 0.00 to 38.02 ± 31.52 ng/gm for TAFs, respectively.Conclusions:The results demonstrate the feasibility of using the suggested TLC method in conjunction with a novel solvent solution (free of carcinogenic chloroform) for the rapid and accurate measurement of TAFs in foods/feeds.

Transfer of Mycotoxins from Lactation Feed to Colostrum of Sows.

Simple SummaryMycotoxin risk levels are known to vary depending on the type of mycotoxins, animal species, age and type of production. In lactating animals, mycotoxins can be transferred from feed consumed to colostrum and milk. This has been well documented for aflatoxicosis in cattle, but not in sows and not for the most diffused mycotoxins. Samples of in-house produced complete feed for lactating sows were obtained from Italian farms. Samples of colostrum were obtained at farrowing from each farm. The feed content of the mycotoxins was generally low. Of the 19 samples analyzed, 10, 12, 17 and 2 were positive for aflatoxins, fumonisins, deoxynivalenol (DON) and zearalenone, respectively; however, only two were above the risk limit. The colostrum samples were all negative for aflatoxins while a faint analytical signal was detected for fumonisins in five samples, notwithstanding very low values in the feed. Deoxynivalenol was frequently present in the colostrum; the highest value was seen in the farm presenting the highest value in the feed. However, this colostrum value was far from the presumed risk value for suckling piglets. More controls regarding feed on the farm are suggested while more studies are advisable regarding the risk of DON toxicosis in suckling pigs.Studies regarding the transfer of mycotoxins from sow feed to colostrum are scarce. A sample of in-house produced lactation feed and one of colostrum were collected from two or three sows per farm (total 49) from 19 farms. The feed contents of aflatoxins (AFs), fumonisins (FUs), deoxynivalenol (DON) and zearalenone (ZEA) were assessed using ELISA and confirmed by liquid chromatography-mass spectrometry (LC-MS), The values were very low (10, 12, 17 and 2 positive samples for AFs, FUs, DON and ZEA, respectively), except for two samples (one AF, one DON). Based on feed values, colostrum samples from 13 farms were tested for at least one mycotoxin (Total 35). Aflatoxins were not found in any sample. A signal for FUs was observed in 5 of 11 colostra, despite low feed values; DON was frequently present in the colostrum (10/14). On the farm where the feed exceeded the DON suggested limits, a higher colostrum content was seen, 10.9 µg/kg, approximately 1/69 of the value showing toxicity in young pigs. The absence of reference values for neonate pigs, and the risk of higher and longer ingestion of DON by sows suggested considering routine checks of sow feed; more research on DON transfer and toxicity in piglets is needed.

Sample Preparation and Analytical Considerations for the US Aflatoxin Sampling Program for Shelled Peanuts

ABSTRACT The USDA aflatoxin sampling program for shelled peanuts is an important component of broader industry efforts to minimize aflatoxin occurrence in the edible market. In this program, official samples are milled with either a traditional hammer/automatic sub-sampling mill, commonly called the Dickens Mill (DM) or with a vertical cutter mill (VCM). Particle size reduction and sample homogenization are the primary objectives of sample preparation (milling) to generate subsamples which best represent the parent sample composition for downstream analysis. DM particle size reduction is limited by the 3.2 mm round hole screens internal to the mill which prevent pasting of the sample. VCM grinding converts the sample to a paste while simultaneously homogenizing the sample. Experiments demonstrate that when testing aflatoxin contaminated peanuts for equivalent sized subsamples prepared from the two mill types, made into water slurries per USDA specifications and subsequently extracted and tested for total aflatoxin per USDA specifications, VCM subsamples are more normally distributed around the sample aflatoxin mean, whereas DM subsamples are more positively skewed (median lower than mean) around the sample aflatoxin mean. Accordingly, milling official samples with a DM compared to VCM promotes more lot misclassifications. It is also demonstrated that for a given subsample after extraction and immunoaffinity column (IAC) purification, the total aflatoxin measured by either high performance liquid chromatography (HPLC) or fluorometry (both USDA approved) are practically equivalent from an accuracy perspective. There are costs (time and resources) associated with decreasing natural variation due to sampling, sample preparation and analytical testing in an aflatoxin sampling/testing program. Sample preparation is a greater source of variation compared to that of the analytical testing. Resources would be better spent replacing DM with VCM mills than converting the final analytical step from IAC-fluorometry to IAC-HPLC in an effort to best classify peanut lots for the edible market.

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

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.

Potential economic losses to the US corn industry from aflatoxin contamination

ABSTRACTMycotoxins, toxins produced by fungi that colonise food crops, can pose a heavy economic burden to the US corn industry. In terms of economic burden, aflatoxins are the most problematic mycotoxins in US agriculture. Estimates of their market impacts are important in determining the benefits of implementing mitigation strategies within the US corn industry, and the value of strategies to mitigate mycotoxin problems. Additionally, climate change may cause increases in aflatoxin contamination in corn, greatly affecting the economy of the US Midwest and all sectors in the United States and worldwide that rely upon its corn production. We propose two separate models for estimating the potential market loss to the corn industry from aflatoxin contamination, in the case of potential near-future climate scenarios (based on aflatoxin levels in Midwest corn in warm summers in the last decade). One model uses the probability of acceptance based on operating characteristic (OC) curves for aflatoxin sampling and testing, while the other employs partial equilibrium economic analysis, assuming no Type 1 or Type 2 errors, to estimate losses due to proportions of lots above the US Food and Drug Administration (USFDA) aflatoxin action levels. We estimate that aflatoxin contamination could cause losses to the corn industry ranging from US$52.1 million to US$1.68 billion annually in the United States, if climate change causes more regular aflatoxin contamination in the Corn Belt as was experienced in years such as 2012. The wide range represents the natural variability in aflatoxin contamination from year to year in US corn, with higher losses representative of warmer years.

Assessing aflatoxin B1 distribution and variability in pistachios: Validation of a Monte Carlo modeling method and comparison to the Codex method

Aflatoxin B1 (AFB1) has genotoxic carcinogenic effects with no threshold. This mycotoxin, produced by Aspergillus fungi species, can be found at a very low incidence in pistachios. More precisely, the contaminant is heterogeneously distributed. Moreover, it is usually found at high concentration levels in contaminated individual nut kernels. For this reason, it is crucial to assess AFB1 distribution and variability accurately in pistachio samples, in order to establish informed sampling schemes for health protection purposes. A modeling method using Monte Carlo simulations for AFB1 distribution in pistachio samples, developed in previous work, required validation. For this purpose, the simulation was adjusted to the distribution observed in 30 kg samples as calculated from the RASFF (Rapid Alert System for Food and Feed) levels reported by Germany for Iranian pistachio imports from September 2002 to September 2004, for the lots tested. As a final result, when the simulated distribution in 10 kg samples was computed from the prior simulation, it was very similar to the distribution observed in representative samples for the same sample size from the RASFF. The simulation method was then compared to another method, for AFB1 distribution and variability assessment, used by the Codex to design aflatoxin sampling plans for tree nuts. Indeed, the distribution observed in 30 kg samples from the RASFF was considered as an input distribution. The output distribution for 10 kg representative samples, as computed using the method, was close to the observed distribution. Results of both simulation methods were very similar. Finally, an extensive comparison of the principles of both methods was performed.

Aflatoxin Sampling and Testing Proficiency in the Texas Grain Industry

Aflatoxin is a group I carcinogen and represents a significant public health and food safety risk throughout the world. Aflatoxin contaminated cereals and oilseeds that contain greater than 20 μg/kg of the toxin (B1, B2, G1, G2) are defined as adulterated by the Texas Commercial Feed Rules and are regulated by the Texas Feed and Fertilizer Control Service. This study was performed to assess sampling and testing of maize for aflatoxin contamination. During 2010, 87 Texas grain elevators’ sampling procedures were assessed and a second investigation documented aflatoxin analysis procedures at 41 grain elevator establishments. The average sample size was 1.8 kg (4 pounds) and fewer than 20% of the grain elevators collected samples using an official (prescribed) sampling pattern by the grain inspection, crop insurance or regulatory authorities within the United States. Proficiency samples were analyzed by 39 cooperating grain elevators and 7 firms accurately analyzed samples containing greater than 300 μg/kg aflatoxin. While sampling contributes to variability in measuring aflatoxin in grain, this study highlights that aflatoxin analysis using commercially available test kits is a major contributor to variation in aflatoxin test results among commercial grain handlers.

Natural co-occurrence of aflatoxins and deoxynivalenol in poultry feed in Pakistan

Two hundred and fifteen broiler poultry feed samples were analysed over the time period of one year for the co-occurrence of aflatoxins and deoxynivalenol (DON). These were determined by GC–MS and ELISA, respectively. LOD values for aflatoxins and DON were 0.5 and 5 µg/kg, respectively. From all investigated 215 poultry feed samples, aflatoxins and DON co-occurred in 100 samples (46%). DON was detected in 114 samples while 100 samples also were positive for aflatoxins. Mean concentrations of positive samples for aflatoxins and DON were 18 and 807 µg/kg, respectively. Twenty-one DON-positive and 42 aflatoxin positive samples were contaminated above the EU maximum legal limits of 1000 µg/kg and 20 µg/kg, respectively. The present study provided useful data on aflatoxin and DON contamination, which may be helpful for future strategies to control contamination and to formulate standards in poultry feeds.

Using antibody coated gold nanoparticles as fluorescence quenchers for simultaneous determination of aflatoxins (B1, B2) by soft modeling method

Preparation of antibody coated gold nanoparticles (GNPs) specific to aflatoxins B1 and B2 and its use in rapid aflatoxin determination method was presented in this paper. The formation of gold-labeled antibodies was accomplished at optimal condition. The processes were monitored by UV–visible light measurements, transmission electron microscopy (TEM) and fluorescence spectroscopy. It was found that GNPs with definite surface plasmon absorption can quench the fluorescence of aflatoxins. The quenching of the fluorescence of excitation emission matrices (EEMs) of both aflatoxin samples, provoked by gold-labeled antibodies, was studied by multivariate curve resolution with alternating least squares (MCR–ALS) method. Quantitative results obtained from aflatoxins in pistachio nut samples by MCR–ALS are compared to those obtained using the HPLC method. There are no significant differences between the methodology proposed and the standard one, and may be a good alternative to the traditional methods of analysis for aflatoxins.

Assessment of aflatoxin intake in São Paulo, Brazil

In this study, the aflatoxin consumption was assessed by aflatoxin determination in peanut, corn, bean, milk and derivatives collected directly from home of residents of Pirassununga Sao Paulo, Brazil, and a Food Frequency Questionnaire (FFQ) answered by volunteers. Samples were collected four times every three month, totaling 240 samples from 34 volunteers who answered the FFQs. Aflatoxins B1, B2, G1, G2 and M1 were determined by high performance liquid chromatography using a previous validated method with immunoaffinity column clean-up. Thirty-five percent of peanut samples tested positive for aflatoxin (AFB1 + AFB2 + AFG1 + AFG2) at levels of 0.05–36.7 μg kg−1. Corn derivatives showed 42% positive samples for aflatoxins (0.05–8.3 μg kg−1), with a higher incidence in corn meal. Bean samples had the highest incidence of aflatoxins (75% positive samples), but at lower levels (0.025–0.042 μg kg−1). Forty percent of fluid milk samples tested positive for AFM1 at concentrations from 0.009 to 0.069 μg L−1. AFM1 was quantified in 30% of positive cheese at levels from 0.091 to 0.30 μg kg−1. Yoghurt samples had no detectable levels of AFM1. Aflatoxin intake was calculated considering the aflatoxin concentration values in the food products and the individual FFQ results. Peanut products had the highest contribution to aflatoxin intake, with mean probable daily intake (PDI) of 1.56 ng kg−1 body weight (b.w.) day−1. Milk was the main source of AFM1 in the diet of individuals, which PDI values ranged from up to 0.10 ng kg−1 b.w. day−1. Although low levels of aflatoxin were found in all types of samples, the consumption data reported indicate that the food products evaluated may contribute significantly for the overall human exposure in the population studied.

MONITORING OF FUNGI PRODUCING AFLATOXINS, AND DIETARY INTAKE OF AFLATOXINS IN FOOD CONSUMED BY EGYPTIAN INFANTS AND YOUNG CHILDREN

Fungi producing aflatoxins B1, B2, G1 and G2 are common contaminants of cereals and corn-based products. A monitoring study of fungi producing aflatoxins in baby corn-based products was carried out in Great Cairo Governorate during the year 2008. One hundred (100) samples of cereal based product (50 samples of each are cereal-based infants food and corn-based snacks) were purchased from supermarkets and small shops. The samples were subjected to isolation and identification of fungi producing aflatoxins, five genera of filamentous fungi were isolated from the cereal-based infants food samples. The most fungi found in samples were Aspergillus spp. followed by Penicillium spp., Alternaria spp., Fusarium spp. and Cladosporium spp. and the numbers of contaminated samples were 18, 6, 2, 2 and 1 samples respectively. The same five genera were isolated from corn-based snacks samples, Aspergillus spp. was the most frequent and abundant genus and the number of contaminated samples was (23), then Penicillium spp. (10), Alternaria spp. (8), Fusarium spp. (6), and Cladosporium spp. (2). Prepared samples were extracted with methanol: water (80+20) and cleaned up with 0.5 g silica gel column while detection was with liquid chromatograph using fluorescence detector. Only samples which contain corn or maize were contaminated when the others were free from any detected amount of aflatoxins. Seven samples of 50 cereal-based infant food were contaminated with aflatoxin B1 and total aflatoxins the mean minimum and maximum amounts were (1, 38, 0.54, 2, 22) and (2.42, 0.54, 6.9), respectively. However, the numbers of contaminated samples with B2, G1 and G2 were 1; 3 and 2 respectively. Mean, minimum and maximum were (0.5), (1.66, 0.8, 2.98) and (0.9, 0.6, 1.2), respectively. The monitored corn-based snacks samples have corn as the main component in addition to different types of flavors including cheese, chili, peanut, tomato, salt, ketchup, honey, kabab, par pique and spices that increase the numbers of contaminated samples with aflatoxins B1, B2, G1, G2 and total which were 17, 7, 9, 4 and 17 samples respectively. Also the means were high, they recorded 4.43, 0.51, 3.74, 1.55 and 6.7 µg/kg, respectively. However, the minimum were almost near to the data of cereal-based infant food (0.59, 0.51, 1.1, 0.92 and 0.59 µg/kg, respectively) but the maximum amounts were clearly higher (15.83, 2.01, 8.1, 2.42 and 18.84 µg/kg, respectively), thus according to the present study 12 samples of corn-based snacks surpassed the established limit (2 µg/kg ) for B1 with violation percentage 71%, and 7 samples surpassed the limit established for total aflatoxins (4 µg/kg) with violation percentage 41%. As a second tool of risk assessment, estimated daily Intake (EDI) and (EWI) of aflatoxin B1 and total aflatoxins were calculated from the mean of contaminated samples of cereal based infant food. EDI and EWI of aflatoxin B1 due to consuming cereals-based infant food by babies were 4.14 and 28.7 ng/kg b.w., however, EDI and EWI of total aflatoxins were 7.26 and 50.82 ng/kg b.w. Moreover, ratio percentages of EDI and EWI were calculated for only B1, the calculated results were 41.40% for both, which means that the babies consumed 14-fold higher than the PMTDI that, subject babies to health risk. Also only EDI and EWI were calculated from the mean of contaminated corn-based snacks samples for total aflatoxins for babies, adolescent and adults and the results are for EDI (20.1, 8.37 and 5.58 ng/kg b.w./day, respectively) and for EWI (140.7, 58.59 and 39.06 ng/kg b.w./week, respectively). While EDI and EWI were calculated with aflatoxin B1 and the values are, EDI (13.29, 5.54 and 3.69 ng/kg b.w./day, respectively) and EWI (93.07, 38.78 and 25.83 ng/kg b.w./week, respectively). Ratio percentages of EDI and EWI were also calculated for aflatoxin B1 and the percentages are 8860, 3693 and 2460%, respectively.

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

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.

Number of export almond lots rejected in the EU due to USA sampling plans and aflatoxin contamination levels among lots tested

In March 2010, the European Union (EU) modified their aflatoxin limits and sampling plans for almonds, pistachios, and hazelnuts to closely resemble that developed by Codex in 2008. To assist the USA almond industry evaluate how to modify their aflatoxin sampling plan to minimise USA lots rejected by the EU at import, studies were conducted to: (a) develop a model to predict the number of USA almond lots rejected at origin and at destination by various Codex style aflatoxin-sampling plans used by the USA where accept/reject limits vary from EU limits of 8 ng/g aflatoxin B1 / 10 ng/g total aflatoxins (AFT) to 8, 6, 4, 2, and 0.5 ng/g AFT; (b) determine the effect of the level of aflatoxin contamination among lots tested in the USA on the number of lots accepted and rejected at origin and at destination; and (c) develop a method based upon lots rejected in the USA to predict the lots rejected several months later in the EU. For a given USA crop contamination level, as the accept/reject limits of the USA sampling plan decreases from 8 to 0.5 ng/g AFT, the number of lots rejected in the USA increases, the average aflatoxin concentration among all lots accepted for export decreases, the number of lots rejected in the EU decreases, and the average aflatoxin concentration among lots accepted in the EU decreases. For a given USA aflatoxin sampling plan used at origin, an increase in the USA crop aflatoxin contamination level increases the number of lots rejected at origin, increases the average aflatoxin concentration in USA lots accepted for export, increases the number of lots rejected in the EU, and increases the average aflatoxin concentration among lots accepted in the EU. Graphical techniques were developed to use the percentage of lots rejected in the USA to predict the percentage of USA lots rejected by the EU.

Comparing the performance of sampling plans that use a single regulatory limit based upon total aflatoxins to sampling plans that use dual limits based upon B1 and total aflatoxins

The European Commission (EC) aflatoxin sampling plan for ready-to-eat tree nuts such as almonds requires that each of the three 10 kg laboratory samples must all test less than 2 ng/g aflatoxin B1 (AFB1) and 4 ng/g total aflatoxins (AFT) for the lot to be accepted. Exporters have observed that the AFB1/AFT ratio varied greatly from sample to sample and the ratio appeared to average more than 50%. Because of the concern that dual limits associated with the EC aflatoxin sampling plans may reject more lots than similar sampling plans that use a single limit based upon total aflatoxins, studies were designed with the objectives to (a) measure the distribution of AFB1/AFT ratio values using sample test results associated with testing U.S. almond lots exported to the European Union; (b) use Monte Carlo methods to develop a model to compute the effects of using dual limits based upon AFB1 and AFT on the probability of accepting almond lots; and (c) compare the probability of accepting almond lots using the current Codex aflatoxin sampling plans for tree nuts when using single limits versus the use of dual limits. The study results showed that the mean and median among 3,257 AFB1/AFT ratio values was 87.6% and 91.9%, respectively, indicating that the distribution among the ratio values was negatively skewed. Only 31% of the 3,257 AFB1/AFT ratio values are less than the mean ratio of 87.6%. Codex aflatoxin sampling plans for tree nuts using a single limit based upon total aflatoxins had the highest probability of accepting lots at all lot concentrations when compared to the probability of accepting lots with dual limits. As the AFB1 limit decreased from 90 to 50% of the total limit, the probability of rejecting lots at all concentrations increased when compared to the Codex aflatoxin sampling plans with a single limit based upon total aflatoxins.

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

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.

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

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.

Updated profile of aflatoxin and Aspergillus section Flavi contamination in rice and its byproducts from the Philippines

Our goal was to develop an updated profile of aflatoxin (AF) and AF-producing fungi contamination in rice and its byproducts from the Philippines. The total AF levels in 78 samples of polished and brown rice, determined by an immunoaffinity column clean-up method coupled with HPLC (detection limit: 25 ng/kg), ranged from <0.025–2.7 µg/kg (mean of positive samples: 0.37 µg/kg) and 0.03–8.7 µg/kg (mean of positive samples: 2.7 µg/kg), respectively. The incidence (% of positive samples) of AF in polished and brown rice were 94% and 100%, respectively. The AF levels in polished rice imported from Thailand and Vietnam were approximately 20% of the levels found in locally produced polished rice. AF levels decreased as the rice progressed through the various stages in milling. Fungi recovered include toxigenic Aspergillus flavus and A. parasiticus with an incidence ranging from 14% in rice bran to 78% in rough rice and producing <0.025−6200 µg/kg total AF in in vitro cultures on rice. All samples of rice bran and rice hull contained AF at levels ranging from 0.27–11 µg/kg. The estimated potential daily intake of AFB1 from rice is between 0.1 and 7.5 ng/kg of body weight/day, the mean of which is 1.0 ng representing 9.1–5.3 times the estimated tolerable daily intake for AFB1 reported to date for Asia. Thus, Filipinos have a potentially high risk of exposure to AF that can be easily controlled through proper post-harvest handling and storage of rice and its byproducts.

Standardisation of mycotoxin sampling procedures: an urgent necessity

A mycotoxin sampling plan is defined by the mycotoxin test procedure (sample size, sample preparation method, and analytical method) and the accept/reject limit. Because of the variability associated with each step of the mycotoxin test procedure, the true mycotoxin concentration of a bulk lot cannot be determined with 100% certainty. As a result, some lots will be misclassified by the sampling program. Some good lots will be rejected by the sampling plan (seller’s risk or false positives) and some bad lots will be accepted by the sampling plan (buyer’s risk or false negatives). The magnitude of these risks is directly related to the magnitude of the variability associated with the mycotoxin test procedure. It is difficult for an exporter to have an effective control program when regulatory limits and sample designs differ greatly among trading countries. In order to facilitate trade and provide protection for the consumer, it would be desirable for all trading countries to have the same mycotoxin limits and sample plan. While standardization of sampling plans among trading nations is important, any standardised sampling plan must be designed to minimize both the seller’s and buyer’s risks to the lowest possible levels that resources will allow. Reducing the variability of the mycotoxin test procedure will reduce both the buyer’s and seller’s risks. It is important to understand the sources of error in the mycotoxin test procedure so the errors can be effectively reduced. The sampling step usually is the largest source of error due to the extreme mycotoxin distribution among kernels in the lot. As an example, sampling (5 kg), sample preparation (USDA subsampling mill and 250 g subsample), and analysis (TLC) accounted for 83%, 9%, and 8% of the total aflatoxin testing error, respectively, when testing raw shelled peanuts for aflatoxin. Examples are given to show how increasing sample size reduces sampling error; increasing the fineness of grind and using larger subsamples reduces sample preparation error, and increasing the number of aliquots analyzed and using improved technology (HPLC versus TLC) decreases analytical error. International organizations such as FAO/WHO have used scientific techniques to evaluate and design aflatoxin sampling plans for raw shelled peanuts traded in the export market.