Quality Control of Pesticide Residue Measurements and Evaluation of Their Results.

Pesticide residues are monitored in many countries around the world. The main aims of the programs are to provide data for dietary exposure assessment of consumers to pesticide residues and for verifying the compliance of the residue concentrations in food with the national or international maximum residue limits. Accurate residue data are required to reach valid conclusions in both cases. The validity of the analytical results can be achieved by the implementation of suitable quality control protocols during sampling and determination of pesticide residues. To enable the evaluation of the reliability of the results, it is not sufficient to test and report the recovery, linearity of calibration, the limit of detection/quantification, and MS detection conditions. The analysts should also pay attention to and possibly report the selection of the portion of sample material extracted and the residue components according to the purpose of the work, quality of calibration, accuracy of standard solutions, and reproducibility of the entire laboratory phase of the determination of pesticide residues. The sources of errors potentially affecting the measured residue values and the methods for controlling them are considered in this article.

Probabilistic modeling and risk characterization of the chronic aflatoxin M1 exposure of Hungarian consumers.

Aflatoxin contamination can appear in various points of the food chain. If animals are fed with contaminated feed, AFB1 is transformed-among others-to aflatoxin M1 (AFM1) metabolite. AFM1 is less toxic than AFB1, but it is still genotoxic and carcinogenic and it is present in raw and processed milk and all kinds of milk products. In this article, the chronic exposure estimation and risk characterization of Hungarian consumers are presented, based on the AFM1 contamination of milk and dairy products, and calculated with a probabilistic method, the two-dimensional Monte-Carlo model. The calculations were performed using the R plugin (mc2d package) integrated into the KNIME (Konstanz Information Miner) software. The simulations were performed using data from the 2018-2020 food consumption survey. The AFM1 analytical data were derived from the Hungarian monitoring survey and 1,985 milk samples were analyzed within the framework of the joint project of the University of Debrecen and the National Food Chain Safety Office of Hungary (NÉBIH). Limited AFM1 concentrations were available for processed dairy products; therefore, a database of AFM1 processing factors for sour milk products and various cheeses was produced based on the latest literature data, and consumer exposure was calculated with the milk equivalent of the consumed quantities of these products. For risk characterization, the calculation of hazard index (HI), Margin of Exposure, and the hepatocellular carcinoma incidence were used. The results indicate that the group of toddlers that consume a large amount of milk and milk products are exposed to a certain level of health risk. The mean estimated daily intake of toddlers is in the range of 0.008-0.221 ng kg-1 bw day-1; the 97.5th percentile exposure of toddlers is between 0.013 ng kg-1 bw day-1 and 0.379 ng kg-1 bw day-1, resulting in a HI above 1. According to our study, the exposure of older age groups does not pose an emergent health risk. Nevertheless, the presence of carcinogenic compounds should be kept to a minimum in the whole population.

A Systematic Review of the Efficacy of Interventions to Control Aflatoxins in the Dairy Production Chain-Feed Production and Animal Feeding Interventions.

The study presents a systematic review of published scientific articles investigating the effects of interventions aiming at aflatoxin reduction at the feed production and animal feeding phases of the milk value chain in order to identify the recent scientific trends and summarize the main findings available in the literature. The review strategy was designed based on the guidance of the systematic review and knowledge synthesis methodology that is applicable in the field of food safety. The Web of Science and EBSCOhost online databases were searched with predefined algorithms. After title and abstract relevance screening and relevance confirmation with full-text screening, 67 studies remained for data extraction, which were included in the review. The most important identified groups of interventions based on their mode of action and place in the technological process are as follows: low-moisture production using preservatives, acidity regulators, adsorbents and various microbiological additives. The results of the listed publications are summarized and compared for all the identified intervention groups. The paper aimed to help feed producers, farmers and relevant stakeholders to get an overview of the most suitable aflatoxin mitigation options, which is extremely important in the near future as climate change will likely be accompanied by elevated mycotoxin levels.

Corrigendum: Detection of Aflatoxins in Different Matrices and Food-Chain Positions.

[This corrects the article DOI: 10.3389/fmicb.2020.01916.].

Sources of Random Variation of Pesticide Residue Analytical Results.

BACKGROUND: Pesticide residues are analyzed in thousands of samples yearly by national authorities and private laboratories. Intensive research is ongoing to develop new methods or improve existing ones concentrating on extraction, cleanup, and detection techniques. Little attention has been paid to the contribution of prior steps in the determination process to overall laboratory sampling errors, though several publications demonstrate their practical importance. Consequently, the repeatability and reproducibility of the results are often reported based on the recovery tests alone. A few previous publications are cited in this paper which illustrate the magnitude of random errors derived from subsampling, comminution of analytical samples, and selection of small test portions. OBJECTIVES: We aim to call attention to the importance of considering all steps of laboratory sampling and analysis processes in calculating the combined uncertainty of results and realistic performance assessments of methods including their long-term intermediate precision. METHOD: Validation of laboratory sampling of large fruits is used to illustrate the recommended procedures, determination of their random error, and long-term method performance. RESULTS: The results indicate that subsampling, comminution, and selection of test portions can be major contributors to the combined uncertainty of results. CONCLUSIONS: All these steps should be considered in estimation of random variation (uncertainty) of measured residues. HIGHLIGHTS: Random error of laboratory sampling for pesticide residues. Mass reduction of large crop units. Internal quality control of laboratory operations.

Detection of Aflatoxins in Different Matrices and Food-Chain Positions.

Aflatoxins, produced mainly by filamentous fungi Aspergillus flavus and Aspergillus parasiticus, are one of the most carcinogenic compounds that have adverse health effects on both humans and animals consuming contaminated food and feed, respectively. Aflatoxin B1 (AFB1) and aflatoxin B2 (AFB2) as well as aflatoxin G1(AFG1) and aflatoxin G2 (AFG2) occur in the contaminated foods and feed. In the case of dairy ruminants, after the consumption of feed contaminated with aflatoxins, aflatoxin metabolites [aflatoxin M1 (AFM1) and aflatoxin M2 (AFM2)] may appear in milk. Because of the health risk and the official maximum limits of aflatoxins, there is a need for application of fast and accurate testing methods. At present, there are several analytical methods applied in practice for determination of aflatoxins. The aim of this review is to provide a guide that summarizes worldwide aflatoxin regulations and analytical methods for determination of aflatoxins in different food and feed matrices, that helps in the decision to choose the most appropriate method that meets the practical requirements of fast and sensitive control of their contamination. Analytical options are outlined from the simplest and fastest methods with the smallest instrument requirements, through separation methods, to the latest hyphenated techniques.

Occurrence of Aflatoxin M1 in Raw Milk Marketed in Italy: Exposure Assessment and Risk Characterization.

The current study is based on the AFM1 contamination of milk determined from April 2013 to December 2018 in the framework of a self-control plan of six milk processing plants in Italy. These data - together with the consumption data of milk consumers - were evaluated and used for the calculation of the Estimated Daily Intake (EDI), the Hazard Index (HI), and the fraction of hepatocarcinoma cases (HCC) due to AFM1 exposure in different population groups. Altogether a total of 31,702 milk samples were analyzed, representing 556,413 tons of milk, which is an outstanding amount compared to published studies. The results indicate the monthly fluctuation of AFM1 levels through a period of nearly 6 years. The EDI of AFM1 in different population groups was in the range of 0.025-0.328 ng kg-1 body weight (bw) per day, based on the average consumption levels and weighted mean contamination of the milk in the study period. Considering average consumptions, in the groups of infants and toddlers, the HI calculation resulted in 1.64 and 1.4, respectively, while for older age groups, it was <1. The estimated fractions of HCC incidences attributable to the AFM1 intakes were 0.005 and 0.004 cases per 100,000 individuals in the 0-0.9 and 1-2.9-year age groups, respectively, and below 0.004 cases in the other age categories. The monthly average AFM1 contamination of tested milk consignments ranged between 7.19 and 22.53 ng kg-1. Although the results of this extensive investigation showed a low risk of HCC, the variability of climatic conditions throughout years that influence AFB1 contamination of feed and consequently AFM1 contamination of milk justifies their continuous monitoring and update of the risk assessment.

Uncertainty of pesticide residue concentration determined from ordinary and weighted linear regression curve.

Determination of pesticide residues is based on calibration curves constructed for each batch of analysis. Calibration standard solutions are prepared from a known amount of reference material at different concentration levels covering the concentration range of the analyte in the analysed samples. In the scope of this study, the applicability of both ordinary linear and weighted linear regression (OLR and WLR) for pesticide residue analysis was investigated. We used 782 multipoint calibration curves obtained for 72 different analytical batches with high-pressure liquid chromatography equipped with an ultraviolet detector, and gas chromatography with electron capture, nitrogen phosphorus or mass spectrophotometer detectors. Quality criteria of the linear curves including regression coefficient, standard deviation of relative residuals and deviation of back calculated concentrations were calculated both for WLR and OLR methods. Moreover, the relative uncertainty of the predicted analyte concentration was estimated for both methods. It was concluded that calibration curve based on WLR complies with all the quality criteria set by international guidelines compared to those calculated with OLR. It means that all the data fit well with WLR for pesticide residue analysis. It was estimated that, regardless of the actual concentration range of the calibration, relative uncertainty at the lowest calibrated level ranged between 0.3% and 113.7% for OLR and between 0.2% and 22.1% for WLR. At or above 1/3 of the calibrated range, uncertainty of calibration curve ranged between 0.1% and 16.3% for OLR and 0% and 12.2% for WLR, and therefore, the two methods gave comparable results.

Factors affecting the quantitative uncertainty of the estimated short-term intake. Part II-Practical examples.

The effects of the spread of residue concentrations in the samples derived from the selected supervised trials and the number of trials were studied on the magnitude and uncertainty of the short-term dietary intakes calculated with the proposed new procedure (IESTIp) and that one used currently by the FAO (Food and Agriculture Organization) and WHO (World Health Organization) Joint meeting on Pesticide Residues (JMPR) (IESTIc). The residue data of 10 pesticides were obtained from supervised trials conducted on apples and pears. The methods described in Part I were used for the calculations of the uncertainty. The results indicate that the ratio of IESTIP to IESTIc (φIESTI) is directly proportional to the ratio of the estimated maximum residue level (MRL), recommended by the JMPR; to the highest residue (HR) observed in supervised trials, and it may have a wide range depending on the particular conditions. The φIESTI becomes greater with the increase of the difference between the mrl or maximum residue limit (MRL, established by the Codex Alimentarius Commission, CAC) and HR, and becomes smaller if the difference between the large portion (LP) and unit mass (U) decreases. The φIESTI ranged between 2 and 5.1 in the 16 cases examined indicating that the IESTIp calculation method leads to higher intake estimates. The ratio of CVIESTIp and CVIESTIc ranged typically between 0.62 and 1.71. It rapidly increased up to 12 trials. For a larger number of trials, the ratio remained practically constant (1.69-1.71). The processing factor (PF) equally affects the MRL and HR values, therefore, it will not practically influence the φIESTI. The uncertainty of the estimated median residues depends on the spread and number of values in the residue datasets, which affects the uncertainty of the conversion factor (CF) and subsequently the uncertainty of the estimated IESTIp. Residue values obtained from minimum nine independent trials are required for the correct calculation of the 95% confidence intervals of the calculated median residues. The uncertainty of the analytical results directly affects the median, HR values and indirectly the calculated mrl and the MRL derived from it. Therefore, it should also be considered for the calculation of the combined uncertainty of the conversion factors. For the correct interpretation of the results of dietary exposure calculations, the upper 95% confidence limit of the short-term intake should also be considered. However, it is not the current practice of regulatory agencies or JMPR.

Factors affecting the quantitative uncertainty of the estimated short-term intake. Part I-Calculation methods.

The calculation of the combined uncertainty of the international estimated short-term intake (IESTI) of ethephon residues in apples is shown as an example. The ethephon residues in apples were reported by the Joint FAO (Food and Agriculture Organization of the United Nations)/WHO (World Health Organization) Meeting on Pesticide Residues (JMPR). The apple consumption data were taken from the IESTI (international short-term intake) calculation template used by the JMPR. The IESTI was calculated with the currently used method (case 2a) and a proposed one recommended by the EFSA (European Food Safety Authority)/RIVM (Dutch National Institute for Public Health) Scientific Workshop co-sponsored by FAO and WHO. In this example, the ratio of IESTIproposed/IESTIcurrent and their combined relative uncertainty are about 2.8, and 1.7, respectively. The larger IESTI and uncertainty obtained with the proposed equation are the consequence of calculation only with the large portion (LP) instead of its combination with unit mass, and the MRL instead of the highest residue (HR). The LP is the major contributor to the combined uncertainty. Both the calculated IESTI and its combined uncertainty depend on the actual food - pesticide residue combination, and should be calculated for each case.

Validation of a picture book to be used in a pan-European dietary survey.

OBJECTIVE: To validate a picture book for estimation of food portion sizes using two approaches: (i) 'perception' of food portions by comparison with a series of food photos; and (ii) 'conceptualization and memory', using the same photos to estimate the amount of served food one hour after self-served food portions. DESIGN: Each partner developed a country-specific picture book based on the so-called EPIC-Soft picture book. Representative and common photo series were chosen achieving approximately 25 % of the original picture book (n 23). Three portions from each photo series were randomly selected. SETTING: The study was performed within the Pilot study in the view of a Pan-European dietary survey - Adolescents, adults and elderly (PILOT-PANEU) project. SUBJECTS: A sample of adolescents and adults was recruited in five countries: Bulgaria (n 103), Finland (n 34), Germany (n 69), Hungary (n 62) and Portugal (n 77). RESULTS: Among the portions of the corresponding photo series and depending on the type of food, from 18 % (cheese) to 96 % (ratatouille) of participants chose the correct portions. In the perception study, agreement between the portions shown and reported was substantial (intraclass correlation coefficient (ICC)=0·805) and the mean difference was very low. In the memory study, agreement between the served and reported portions was lower than in the perception study (ICC=0·536). Agreement also seemed to decrease as the appearance of food on the plate differed from food in the picture. CONCLUSIONS: Overall, the picture series selected can be applied in future intake surveys to quantify foods similar to those depicted in the pictures.

Occurrence and distribution of trifluralin, ethalfluralin, and pendimethalin in soils used for long-term intensive cotton cultivation in central Greece.

In the present study, a soil monitoring program was undertaken in Greek cotton cultivated areas in 2012. Twenty-seven soil samples were collected from the entire Thessaly plain in early summer of 2012, corresponding to approximately three months (current use of pendimethalin), up to one year (for the banned ethalfluralin), and three years (for the also banned trifluralin), after the last dinitroaniline application. Low but not negligible levels of dinitroanilines were detected, ranging from 0.01 to 0.21 µg g-1 d.w. for trifluralin and 0.01-0.048 µg g-1 d.w. for pendimethalin, respectively. Trifluralin was the herbicide most frequently detected (44.4%). The high historic application of trifluralin and its high persistence and accumulation potential is in line with the abundance of the detected residues. The present data indicate that soil samples contain extractable residues of banned trifluralin, but based on the comparison of the theoretical PECplateau for trifluralin (0.277 µg g-1) and the maximum Measured Environmental Concentration, it was concluded that the detected residues should be attributed to previous years' application. The latter suggested the need for continual monitoring of the dinitroaniline family of pesticides, including the banned substances, aiming thus to an improved environmental profile for agricultural areas.

Uncertainty of exposure assessment of consumers to pesticide residues derived from food consumed.

The sources of quantitative and qualitative uncertainties of the exposure of a consumer to a pesticide residue are identified. The contribution of quantifiable uncertainties of input parameters of deterministic model to the combined uncertainty of the estimated exposure is shown with detailed calculation using the pesticide residue content of food consumed during two days. The daily intakes of bifenthrin residues calculated for the 60 kg bodyweight of the reporting person are 0.00257 mg/kgbw and 0.00281 mg/kgbw for day 1 and day 2, respectively with 27-28% combined uncertainty. The major contributors were fruits and whole meal bread. The contribution of the individual steps to the combined uncertainty depends on the particular food item. In general, the variability of recipes, estimation of the mass of consumed food, sampling, processing of raw commodities and analysis of pesticide residues influenced most, in decreasing order, the combined uncertainty of the estimated daily exposure.

Testing the efficiency of extraction of incurred residues from soil with optimized multi-residue method.

The reproducibility of extraction of residues from spiked soil samples and from soils containing incurred residues was tested with 14C-labeled test compounds of different physical-chemical properties. Nearly 100% of the compounds added to the sample before extraction could be recovered with an average reproducibility relative standard deviation (CV) of 5.4%. The additional steps of the determination process (cleanup, evaporation, etc.) contributed to the major part of the variability of the results (CV = 10-20%). The incurred residues were most efficiently extracted with acetone for 30 min followed by the mixture of acetone/ethyl acetate 1:1 for additional 30 min. However, they could only be recovered at various extent (64-90% of total residues), underlying the importance of testing the efficiency of extraction. The residues were identified and quantified by gas chromatography applying thermionic detector. The performance parameters of the method complied with the international method validation guidelines, and they proved to be robust and suitable for determination of pesticide residues in soils of widely different physical-chemical properties.

Distribution of pesticide residues in soil and uncertainty of sampling.

Pesticide residues were determined in about 120 soil cores taken randomly from the top 15 cm layer of two sunflower fields about 30 days after preemergence herbicide treatments. Samples were extracted with acetone-ethyl acetate mixture and the residues were determined with GC-TSD. Residues of dimethenamid, pendimethalin, and prometryn ranged from 0.005 to 2.97 mg/kg. Their relative standard deviations (CV) were between 0.66 and 1.13. The relative frequency distributions of residues in soil cores were very similar to those observed in root and tuber vegetables grown in pesticide treated soils. Based on all available information, a typical CV of 1.00 was estimated for pesticide residues in primary soil samples (soil cores). The corresponding expectable relative uncertainty of sampling is 20% when composite samples of size 25 are taken. To obtain a reliable estimate of the average residues in the top 15 cm layer of soil of a field up to 8 independent replicate random samples should be taken. To obtain better estimate of the actual residue level of the sampled filed would be marginal if larger number of samples were taken.

An effective self-control strategy for the reduction of aflatoxin M1 content in milk and to decrease the exposure of consumers.

The study reports the results of testing the sensitivity of an early warning sampling plan for detecting milk batches with high aflatoxin AFM1 concentration. The effectiveness of the method was investigated by the analysis of 9017 milk samples collected in Italian milk processing plants that applied control plans with different action limits (AL). For those milk processing plants where 30 ng kg-1 AL has been applied, the AFM1 contamination was significantly lower at or above the 95th percentile of the milk samples when compared with plants that used 40 ng kg-1 AL. The results show that the control plan can be used effectively for early warning of occurrence of high AFM1 contamination of milk and to carry out pro-active measures to limit the level of contamination. Estimation of dietary exposure was also carried out, based on the aflatoxin M1 content of the milk samples and on Italian food consumption data. Estimated Daily Intakes (EDI) and Hazard Indices (HI) were calculated for different age groups of the population. HIs show that no adverse effects are expected for the adult population, but in the case of children under age three, the approximate HI values were considerably higher. This underlines the importance of the careful monitoring and control of aflatoxin M1 in milk and dairy products.