Commission Implementing Regulation (EU) 2023/2782 of 14 December 2023 laying down the methods of sampling and analysis for the control of the levels of mycotoxins in food and repealing Regulation (EC) No 401/2006

For confirmatory methods the following performance criteria apply:

Recovery: the average recovery should be between 70 and 120 %.

The average recovery is the average value from replicates obtained during validation when determining the precision parameters RSDr and RSDwR. The criterion applies to all concentrations and all individual toxins, with the exception of ergot alkaloids.

For ergot alkaloids the criterion applies to the sum of each epimer-pair.

In exceptional cases, average recoveries outside the above range can be acceptable but shall lie within 50-130 %, and only when the precision criteria for RSDr and RSDwR are met.

Precision

RSDr shall be ≤ 20 %.

RSDwR shall be ≤ 20 %.

RSDR should be ≤ 25 %.

These criteria apply to all concentrations.

In case a laboratory provides the evidence that the RSDwR criterion is complied with, there is no need to provide that evidence for the RSDr criterion as compliance with the RSDwR guarantees compliance with the RSDr criterion.

In case the maximum level applies to a sum of toxins, then the criteria for precision apply to both the sum and the individual toxins. For ergot alkaloids, the criteria for individual toxins apply to the sum of each epimer pair.

Limit of quantification

When a specific requirement for the LOQ of a mycotoxin has been set in the Table 1 below, the method shall have an LOQ at or below this value.

In all other cases, the following applies:

LOQ: hall be ≤ 0,5ML and should preferably be lower (≤ 0,2ML).

In case the maximum level applies to a sum of toxins, then the LOQ of the individual toxins shall be ≤ 0,5*ML/n, with n being the number of toxins included in the ML definition.

Identification

For identification, the criteria as laid down in the Guidance document on identification of mycotoxins and plant toxins in food and feed (¹⁵) shall be applied.

When additional analytes are added to the scope of an existing confirmatory method, a full validation is required to demonstrate the suitability of the method.

If the confirmatory method is known or expected to be applicable to other commodities, the validity to these other commodities shall be verified. As long as the new commodity belongs to a commodity group (see Table 2 in this Annex) for which an initial validation has already been performed, a limited additional validation is sufficient.

This section applies to bioanalytical methods based on immuno-recognition or receptor binding (such as ELISA, dip-sticks, lateral flow devices, immuno-sensors) and physicochemical methods based on chromatography or direct detection by mass spectrometry (e.g. ambient MS). Other methods (e.g. thin layer chromatography) are not excluded provided the signals generated relate directly to the mycotoxins of interest and allow that the principle described hereunder is applicable.

The specific requirements apply to methods of which the result of the measurement is a numerical value, for example a (relative) response from a dip-stick reader, a signal from LC-MS, etc., and that normal statistics apply.

The requirements do not apply to methods that do not give numerical values (e.g. only a line that is present or absent), which require different validation approaches. Specific requirements for these methods are provided in point 4.2.3.

This document describes procedures for the validation of screening methods by means of an inter-laboratory validation, the verification of the performance of a method validated by means of an inter-laboratory exercise and the single-laboratory validation of a screening method.

The aim of the validation is to demonstrate the fitness of purpose of the screening method. This is done by determination of the cut-off value and determination of the false negative and false suspect rate. In these two parameters performance characteristics such as detection capability, selectivity, and precision are embedded.

Screening methods may be validated by inter-laboratory or by single laboratory validation. If inter-laboratory validation data is already available for a certain mycotoxin/matrix/STC combination, a verification of method performance is sufficient in a laboratory implementing the method.

The validation shall be performed for every individual mycotoxin in the scope. In case of bio-analytical methods that give a combined response for a certain mycotoxin group (e.g. aflatoxins B1, B2, G1 & G2; fumonisins B1 & B2), applicability shall be demonstrated and limitations of the test mentioned in the scope of the method. Undesired cross-reactivity (e.g. DON-3-glycoside, 3- or 15-acetyl-DON for immuno-based methods for DON) is not considered to increase the false negative rate of the target mycotoxins, but may increase the false suspect rate. This unwanted increasing shall be diminished by confirmatory analysis for unambiguous identification and quantification of the mycotoxins.

An initial validation shall be performed for each commodity, or, when the method is known to be applicable to multiple commodities, for each commodity group. In the latter case, one representative and relevant commodity shall be selected from that group (see Table 2).

The minimum number of different samples required for validation is 20 homogeneous negative control samples and 20 homogeneous positive control samples that contain the mycotoxin at the STC, analysed under intermediate precision (RSDRi) conditions spread over 5 different days. Additional sets of 20 samples containing the mycotoxin at other levels may be added to the validation set to gain insight as to what extent the method can distinguish between different mycotoxin concentrations.

For each STC to be used in routine application, a validation shall be performed.

Validation through collaborative trials shall be done in accordance with ISO 5725:1994 or the IUPAC International Harmonised Protocol or other internationally recognised protocol on collaborative trials which requires inclusion of valid data from at least eight different laboratories. The only other difference compared to single laboratory validations shall be that the ≥ 20 samples per commodity/level may be evenly divided over the participating laboratories, with a minimum of two samples per laboratory.

The (relative) responses for the negative control and positive control samples shall be taken as basis for the calculation of the required parameters.

For screening methods with a response proportional with the mycotoxin concentration the following applies:

Cut-off value = RSTC – t-value0,05 SDSTC*

RSTC = mean response of the positive control samples (at STC)

t-value: = one tailed t-value for a rate of false negative results of 5 % (see Table 3)

SDSTC = standard deviation

Similarly, for screening methods with a response inversely proportional with the mycotoxin concentration, the cut-off value is determined as:

Cut-off value = RSTC + t-value0,05 SDSTC*

By using this specific t-value for determining the cut-off value, the rate of false negative results is by default set at 5 %.

Results from the negative control samples are used to estimate the corresponding rate of false suspect results. The t-value is calculated corresponding to the event that a result of a negative control sample is above the cut-off value, thus erroneously classified as suspect.

t-value = (cut-off value – meanblank)/SDblank

for screening methods with a response proportional with the mycotoxin concentration

or

t-value = (meanblank – cut-off value)/SDblank

for screening methods with a response inversely proportional with the mycotoxin concentration.

From the obtained t-value, based on the degrees of freedom calculated from the number of experiments, the probability of false suspect samples for a one tailed distribution can either be calculated (e.g. spread sheet function ‘TDIST’) or taken from a table for t-distribution (see Table 3).

The corresponding value of the one tailed t-distribution specifies the rate of false suspect results.

This concept is described in detail with an example in Analytical and Bioanalytical Chemistry DOI 10.1007/s00216 -013-6922-1.

When additional analytes are added to the scope of an existing screening method, a full validation shall be required to demonstrate the suitability of the method.

If the screening method is known or expected to be applicable to other commodities, the validity to these other commodities shall be verified. As long as the new commodity belongs to a commodity group (see Table 2 in this Annex) for which an initial validation has already been performed, a limited additional validation is sufficient. For this, a minimum of 10 homogeneous negative control and 10 homogeneous positive control (at STC) samples shall be analysed under intermediate precision conditions. The positive control samples shall all be above the cut-off value. In case this criterion is not met, a full validation is required.

For screening methods that have already been successfully validated through a collaborative laboratory trial, the method performance shall be verified. For this a minimum of 6 negative control and 6 positive control (at STC) samples shall be analysed. The positive control samples shall all be above the cut-off value. In case this criterion is not met, the laboratory has to perform a root-cause analysis to identify why it cannot meet the specification as obtained in the collaborative trial. Only after taking corrective action, it shall re-verify the method performance in its laboratory. In case the laboratory is not capable to verify the results from the collaborative trial, it will need to determine its own cut-off value in a complete single laboratory validation.

After initial validation, additional validation data are acquired by including at least two positive control samples in each batch of samples screened. One positive control sample shall be a known sample (e.g. one used during initial validation), the other shall be a different commodity from the same commodity group (in case only one commodity is analysed, a different sample of that commodity is used instead). Inclusion of a negative control sample is optional. The results obtained for the two positive control samples are added to the existing validation set.

At least once a year the cut-off value is re-determined and the validity of the method is re-assessed (re-evaluation of the available QA/QC data obtained in the last year). The continuous method verification serves several purposes, including:

— quality control for the batch of samples screened;

— providing information on robustness of the method at conditions in the laboratory that applies the method;

— justification of applicability of the method to different commodities;

— allowing to adjust cut-off values in case of gradual drifts over time.

The validation report shall contain:

— a statement on the STC;

— a statement on the determined cut-off value; Note: The cut-off value shall have the same number of significant figures as the STC. Numerical values used to calculate the cut-off value need at least one more significant figure than the STC.

— a statement on calculated false suspected rate;

— a statement on how the false suspected rate was generated. Note: The statement on the calculated false suspected rate indicates if the method is fit-for-purpose as it indicates the number of blank (or low level contamination) samples that will be subject to verification. Table 2 Commodity groups for the validation of confirmatory and screening methods Commodity groups Commodity categories Typical representative commodities included in the category High water content Fruit Juices Alcoholic beverages Root and tuber vegetables Cereal or fruit based purees Apple juice, grape juice Wine, beer, cider Fresh ginger, herbal infusions (liquid) Purees intended for infants and small children High oil content Tree nuts Oil seeds and products thereof Oily fruits and products thereof Walnuts, hazelnuts, chestnuts rapeseed, sunflower, cottonseeds, soybeans, peanuts, sesame seeds etc. Oils and pastes (e.g. peanut butter, tahina) High starch and/or protein content and low water and fat content Cereal grain and products thereof Dietary products Wheat, rye, barley, maize, rice, oats Wholemeal bread, white bread, crackers, breakfast cereals, pasta Dried powders for the preparation of food for infants and small children High acid content and high water content (¹) Citrus products ‘Difficult or unique commodities’ (2)

Cocoa beans and products thereof, copra and products thereof, coffee, tea (dried product) Spices, liquorice root, herbal infusions (dried product), food supplements, pollen, and pollen products High sugar low water content Dried fruits Figs, raisins, currants, sultanas Milk and milk products Milk Cheese Dairy products (e.g. milk powder) Cow, goat and buffalo milk Cow, goat cheese Yogurt, cream Meat (tissue) Edible offals Muscle, processed meat products Kidney, liver ham (¹) If a buffer is used to stabilise the pH changes in the extraction step, then this commodity group can be merged into one commodity group ‘High water content’. (2) ‘Difficult or unique commodities’ needs only to be fully validated if they are frequently analysed. If they are only analysed occasionally, validation may be reduced to just checking the reporting levels using spiked blank extracts. Table 3 One tailed t-value for a false negative rate of 5 % Degrees of Freedom Number of replicates t-value (5 %) 10 11 1,812 11 12 1,796 12 13 1,782 13 14 1,771 14 15 1,761 15 16 1,753 16 17 1,746 17 18 1,74 18 19 1,734 19 20 1,729 20 21 1,725 21 22 1,721 22 23 1,717 23 24 1,714 24 25 1,711 25 26 1,708 26 27 1,706 27 28 1,703 28 29 1,701 29 30 1,699 30 31 1,697 40 41 1,684 60 61 1,671 120 121 1,658 ∞ ∞ 1,645

The development of validation guidelines for binary test methods is currently carried out by various standardisation bodies (e.g. AOAC, ISO). AOAC has drafted a guideline on the validation of binary test methods. This document can be regarded as the current state of the art in the field of validation of binary test methods. Therefore, methods that give binary results (e.g. visual inspection of dip-stick tests) should be validated according to AOAC International Guidelines for Validation of Qualitative Binary Chemistry Methods (¹⁶).

However, other recognised validation guidelines can be used such as the approach provided for in ISO/TS 23758:2021 | IDF/RM 251 Guidelines for the validation of qualitative screening methods for the detection of residues of veterinary drugs in milk and milk products.

Ergot sclerotia in cereals shall be determined by visual (macroscopic/microscopic) identification of the ergot sclerotia and ergot sclerotia fragments. Quantification shall be done by weighing the amount of identified ergot sclerotia and ergot sclerotia fragments with a particle size > 0,5 mm.

4.3.   Estimation of measurement uncertainty, recovery calculation and reporting of results (¹⁷)

The analytical result shall be reported as follows:

(a) Corrected for recovery, where appropriate and relevant, and when corrected it shall be stated. The recovery rate is to be quoted unless intrinsic correction for bias is part of the procedure. The correction for recovery is not necessary in case the recovery rate is between 90-110 %.

(b) As x +/– U whereby x is the analytical result and U is the expanded analytical measurement uncertainty, using a coverage factor of 2 which gives a level of confidence of approximately 95 %.

As a possibility a default expanded measurement uncertainty of 50 % may be reported, provided that the laboratory meets all precision requirements specified in point 4.2. An individual laboratory can demonstrate that by achieving the criteria for the repeatability (RSDr) and the within-laboratory reproducibility (RSDwR), supplemented by successful participation in proficiency testing programs (unless no suitable proficiency testing program is available), as a mean z-score of |z| ≤ 2 demonstrates that the required reproducibility (RSDR) is met (based on a target standard deviation of 25 %).

In case the maximum level has been set for the sum of toxins (e.g. aflatoxins, T-2/HT-2-toxin, fumonisins, ergot alkaloids), the analytical results of all individual toxins shall be reported. For ergot alkaloids, it is also allowed to report the sum of each of the six epimer pairs instead of the 12 individual epimers.

Recovery correction, if applicable, shall be done for each of the individual toxins before summation of the concentrations. For ergot alkaloids, the correction can also be done based on the recovery obtained for each of the epimer pairs.

For compliance verification with the sum-ML, a lower-bound approach shall be applied which means that results for individual toxins that are <LOQ shall be replaced by zero for the calculation of the sum.

The present interpretation rules of the analytical result in view of acceptance or rejection of the lot apply to the analytical result obtained on the sample for official control. In case of analysis for defense or referee purposes, the national rules apply. In particular, if

the analytical result of the official control sample indicates a non-compliance beyond reasonable doubt, taking into account the expanded measurement uncertainty and

the analytical result of the defense sample indicates a non-compliance but not beyond reasonable doubt with a larger expanded measurement uncertainty than the one of the official control,

then the analytical result of the defense sample cannot supersede the non-compliance established for the official control sample.

The result of the screening shall be expressed as compliant or suspected to be non-compliant.

‘Suspected to be non-compliant’ means the sample exceeds the cut-off value and may contain the mycotoxin at a level higher than the STC. Any suspect result triggers a confirmatory analysis for unambiguous identification and quantification of the mycotoxin.

‘Compliant’ means that the mycotoxin content in the sample is < STC with a level of confidence of 95 % (i.e. there is a 5 % chance that samples will be incorrectly reported as negative). The analytical result is reported as ‘< level of STC’ with the level of STC specified.

4.4.   Laboratory quality standards

A laboratory shall comply with the provisions of Article 37(4) and (5) of Regulation (EU) 2017/625.