Guidance on the Organisation of Informal Food Authenticity Surveys

FA0173 February 2020

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Guidance on the Organisation of Informal Food Authenticity Surveys

1 Introduction

During the 2013 horsemeat incidence, the food industry carried out 29,600 analyses on its products

and ingredients in order to rebuild consumer confidence. Concerns were raised as to effectiveness

of both the sampling and the methods of analysis used to detect horsemeat. This Guidance is in

response to the Authenticity Methods Working Group’s1 (AMWG) deliberations to one of the

recommendations - (No 4) of the Elliott Review2 on the “Integrity and Assurance of Food Supply

Networks” post-horsemeat incident. One of the sub-recommendations of the Elliott Report was that

Government should “facilitate the development of guidance on surveillance programmes to inform

national sampling programmes”. It also encompassed another sub-recommendation, which

requested that Government “facilitate work to standardise the approaches used by the laboratory

community testing for food authenticity”, which the AMWG interpreted as using “fit for purpose”

validated methodology.

The AMWG’s own recommendations on authenticity sampling were that more effort is needed to

ensure sampling is representative and appropriate to ensure that reliable analyses can be carried

out:

“We recommend that the Government’s authenticity programme:

i) Produces food authenticity-specific sampling guidance focussing on the strengths and

weaknesses of each approach and demonstration that sampling has been correctly undertaken.

ii) Prepares short ‘Explanatory Notes’ on authenticity sampling of specific commodities for use by

industry and enforcers. The AMWG should explore with, for example, the Royal Society of

Chemistry’s Analytical Methods Committee (RSC-AMC), options for preparing these notes.”

Given the number of commodities that potentially could be sampled, the latter recommendation was

felt to be too large a project to carry out effectively. Hence this guidance will focus on informal

authenticity sampling and design of a survey using ‘fit for purpose’ methodology.

2 Formal and Informal Sampling

2.1 Formal samples

Formal samples are those taken by a local authority authorised officer (usually a Trading Standards

or Environmental Health Officer) as directed by the Food Safety Act 1990. A formal sample is a legal

requirement to take a prosecution. Each sample must be divided into three parts, where one part is

sent to an appointed public analyst, although single part samples may also be taken where it is

considered division of a sample is not appropriate. The procedures that have to be followed in taking

a formal sample and analysing it, are laid down in The Food Safety (Sampling and Qualifications)

(England) Regulations 20133 (and devolved administration equivalents), and there is a Food

Analytical Methods Committee

Food and Feed Authenticity Expert Working Group

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Standards Agency Code of Practice4 on formal sampling. Formal sampling for enforcement

purposes is not covered by this guidance.

2.2 Informal samples

The aim of this guidance is to assist any organisation whether it be governmental, local authority,

trade or consumer organisations, or even individual companies in the undertaking of informal

authenticity surveys or programme of surveys. Hence, an informal sample is any sample taken for

information or research and not for the purpose of enforcement. Sampling for surveys is accordingly

regarded as informal sampling. Informal samples need not be taken by an authorised enforcement

officer or sent to an approved public analyst. However, the results of informal market surveillance

may be used to inform policy, to guide future enforcement action, or to direct further research. It,

therefore, remains important to ensure that informal samples are collected in accordance with an

agreed sampling plan, carefully documented, stored appropriately and analysed by a competent

laboratory. The aim of this guidance is to ensure that the correct procedures are carried out in

sampling, analysis and interpretation including any sampling and analysis uncertainty, so that

confidence can be placed in the results of informal surveys and the correct decisions made on any

survey follow-up.

3 Qualitative and Quantitative Surveys

A key decision in planning an authenticity survey is whether the survey is to provide quantitative

or qualitative results, as this has important implications for planning, survey size and consequent

costs. In qualitative or quantitative surveys, either qualitative or quantitative analytical methods

may be used.

For this guidance, a survey is considered quantitative if it is intended to give an accurate estimate of

the proportion of adulterated foodstuffs in a particular sector, location or product range. The results

may be used to deduce the prevalence of adulteration or other authenticity issues in the relevant

market segment.

A qualitative survey seeks only to establish whether adulteration exists in a particular market

segment and to establish the nature of adulteration. In general, such a survey will be targeted at high

risk products, locations or supply chains. In consequence of this selective sampling, which aims to

increase the chance of detecting adulteration if it is present, the proportion of adulterated samples

found in the survey cannot generally be interpreted as prevalence in the marketplace.

4 Planning an Authenticity Survey

In addition to the enforcement of the many requirements of food labelling and standards, the

prevention of food fraud for the protection of both consumers and honest food producers, retailers

and caterers is a major driver in undertaking authenticity surveys. In order to ensure that the results

of any survey are sufficiently accurate and meaningful, planning of the survey in terms of sampling,

analysis and interpretation of the results, is an important and essential stage in any survey.

4.1 Purpose of the survey and the authenticity issue

It must be clear what the survey is trying to achieve, and the authenticity issue being investigated.

Table 1 below outlines the main authenticity issues with some examples. However, it should be

noted that issues are often related and hence should not be considered in isolation, e.g.

adulteration/substitution may also involve tariff fraud.

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What is the authenticity issue?

Labelling requirements (name of food, legal names, ingredients list, QUID (Quantitative Ingredient Declaration), drained weights, allergen declarations), Legal Names (specific vertical legislation - meat products, chocolate, honey, marketing standards etc)

Adulteration (added water - specific requirements for poultrymeat, and cuts of meat), Substitution (with cheaper ingredients - replacing named species or varieties Basmati rice, durum wheat)), Counterfeiting (brands),

Falsifying geographical origin (general requirement of FIR, and specific requirements - meat, poultry and fish, PDOs (Protected Denomination Of Origin), PGIs (Protected Geographical Indication)), Falsifying of Production Origin (GMOs (Genetically Modified Organisms), irradiated ingredients, previously frozen, QFF (Quick Frozen Foods), organic, halal).

Avoiding hygiene requirements (recycling Category 3 by-products, illegal slaughterhouses or cutting plants, illegal animal imports),

Subsidy or tariff fraud (export refunds, import tariffs)

Table 1 Summary of Authenticity Issues

Alternatively, if reliable intelligence or information has been received about a specific authenticity

issue, and a survey is being organised to determine the extent of this authenticity issue either locally

or nationally, then the above considerations should be used to check the legal status of the issue.

4.2 Is there a “fit for purpose” method?

Having clarified the authenticity issue, a survey can only be organised if there are appropriate

sampling and “fit for purpose” methods available. The investigation of food authenticity issues

requires a wide variety of analytical methods ranging from, for example, basic compositional analysis

(nitrogen, fat, ash etc.), immunological methods, DNA methods (both qualitative and quantitative),

mass spectroscopy (isotopic analysis, proteomics), NMR (SNIF-NMR, metabolomics), vibrational

spectroscopy (NIR, UV, multispectral analysis), microscopy, etc. An extensive list of methods

associated with specific authenticity issues can be found in the AMWG’s response to the Elliott

Report1. The term “fit for purpose” method is also fully discussed in this publication1 and a summary

can also be found on the Food Authenticity Network website5. The most important aspect is that the

method has been validated, so that its performance criteria are known and have been verified. There

are also other considerations mentioned; for example, that a laboratory has ISO 17025 accreditation

(now applies to sampling), and uses a method which is also ISO17025 accredited or if it is a new

method not yet accredited but has suitable quality assurance systems in place6. This would require

participation in a proficiency test scheme (e.g. FAPAS), and that the laboratory uses certified

reference materials when these are available. Table 2 gives the performance criteria requirements

for the methods that are used for surveys. However, the problems of reliance on Z scores from

proficiency testing have been discussed in the RSC Technical Brief No 687, and the use of fitness

for purpose uncertainty gets around most of these problems. In exceptional cases, reference to a

professional specialist outside this system is permitted.

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Qualitative Method Limit of detection, information on false positive/negatives

Quantitative Method

Limit of detection and quantification, accuracy, estimation of measurement of uncertainty MoU if possible, including the within laboratory variation (repeatability), and between laboratory variation

(reproducibility), recovery, linearity, and selectivity6.

Table 2 Performance Criteria of Methods

4.3 Information about the Food Products being Surveyed

Having chosen the subject of a survey, it is important to have information about the market

situation of the food product/s, so that an appropriate sampling plan can be drawn up. Factors

to take into consideration:

Are samples being taken on a national basis or does the survey involved taking samples

outside the UK?

Is the survey sampling finished products or ingredients, which need to be collected in

processing plants, ports of entry etc?

Is the survey looking at the entire retail market or only a part of it, and does this include

wholesale sales, on-line sales etc.?

Is the survey looking at the catering sector, which includes restaurant/catering chains,

takeaways including fish and chip shops, as well as wholesale, or a specific sector of

catering?

Is the survey looking at a whole group of products e.g. meat products or just one small

group or an individual food?

What is the market share of the product or group of products in question, and should the

sampling plan be adjusted accordingly?

5 Drawing up a Sampling Plan

Having established the purpose of the survey, the method of analysis that will be used, and the type

of samples and where in the food chain the samples will be collected, a sampling plan can be

constructed. There several considerations to be take into account:

i) Is the material to be sampled homogenous or heterogeneous, taking due consideration of the

particle size of the material, as appropriate – this will influence how sampling is undertaken to

ensure the sample is sufficiently representative, and if relevant, generates an acceptable level of

measurement uncertainty . For example, a spirit drink is most likely homogenous, a nut powder

used to make a curry from a refillable container in a takeaway may be heterogenous

ii) How many samples need to be taken so that the samples are sufficiently representative of the

batch or production lot in question?

iii) How many samples need to be taken so that they are sufficiently representative of the market

being studied?

These questions need to be considered in the light of the budget available for the survey as the cost

of collection of the samples and their analysis, especially as many of the authenticity methods are

expensive. In addition, there is also the issue is whether the survey is designed to be representative

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of the whole market of the food in question, or whether the survey is targeted to a specific food in a

specific part of the food chain. In the latter case, there are usually much fewer samples involved.

5.1 Choice of sampling points and products

The choice of sampling points, products, product types, sampling times etc depends in the first

instance on whether the survey is intended to be quantitative or qualitative. (Here, a ‘sampling point’

is typically a particular site, such as a manufacturer or retail outlet).

5.2 Planning for Quantitative surveys

Where a survey is intended to be quantitative (see Section 3), it is essential that sampling is

sufficiently representative of the target market segment and properly randomised across the

complete population of possible sampling points, products and types. It can also be important that

sampling and subsequent analysis of the results takes account of the volume of product passing

through each sampling point.

There is a broad range of strategies for choosing sampling points for quantitative surveys. These

include, for example:

- Simple random sampling, in which sampling points are chosen at random from the complete

population of possible sites and product ranges. This is simple to plan but usually results in

large variability.

- Stratified sampling, in which the possible population is first divided into groups known as

‘strata’ (such as product types or outlet type) and a random sample chosen from each

‘stratum’. This can reduce variability in results compared to simple random sampling, but

generally requires prior knowledge of possible groups and group sizes.

- Cluster sampling, in which ‘clusters’ of sampling locations are chosen at random from within

a previous random selection of possible (usually geographical) regions. For example, a

random set of retail outlets might be chosen in each of a number of towns, also chosen at

random from a larger number. This is typically more variable than stratified sampling if the

regions are very different, but can substantially reduce transport costs and overall survey

time.

All of these have advantages and disadvantages, which should be discussed with the statistician in

order to select the most appropriate strategy for the survey in question. In addition, some require

specialist data analysis to give accurate prevalence. Costs will also depend both on the sampling

strategy and on the number of samples required for an accurate estimate of prevalence. For

quantitative surveys, therefore, it is essential that a suitably qualified statistician, with experience of

survey design, is involved at the planning stage as well as in any subsequent data analysis.

5.3 Planning for Qualitative surveys

Qualitative surveys are intended to give an indication of the existence and types of authenticity

issues in a particular market segment or (for example) geographical area. Efficient sampling plans

for qualitative surveys can therefore aim to maximise the chance of detecting adulteration, or

maximise coverage, rather than focusing on the sufficiently representative sampling required for

quantitative evaluation.

Maximising the chance of detecting adulteration requires selection based on perceived or known risk

of adulteration. Higher risk of adulteration is typically associated with one or more of:

- high added value of adulteration (for example, adulteration of virgin olive oil with low cost oils);

- ease of adulteration;

- limited or low regulatory oversight at the point of production;

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- long supply chain of ingredients

- history of adulteration either in UK or elsewhere

Where a qualitative survey aims at maximising coverage, samples are taken from as many product

types, import streams, outlets etc. as reasonably practical (see Section 5.5). Usually, a small number

of individual samples should be taken from each location; two or three is often sufficient to gain

insight into the incidence and nature of adulteration.

5.4 Taking a sufficiently representative sample from each sampling point

The term “representative” sample has its problems, and the number of samples taken is almost

always a compromise between what is regarded as adequate statistically, and what is affordable.

Therefore, a “sufficiently representative” sample is often referred to as an “appropriate” sample8. In

contrast to chemical and microbiological contamination, authenticity issues such as adulteration and

substitution tend to be more homogeneous in a batch or production lot of food (provided

manufacturing practice is carried out “properly”). Therefore, in most cases dealing with a qualitative

method, one sample should be appropriate for a batch of production to indicate whether there is a

problem with that batch. In the case of a quantitative method, if a small proportion of the batches

(e.g. 10%) have a second duplicate sample taken, then it becomes possible to estimate the

measurement uncertainty from the sampling9. There may be exceptions to this situation, for example

if the substitution is accidental rather than deliberate, or random, such as in catering, and the

sampling plan should be adjusted accordingly.

5.5 Market coverage

Market information about the food/s that are the subject of the study has already been considered in

Section 4.3. Therefore, the number of samples needs to be decided to cover the chosen market. Is

the study a targeted study, and only a few samples will be taken? What are all the variables and

categories in this study?

- the areas of the country to be covered,

- the types of outlet where samples are collected – large retailers, smaller retailers (corner shops),

wholesalers, catering wholesalers, restaurants, takeaways (including fish and chip shops)

- the types of products e.g. as many types of meat products as possible or just one group, and state

of preservation – raw, cooked, fresh, frozen, canned etc.

- the timeframe of the survey – is it “one off”, or over several seasons etc.

6 Organisation of the Survey

Attention to the following considerations will help to ensure a survey runs smoothly:

- Choice of laboratory/ies – experience, performance data, laboratory capacity, turnaround times,

ability to interpret results in a legal context (Centres of Expertise Laboratories listed on the

www.foodauthenticity.uk website may be a good starting point if a specialist laboratory is

required).

- Choice of collectors – if possible, Trading Standards Officers/Environmental Health Officers

should be used because they have experience of businesses where samples are collected, and

experience in sampling both packaged and loose foods. If other collectors are used, then the

organisation should be accredited and participate in a PT sampling scheme10.

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- Sample collection form – sampling codes, information of place and time of collection – address,

batch codes, labelling information on the packaging or documents etc.

- Sample handling – give specific instructions in how to take samples. Do collectors need training

in handling unpackaged (loose) samples e.g. when collecting for DNA analysis? Have the

collectors or organisers the correct sampling equipment, containers and storage for the samples.

If the sample is pre-packaged, then it is preferable to collect the sample in its original packaging.

Loose foods from retail and catering require special handling to avoid cross contamination. Labels

of sampling codes should preferable be placed inside a container or bag (but still visible) in the

same sample (but not in contact with it) to ensure they stay with the sample all the way to the

laboratory.

- Has suitable transport to laboratories been arranged, and is chilled or frozen transport required?

- Details of when samples should be collected and the timeframe – coordinated with the laboratory

- An agreed format for recording and transferring survey data, both from sample collection and data

analysis.

- Agreed QA procedures on the test methods being used.

- A provisional plan for data analysis, setting out expected methods of statistical analysis and

summary.

- Contact details of the survey coordinator (if there is one) to answer any queries from the collectors

or laboratory.

7 Assessment of Results of the Analyses

The analyst undertaking the laboratory analyses should have demonstrable experience in

interpreting and reporting the results of the samples. However, it helps if the survey organiser

understands some of the uncertainty issues around the method’s use and can question if it is felt

that there is a problem with some of the results. Each type of analysis has its own specific issues.

7.1 Results from qualitative methods

Qualitative methods, such as some DNA identification methods, some immunoassays, or protein

identification, positively identify a single species of animal, fish or plant variety. Even with these

methods, there is a limit of detection (LoD) below which the test does not respond, and there may

be issues of specificity as well, if other less well-known species or varieties react with the test in a

similar way i.e. false positive (there may also be false negatives).

The LoD is often defined as the lowest amount of target analyte which can be reliably detected on

at least 95% of occasions. Statistically, a very high level of replication must be tested at different

concentrations in order to provide a 95% confidence of detecting a target 11. This may not always be

feasible, so a more pragmatic approach may need to be adopted in order to determine the LoD. This

could be achieved, for example, by a serial dilution series of the sample where each dilution point

(concentration level) is represented by at least 10 replicates. The lowest concentration where all 10

replicates exhibit a positive response will be the estimated LoD.

Results of qualitative test methods can be counted and tabulated to give a proportion of adulterated

products found in the study, but do not provide information on the amount of an adulterant beyond

the fact that it was present at a detectable level.

7.2 Results from quantitative methods

Interpretation of results is complex and should not be undertaken casually. The advice of the Public

Analyst is vital to this part of the process as they will have the necessary understanding of the

technicalities of the methods used.

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7.2.1 Results from quantitative chemical methods

These methods give a concentration or a relative proportion of an analyte, and often this will be

expressed relative to a statutory limit for the analyte (if one exists). The results are typically obtained

by comparing the instrument response to a standard curve (ideally matrix matched), which have

either been prepared from known concentrations of the analyte or from a dilution series of a standard.

There is a limit of detection of the method, below which it is possible that the analyte cannot be

detected, and a limit of quantification (LoQ), which is the lowest concentration of analyte that can be

reliably and reproducibly quantified. As a ‘rough guide the LoQ is approximately the LoD x 10.

Furthermore, all quantitative results have a measurement of uncertainty (including sampling uncertainty)

associated with them, which should be taken into account (a requirement of ISO 17025) when comparing the

results with statutory limits. Results, which are close to the statutory limit taking into account their uncertainty,

may warrant further investigation before a decision to move to formal samples is taken.

7.2.2 Results from quantitative DNA methods

The main difference between a chemical method and a molecular biology method is that the

quantitative DNA method measures the amount of a specific target DNA sequence (e.g. pork, horse,

common wheat), often relative to the total amount of background DNA present (e.g. the total mammalian

or taxon plant DNA present). This is often facilitated by use of a of an endogenous or ‘normalising’ DNA

sequence. Such quantitative estimation is typically performed using quantitative real-time PCR

(qPCR). Using this approach, it is often possible to measure and then calculate the level of admixture

present in a sample (see example in Figure 1 below of common wheat adulteration of durum wheat

pasta).

PCR can possibly introduce more variation than a chemical method because it can be affected by

other ingredients in the product, as can the extraction of the DNA. The amount of starting DNA may

vary with different cuts of meat for example. When an efficient DNA extraction method is used,

coupled with a quality assurance process, such matrix differences between sample types can often

be reduced. Usually two independent calibration curves are used for quantification prepared using a

range of reference materials of known analyte concentrations, or from a serial dilution derived from

one standard or reference material. An example of calibration curves generated from a single

reference material of known composition is the ‘relative quantification’ of T.aestivum (common or

bread wheat) present in T. durum pastas or semolinas. The amount of T.aestivum present in pasta,

semolina and couscous samples can be determined by quantitative real-time PCR (qPCR) using two

DNA targets, an intron specific D-genome specific DNA sequence and a normalising adjacent DNA

sequence present in all three genomes (A, B and D)12 by determining the ‘relative copy number’ for

each target sequence and consequently the percentage of T. aestivum present to be calculated

using the ratio of the two relative copy numbers determined from the two calibration curves.

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Figure 1 Common Wheat (D Genome) Adulteration of Durum Wheat

The calculation is uncomplicated when a single copy of an inserted DNA sequence (i.e. as in some

but not all GMOs) is quantified against a single copy of an endogenous gene. However, when T.

aestivum is present in pasta or a T. durum product, the calculation is made more complicated by the

difference in ploidy levels between the two species.12

A more common example of quantitative DNA methods is that of GMO (Genetically Modified

Organism) analysis using real-time PCR. This approach typically measures an event specific GM

target of a particular species (e.g. RoundUp Ready Soya) and expresses this relative to the response

from an endogenous taxon specific marker (e.g. lectin). For GMOs the relative percentage GM

content measured on a DNA:DNA basis, can usually be directly related to the w/w ingredient level

of the original sample. Similar approaches for making quantitative estimates in other areas of food

analysis can also be made (e.g. quantitative meat species analysis), but the situation is further

complicated as there is often no direct way to relate the DNA:DNA measurement to the w/w

ingredient level without a number of assumptions being made. It should also be noted that

quantitative meat species determination using this approach is based upon DNA extracted from raw

meats and hence the results will also be expressed as % DNA on a raw meat basis. Extrapolation

of the DNA:DNA estimates to a m/m measurement i.e. % or total weight basis, is only valid in specific

instances and has to be fully validated first (e.g. FSA project FS12600113 on the collaborative trial

of the horse meat method). Often, a conversion factor is a necessity in these instances.

Many modern qPCR approaches use a dilution series derived from a single standard for construction

of a calibration curve, further minimising uncertainty due to using gravimetric preparations. In

general, quantitative DNA methods usually have quite low limits of detection (LoD) and quantification

(LoQ) e.g. a number of published assays (e.g. horse in beef or GMOs) quote having an LoD of 0.1%

(m/m).

Recent developments in quantitative molecular analyses should also be considered due to their

intrinsic accuracy and lower analytical uncertainty. For example, digital PCR can be used for

accurate single molecule detection and is thus suitable for accurate value assignment (e.g. for a

reference material), but the full utility of this new technology needs to be demonstrated following

method validation.

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Molecular biology approaches using DNA as the target analyte provide a number of benefits for

quantitation. These can help augment the results from proteomic approaches, which tend to be

less well developed for use for quantitation and can often be subject to selectivity issues and

differential peptide expression based on tissue type and age of an organism.

7.2.3 Results from multivariate analyses

There are many authenticity methods that rely on the use of multiple analyses or data sets on a

population (collection) of authentic samples. This data is then analysed chemometrically (usually by

principal component analysis (PCA)) to determine the components which best represent the

variability of the population. A 2D or 3D graph can be constructed using either 2 or 3 of the

components, and a boundary normally of a 95% confidence limit can then be drawn around the

population, which will determine the authenticity of an unknown sample. This multivariate approach

is widely used with spectroscopic techniques – from infra-red, nuclear magnetic resonance, to mass

spectroscopy usually combined with chromatographic separation techniques such as LC (liquid

chromatography) or GC (gas chromatography). These methods are commonly used for geographic

or processing origin, and even for variety or species determination. Figure 2 taken from a Food

Standards Agency survey14 on determining wild from farmed sea bass, illustrates this approach

where the two components F1 (56.3% of the total variability) F2 (17.4% of the total variability) are

derived from the analytical variables of % total oil, C18:2n-6, C20:4n-6, δ13 C oil, δ18 O oil, and δ15 N

Figure 1 Multivariate Analysis of Wild and Farmed Sea Bass and Survey Results

of the choline fraction of the oil. Where the blue and orange dots represent the farmed and wild

authentic samples data respectively, and it can be seen that there is some small overlap between

the 95% confidence boundaries of these two populations. The green dots are the survey results,

which show 4 survey samples are consistent with the farmed sea bass population at the 95%

confidence limits. Results which place the sample on the border of the population are usually given

the “benefit of the doubt”.

It can be seen from the example above that one authentic sample and two of the survey samples

are outside the boundary of the wild sea bass population. The uncertainty of a multivariate analysis

decreases the larger the population of authentic samples on which it is based. However, sometimes

there are authentic samples which do not conform with the model on which the multivariate analysis

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is based. In these cases, samples which fall outside the boundaries of population are usually

described as “not being consistent with X population”.

7.3 Summary reports and inference

Generally, summaries should be prepared by product type and geographical region where the latter

is relevant.

For quantitative surveys, tabulated proportions or averages should be accompanied by information

on any known limitations of the study and sampling methodology and on how these were minimised.

Summary data should also include information on possible bias and uncertainty in estimates of

incidence, prevalence etc.

For qualitative surveys, summary results may be tabulated and may show the proportion of samples

found to be adulterated within the study. However, the report must contain a clear disclaimer to the

effect that averages, or statements of proportion are limited to the samples collected in the study

and must not be interpreted as a proportion of all products on the market.

The Code of Practice for Statistics published by the Office for Statistics Regulation15 gives more

information on the collection and reporting of statistical information.

8. Follow-up of the Informal Survey

Once the results have been collated and verified, certain courses of action are available.

- If the results of the survey are being made public, for qualitative surveys any communication should

be clear that the results are not indicating prevalence of the authenticity issue in the market as a

whole, but in a specific sector or part of the market. Consideration on its significance taking into

account the sampling plan used, and a decision can be taken if the results merit further investigation

and possible follow-up survey/s.

- The approach taken for follow-up of each survey will depend on the policy need. Responsibility for

law enforcement sits with the FSA, who will work with Government departments, businesses, Local

Authorities and the National Food Crime Unit as appropriate.

9. Acknowledgement

This guidance document was funded by Defra’s Food Authenticity Programme

10. References. 1. AMWG’s Response to the Elliott Review Recommendation 4, March 2015.

http://www.gov.uk/government/publications/report-on-food-authenticity-testing-and-method-standardisation

2. Elliott Review into the Integrity and Assurance of Food Supply Networks: Final Report http://www.gov.uk/government/publications/elliott-review-into-the-integrity-and-assurance-of-food-supply-networks-final-report

3. The Food Safety (Sampling and Qualifications) (England) Regulations 2013 http://www.legislation.gov.uk/uksi/2013/264/made

4. Food Standards Agency Sampling Guidance Parts 1, 2, & 3, 2001

http://webarchive.nationalarchives.gov.uk/20100720141523/http://www.food.gov.uk/foodindust

ry/guidancenotes/foodguid/guidance/

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5. Summary Criteria for Analytical Laboratories “Fit for Purpose”. http://storage.ning.com/topology/rest/1.0/file/get/1030811?profile=original 6. Regulation (EU) 2017/625 of the European Parliament and of the Council of 15 March 2017 on

Official Controls- Annex III. OJ L137, 24.05.2017, p40 (2017/625) http://eur-lex.europa.eu/eli/reg/2017/625/oj

7. Fitness for Purpose: The Key Feature in Analytical Testing (TB 68) Analytical Methods, 2015,

7, 7404. http://pubs.rsc.org/en/results?artrefjournalname=anal.%20methods&artrefstartpage=7404&artrefvolumeyear=2015&fcategory=journal

8. Representative Sampling: Views from a Regulator and a Measurement Scientist. (TB 73)

Analytical Methods, 2016, 8, 4783

http://pubs.rsc.org/en/results?artrefjournalname=anal.%20methods&artrefstartpage=4783&artr

efvolumeyear=2016&fcategory=journal

9. Ramsey M.H., Ellison S. L. R., and Rostron P.(eds.) (2019) Eurachem/EUROLAB/

CITAC/Nordtest/ AMC Guide: Measurement uncertainty arising from sampling: a guide to

methods and approach, Second Edition, ISBN 978-0-948926-35-8

http://www.eurachem.org/index.php/publications/guides/musamp

10. Proficiency testing of sampling. (TB 78), July 2017, Anal. Methods, 2017, 9, 4110, DOI:

10.1039/c7ay90092a http://doi.org/10.1039/C7AY90092A

11. JRC Technical Report (2017) “Verification of analytical methods for GMO testing when

implementing interlaboratory validated methods” ISBN 978-92-79-77310-5, ISSN 1831-9424,

DOI: 10.2760/645114

12. G. Wiseman in “DNA Techniques to Verify Food Authenticity: Applications in Food Fraud”

(2019), Editors: M. Burns, L. Foster and M. Walker. RSC Series: Food Chemistry, Function

and Analysis. ISBN: 978-1-78801-178-5. ISSN: 2398-0656

13. International collaborative trial of a Real-Time PCR method for the Relative Quantitation of Horse DNA. Defra Project FS126001 http://www.food.gov.uk/research/research-projects/international-collaborative-trial-of-a-real-time-pcr-method-for-the-relative-quantitation-of-horse-dna

14. FSA Survey on the Production Method and Geographic Origin of Fish. FSIS 02/07

http://webarchive.nationalarchives.gov.uk/20100721055907/http://www.food.gov.uk/multimedia

/pdfs/farmedwildfish.pdf

15. Code of Practice for Statistics. UK Statistics Authority.

https://www.statisticsauthority.gov.uk/code-of-practice/