National governments introduced residue limits and guideline levels for pesticide residues in water when policies were implemented to minimize the contamination of ground and surface waters. Initially, the main attention was given to drinking water.Regulatory limits for pesticide residues in waters should have the following characteristics: definition of the type of water, definition of the residue, a suitable analytical method for the residues, and explanation for the basis for each limit.Limits may be derived by applying a safety factor to a no-effect-level, or from levels occurring when good practices are followed and also passing a safety assessment, or from the detection limit of an analytical method, or directly by legislative decision.The basis for limits and guideline values issued by WHO, Australia, the United States, New Zealand, Japan, Canada, European Union, and Taiwan is described, and examples of the limits are provided. Limits have been most commonly developed for drinking water, but values have also been proposed for environmental waters, effluent waters, irrigation waters, and livestock drinking waters. The contamination of ground water is of concern because it may be used as drinking water and act as a source of contamination for surface waters. Most commonly, drinking water standards have been applied to ground water.The same terminology may have different meanings in different systems. For example, guideline value (GV) in WHO means a value calculated from a toxicology parameter, whereas in Australia, a GV is at or about the analytical limit of determination or a maximum level that might occur if good practices are followed. In New Zealand, the GV is the concentration where aesthetic significance is influenced.The Australian health value (HV) is conceptually the same as the WHO GV. The New Zealand maximum acceptable value (MAV) and the Canadian maximum acceptable concentration (MAC) are also conceptually the same as the WHO GV.Each of the possible ways of defining the residues has its merits. A residue limit in water expressed as the sum of parent and toxicologically relevant transformation products makes sense where it is derived from the acceptable daily intake (ADI). For monitoring purposes, where it is best to keep the residue definition as simple as possible for the sake of practical enforcement and economy, theparent or a marker residue is preferable. It is also possible for parent and degradation products (hydrolysis and photolysis products and metabolites) to become physically separated as the water moves through soil strata, which suggests that separate limits should be set for parent and important degradation products.The Commission has made 12 recommendations for regulatory limits for pesticide residues in water. The recommendations will act as a checklist for authorities introducing or revising limits or guidelines for pesticide residues in water.

Consumer risk assessment is a crucial step in the regulatory approval of pesticide use on food crops. Recently, an additional hurdle has been added to the formal consumer risk assessment process with the introduction of short-term intake or exposure assessment and a comparable short-term toxicity reference, the acute reference dose. Exposure to residues during one meal or over one day is important for short-term or acute intake. Exposure in the short term can be substantially higher than average because the consumption of a food on a single occasion can be very large compared with typical long-term or mean consumption and the food may have a much larger residue than average. Furthermore, the residue level in a single unit of a fruit or vegetable may be higher by a factor (defined as the variability factor, which we have shown to be typically x3 for the 97.5th percentile unit) than the average residue in the lot. Available marketplace data and supervised residue trial data are examined in an investigation of the variability of residues in units of fruit and vegetables. A method is described for estimating the 97.5th percentile value from sets of unit residue data. Variability appears to be generally independent of the pesticide, the crop, crop unit size and the residue level. The deposition of pesticide on the individual unit during application is probably the most significant factor. The diets used in the calculations ideally come from individual and household surveys with enough consumers of each specific food to determine large portion sizes. The diets should distinguish the different forms of a food consumed, eg canned, frozen or fresh, because the residue levels associated with the different forms may be quite different. Dietary intakes may be calculated by a deterministic method or a probabilistic method. In the deterministic method the intake is estimated with the assumptions of large portion consumption of a 'high residue' food (high residue in the sense that the pesticide was used at the highest recommended label rate, the crop was harvested at the smallest interval after treatment and the residue in the edible portion was the highest found in any of the supervised trials in line with these use conditions). The deterministic calculation also includes a variability factor for those foods consumed as units (eg apples, carrots) to allow for the elevated residue in some single units which may not be seen in composited samples. In the probabilistic method the distribution of dietary consumption and the distribution of possible residues are combined in repeated probabilistic calculations to yield a distribution of possible residue intakes. Additional information such as percentage commodity treated and combination of residues from multiple commodities may be incorporated into probabilistic calculations. The IUPAC Advisory Committee on Crop Protection Chemistry has made 11 recommendations relating to acute dietary exposure.

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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.

In this study, a version of the "quick, easy, cheap, effective, rugged, and safe" (QuEChERS) method was modified to use ethyl acetate (EtOAc) rather than acetonitrile (MeCN) for extraction in the determination of multiple pesticide residues in fruits and vegetables. EtOAc is better suited than MeCN for gas chromatographic (GC) analysis with electron capture detection (ECD) and nitrogen-phosphorus detection (NPD). The method entailed extraction of 30 g chopped sample plus 5 g NaHCO(3) and 30 g anhydrous Na(2)SO(4) with 60 mL EtOAc using a probe blender. After a centrifugation step, removal of residual water and cleanup were performed using dispersive solid-phase extraction (dispersive-SPE) with MgSO(4) and primary secondary amine (PSA) sorbent. (14)C-labeled chlorpyrifos with liquid scintillation counting was used to assist in optimizing and characterizing the method, and GC-ECD and GC-NPD were used for analysis of 24 selected pesticides. The method was validated using tomato, apple and frozen green bean matrices spiked at 0.05, 0.5, and 5 mg/kg. For 22 of the analytes, recoveries averaged 93% for all three commodities over the validation range with a relative standard deviation of 10% (n = 1182). Lower recoveries of dichlorvos were obtained with the method and iprodione determination was compromised in the green beans by an interfering peak. Typical limits of detection were 0.005-0.01 mg/kg with the method.

Information on the variability of residues in individual fruits and vegetables is required to estimate the acute dietary exposure to pesticides. The distribution of residues in apples, kiwi fruits, potatoes and butter beans was studied in field experiments representing commercial farming practice. No correlation was found between the residue concentration or surface residue and the mass of apples. The relative frequency distributions of residues in crop units were continuous and skew positive. The log-normal transformation did not result in a normal distribution in any of the trials. Consequently, 299, 120 and 59 random samples should be analysed to estimate 99th, 97.5th and 95th percentile of the residues at 95% confidence level. The distribution of residues is not significantly influenced by the mean residue, pre-harvest interval, chemical and physical properties of the active ingredient, formulation of pesticide or, on top fruit, the foliar application method. However, the residue distribution is likely to be influenced by the size, shape and density of the plants, and mode of application of pesticides. The variability factor should be defined as the ratio of the highest value at a specified percentile of residues occurring in unit crops and the population mean. Generic variability factors may be determined for various groups of commodities. Variability factors of 5 and 9 are recommended for medium size fruits, and potato following granular application of pesticides, respectively.

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.

The homogeneity of analytical samples and the stability of pesticides during the sample processing of oranges and tomatoes were evaluated. The mean concentrations of 14C-labeled chlorpyrifos in analytical portions (subsamples) after processing show that homogeneity is dependent on sample type as well as the processing procedure. The homogeneity of analytical samples of tomatoes processed cryogenically was much better than those processed at ambient temperature. For tomatoes, the minimum analytical portion masses required for between-analytical portion variation of < 0.3 Ho were 110 and 5 g for processing at ambient and cryogenic temperatures, respectively. Results for orange showed that analytical portion sizes of 5 g provided sufficient homogeneity from both sample processing procedures. Assessments of pesticide stability demonstrated that most were relatively stable during processing at either ambient or cryogenic temperatures. However, some pesticides, including dichlofluanid, chlorothalonil, tolylfluanid, and dicloran, appeared to suffer much greater losses (>20%) during processing at ambient temperature. For these analytes, loss is interpreted as chemical degradation.