Microbiology of the food chain - Estimation of measurement uncertainty for quantitative determinations (ISO 19036:2019)

This document specifies requirements and gives guidance for the estimation and expression of measurement uncertainty (MU) associated with quantitative results in microbiology of the food chain.
It is applicable to the quantitative analysis of:
— products intended for human consumption or the feeding of animals;
— environmental samples in the area of food production and food handling;
— samples at the stage of primary production.
The quantitative analysis is typically carried out by enumeration of microorganisms using a colony-count technique. This document is also generally applicable to other quantitative analyses, including:
— most probable number (MPN) techniques;
— instrumental methods, such as impediometry, adenosine triphosphate (ATP) and flow cytometry;
— molecular methods, such as methods based on quantitative polymerase chain reaction (qPCR).
The uncertainty estimated by this document does not include systematic effects (bias).

Mikrobiologie der Lebensmittelkette - Feststellung von Messunsicherheiten bei quantitativen Bestimmungen (ISO 19036:2019)

Dieses Dokument legt Anforderungen fest und bietet eine Anleitung für die Abschätzung und Angabe der Messunsicherheit (MU), die mit quantitativen Ergebnissen in der Mikrobiologie der Lebensmittelkette verbunden ist.
Sie ist anwendbar für die quantitative Analyse von:
- Produkten, die für den menschlichen Verzehr oder als Futtermittel bestimmt sind;
- Umgebungsproben aus den Bereichen der Herstellung von Lebensmitteln und beim Umgang mit Lebensmitteln;
- Proben aus der Primärproduktion.
Die quantitative Analyse erfolgt in der Regel durch die Auszählung der Mikroorganismen anhand eines Koloniezählverfahrens. Dieses Dokument gilt allgemein auch für andere quantitative Analysen, einschließlich:
- Verfahren der wahrscheinlichsten Keimzahl (MPN);
- instrumentelle Verfahren, wie Impediometrie, Adenosintriphosphat (ATP) und Durchflusszytometrie;
- molekulare Verfahren, wie Verfahren, die auf der quantitativen Polymerase Kettenreaktion (en: quantitative polymerase chain reaction, qPCR) basieren.
Die Schätzung der Unsicherheit, die in diesem Dokument enthalten ist, schließt systematische Effekte (systematische Abweichung von Messungen) nicht ein.

Microbiologie de la chaîne alimentaire - Estimation de l'incertitude de mesure pour les déterminations quantitatives (ISO 19036:2019)

Le présent document spécifie des exigences et fournit des recommandations pour l'estimation et l'expression de l'incertitude de mesure (IM) associée à des résultats quantitatifs en microbiologie de la chaîne alimentaire.
Elle s'applique à l'analyse quantitative des:
— produits destinés à la consommation humaine ou à l'alimentation animale;
— échantillons environnementaux dans le domaine de la production et de la manutention de produits alimentaires;
— échantillons au stade de la production primaire.
L'analyse quantitative est généralement effectuée par le dénombrement de micro-organismes à l'aide d'une technique par comptage des colonies. Le présent document s'applique aussi en général à d'autres analyses quantitatives, telles que:
— les techniques du nombre le plus probable (NPP);
— les méthodes instrumentales, comme l'impédancemétrie, l'adénosine triphosphate (ATP) et la cytométrie en flux;
— les méthodes moléculaires, comme les méthodes fondées sur la réaction de polymérisation en chaîne quantitative (qPCR).
L'incertitude estimée par le présent document n'inclut pas les effets systématiques (biais).

Mikrobiologija v prehranski verigi - Ocena merilne negotovosti pri kvantitativnem določanju (ISO 19036:2019)

Ta mednarodni standard podaja zahteve in napotke za oceno in izražanje merilne negotovosti (MU), povezane s kvantitativnimi rezultati mikrobiologije prehranske verige. Uporablja se za kvantitativno analizo:
– izdelkov, namenjenih za prehrano ljudi ali krmo živali;
– okoljskih vzorcev na področju proizvodnje hrane in ravnanja s hrano; ter
– vzorcev v fazi primarne proizvodnje.
Kvantitativna analiza se običajno opravi s štetjem mikroorganizmov s tehniko štetja kolonij. Na splošno se uporablja tudi za druge kvantitativne analize, vključno s tehnikami najverjetnejšega števila (MPN) in instrumentalnimi metodami. Negotovost, ki jo ocenjuje ta mednarodni standard, ne vključuje sistematičnih učinkov (»resničnost« ali »pristranskost«).

General Information

Status
Published
Publication Date
26-Nov-2019
Current Stage
6060 - Definitive text made available (DAV) - Publishing
Due Date
27-Nov-2019
Completion Date
27-Nov-2019

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SLOVENSKI STANDARD
SIST EN ISO 19036:2020
01-januar-2020

Mikrobiologija v prehranski verigi - Ocena merilne negotovosti pri kvantitativnem

določanju (ISO 19036:2019)

Microbiology of the food chain - Estimation of measurement uncertainty for quantitative

determinations (ISO 19036:2019)
Mikrobiologie der Lebensmittelkette - Feststellung von Messunsicherheiten bei
quantitativen Bestimmungen (ISO 19036:2019)

Microbiologie de la chaîne alimentaire - Estimation de l'incertitude de mesure pour les

déterminations quantitatives (ISO 19036:2019)
Ta slovenski standard je istoveten z: EN ISO 19036:2019
ICS:
07.100.30 Mikrobiologija živil Food microbiology
SIST EN ISO 19036:2020 en

2003-01.Slovenski inštitut za standardizacijo. Razmnoževanje celote ali delov tega standarda ni dovoljeno.

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SIST EN ISO 19036:2020
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SIST EN ISO 19036:2020
EN ISO 19036
EUROPEAN STANDARD
NORME EUROPÉENNE
November 2019
EUROPÄISCHE NORM
ICS 07.100.30
English Version
Microbiology of the food chain - Estimation of
measurement uncertainty for quantitative determinations
(ISO 19036:2019)

Microbiologie de la chaîne alimentaire - Estimation de Mikrobiologie der Lebensmittelkette - Feststellung von

l'incertitude de mesure pour les déterminations Messunsicherheiten bei quantitativen Bestimmungen

quantitatives (ISO 19036:2019) (ISO 19036:2019)
This European Standard was approved by CEN on 21 September 2019.

CEN members are bound to comply with the CEN/CENELEC Internal Regulations which stipulate the conditions for giving this

European Standard the status of a national standard without any alteration. Up-to-date lists and bibliographical references

concerning such national standards may be obtained on application to the CEN-CENELEC Management Centre or to any CEN

member.

This European Standard exists in three official versions (English, French, German). A version in any other language made by

translation under the responsibility of a CEN member into its own language and notified to the CEN-CENELEC Management

Centre has the same status as the official versions.

CEN members are the national standards bodies of Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia,

Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Norway,

Poland, Portugal, Republic of North Macedonia, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey and

United Kingdom.
EUROPEAN COMMITTEE FOR STANDARDIZATION
COMITÉ EUROPÉEN DE NORMALISATION
EUROPÄISCHES KOMITEE FÜR NORMUNG
CEN-CENELEC Management Centre: Rue de la Science 23, B-1040 Brussels

© 2019 CEN All rights of exploitation in any form and by any means reserved Ref. No. EN ISO 19036:2019 E

worldwide for CEN national Members.
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SIST EN ISO 19036:2020
EN ISO 19036:2019 (E)
Contents Page

European foreword ....................................................................................................................................................... 3

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SIST EN ISO 19036:2020
EN ISO 19036:2019 (E)
European foreword

This document (EN ISO 19036:2019) has been prepared by Technical Committee ISO/TC 34 "Food

products" in collaboration with Technical Committee CEN/TC 463 “Microbiology of the food chain” the

secretariat of which is held by AFNOR.

This European Standard shall be given the status of a national standard, either by publication of an

identical text or by endorsement, at the latest by May 2020, and conflicting national standards shall be

withdrawn at the latest by May 2020.

Attention is drawn to the possibility that some of the elements of this document may be the subject of

patent rights. CEN shall not be held responsible for identifying any or all such patent rights.

According to the CEN-CENELEC Internal Regulations, the national standards organizations of the

following countries are bound to implement this European Standard: Austria, Belgium, Bulgaria,

Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland,

Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Republic of

North Macedonia, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey and the

United Kingdom.
Endorsement notice

The text of ISO 19036:2019 has been approved by CEN as EN ISO 19036:2019 without any modification.

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SIST EN ISO 19036:2020
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SIST EN ISO 19036:2020
INTERNATIONAL ISO
STANDARD 19036
First edition
2019-10
Microbiology of the food chain —
Estimation of measurement
uncertainty for quantitative
determinations
Microbiologie de la chaîne alimentaire — Estimation de l'incertitude
de mesure pour les déterminations quantitatives
Reference number
ISO 19036:2019(E)
ISO 2019
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SIST EN ISO 19036:2020
ISO 19036:2019(E)
COPYRIGHT PROTECTED DOCUMENT
© ISO 2019

All rights reserved. Unless otherwise specified, or required in the context of its implementation, no part of this publication may

be reproduced or utilized otherwise in any form or by any means, electronic or mechanical, including photocopying, or posting

on the internet or an intranet, without prior written permission. Permission can be requested from either ISO at the address

below or ISO’s member body in the country of the requester.
ISO copyright office
CP 401 • Ch. de Blandonnet 8
CH-1214 Vernier, Geneva
Phone: +41 22 749 01 11
Fax: +41 22 749 09 47
Email: copyright@iso.org
Website: www.iso.org
Published in Switzerland
ii © ISO 2019 – All rights reserved
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SIST EN ISO 19036:2020
ISO 19036:2019(E)
Contents Page

Foreword ..........................................................................................................................................................................................................................................v

Introduction ................................................................................................................................................................................................................................vi

1 Scope ................................................................................................................................................................................................................................. 1

2 Normative references ...................................................................................................................................................................................... 1

3 Terms, definitions and symbols ............................................................................................................................................................ 1

3.1 Terms and definitions ...................................................................................................................................................................... 1

3.2 Symbols ......................................................................................................................................................................................................... 4

4 General considerations .................................................................................................................................................................................. 5

5 Technical uncertainty ...................................................................................................................................................................................... 6

5.1 Identification of main sources of uncertainty .............................................................................................................. 6

5.1.1 General aspects ................................................................................................................................................................. 6

5.1.2 Sampling uncertainty ................................................................................................................................................... 7

5.1.3 Bias .............................................................................................................................................................................................. 7

5.1.4 Critical factors .................................................................................................................................................................... 7

5.2 Estimation of technical uncertainty ...................................................................................................................................... 8

5.2.1 General aspects ................................................................................................................................................................. 8

5.2.2 Reproducibility standard deviation derived from intralaboratory

experiments, s ............................................................................................................................................................... 8

5.2.3 Reproducibility standard deviation derived from interlaboratory studies ...............13

6 Matrix uncertainty .........................................................................................................................................................................................14

6.1 General aspects ....................................................................................................................................................................................14

6.2 Case of homogeneous laboratory (or test) sample ...............................................................................................15

6.3 Multiple test portions from laboratory samples .....................................................................................................15

6.4 Known characteristic of the matrix ....................................................................................................................................16

7 Distributional uncertainties .................................................................................................................................................................17

7.1 General aspects ....................................................................................................................................................................................17

7.2 Colony-count technique — Poisson uncertainty ....................................................................................................17

7.3 Colony-count technique — Confirmation uncertainty ......................................................................................17

7.4 Most probable number uncertainty ...................................................................................................................................18

8 Combined and expanded uncertainty .........................................................................................................................................19

8.1 Combined standard uncertainty ...........................................................................................................................................19

8.1.1 General considerations ............................................................................................................................................19

8.1.2 Combined standard uncertainty based on separate technical, matrix, and

distributional standard uncertainties ........................................................................................................19

8.1.3 Combined standard uncertainty based on reproducibility standard

deviation alone ...............................................................................................................................................................20

8.2 Expanded uncertainty ...................................................................................................................................................................20

8.3 Worked examples ..............................................................................................................................................................................20

8.3.1 Example 1 — Technical, matrix and Poisson components of uncertainty ..................20

8.3.2 Example 2 — Poisson component negligible .......................................................................................20

8.3.3 Example 3 — Poisson, matrix and confirmation components ..............................................21

8.3.4 Example 4 — Technical, matrix and most probable number components ................21

9 Expression of measurement uncertainty in the test reports ..............................................................................22

9.1 General aspects ....................................................................................................................................................................................22

9.2 Results below the limit of quantification ......................................................................................................................23

9.2.1 General aspects ..............................................................................................................................................................23

9.2.2 Example ................................................................................................................................................................................23

Annex A (informative) Calculation of standard deviations with two or more than two

test portions (intralaboratory reproducibility standard deviation and matrix

uncertainty standard deviation).......................................................................................................................................................25

© ISO 2019 – All rights reserved iii
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SIST EN ISO 19036:2020
ISO 19036:2019(E)

Annex B (informative) Matrix effect and matrix uncertainty ..................................................................................................30

Annex C (informative) Intrinsic variability (standard uncertainty) of most probable

number estimates ............................................................................................................................................................................................32

Annex D (informative) Correction of experimental standard deviations for unwanted

uncertainty components ...........................................................................................................................................................................34

Bibliography .............................................................................................................................................................................................................................37

iv © ISO 2019 – All rights reserved
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SIST EN ISO 19036:2020
ISO 19036:2019(E)
Foreword

ISO (the International Organization for Standardization) is a worldwide federation of national standards

bodies (ISO member bodies). The work of preparing International Standards is normally carried out

through ISO technical committees. Each member body interested in a subject for which a technical

committee has been established has the right to be represented on that committee. International

organizations, governmental and non-governmental, in liaison with ISO, also take part in the work.

ISO collaborates closely with the International Electrotechnical Commission (IEC) on all matters of

electrotechnical standardization.

The procedures used to develop this document and those intended for its further maintenance are

described in the ISO/IEC Directives, Part 1. In particular, the different approval criteria needed for the

different types of ISO documents should be noted. This document was drafted in accordance with the

editorial rules of the ISO/IEC Directives, Part 2 (see www .iso .org/ directives).

Attention is drawn to the possibility that some of the elements of this document may be the subject of

patent rights. ISO shall not be held responsible for identifying any or all such patent rights. Details of

any patent rights identified during the development of the document will be in the Introduction and/or

on the ISO list of patent declarations received (see www .iso .org/ patents).

Any trade name used in this document is information given for the convenience of users and does not

constitute an endorsement.

For an explanation of the voluntary nature of standards, the meaning of ISO specific terms and

expressions related to conformity assessment, as well as information about ISO’s adherence to the

World Trade Organization (WTO) principles in the Technical Barriers to Trade (TBT) see www .iso .org/

iso/ foreword .html.

This document was prepared by Technical Committee ISO/TC 34, Food products, Subcommittee SC 9,

Microbiology.

This first edition cancels and replaces ISO/TS 19036:2006, which has been technically revised. It also

incorporates the amendment ISO/TS 19036:2006/Amd.1:2009. The main changes compared with the

previous edition are as follows:

— provision has been made for the estimation of technical uncertainty, and also for other relevant

sources of uncertainty involved in quantitative microbiological tests, relating to:

— the matrix uncertainty (i.e. the uncertainty due to dispersion of microbes within the actual test

matrix);
— the Poisson uncertainty that relates to colony count techniques;

— the confirmation uncertainty associated with tests to confirm the identity of specific organisms

following a count for presumptive organisms;
— the uncertainty associated with most probable number (MPN) estimates;

— the experimental design for the estimation of intralaboratory reproducibility standard deviation

described in this document in connection with the technical uncertainty is now the same as the

design described in ISO 16140-3 for the verification of quantitative methods;

— worked examples have been added to illustrate ways in which uncertainty estimates should be

generated and reported;

— annexes have been added to provide details of some of the important, or alternative, procedures and

issues associated with uncertainty estimation.

Any feedback or questions on this document should be directed to the user’s national standards body. A

complete listing of these bodies can be found at www .iso .org/ members .html.
© ISO 2019 – All rights reserved v
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SIST EN ISO 19036:2020
ISO 19036:2019(E)
Introduction

The term “measurement uncertainty” (MU) is used to denote the lack of accuracy (trueness and

precision) that can be associated with the results of an analysis. In the context of quantitative

microbiology, it provides an indication of the degree of confidence that can be placed on laboratory

estimates of microbial numbers in foods or other materials.

ISO/IEC Guide 98-3 (also known as the “GUM”) is a widely adopted reference document. The principal

approach of ISO/IEC Guide 98-3 is to construct a mathematical or computer measurement model that

quantitatively describes the relationship between the quantity being measured (the measurand) and

every quantity on which it depends (input quantities). That measurement model is then used to deduce

the uncertainty in the measurand from the uncertainties in the input quantities.

ISO/IEC Guide 98-3 recognizes that it might not be feasible to establish a comprehensive mathematical

relationship between the measurand and individual input quantities and that in such cases the effect of

several input quantities can be evaluated as a group. ISO/IEC 17025 also recognizes that the nature of

the test method can preclude rigorous calculation of measurement uncertainty.

In the case of the microbiological analysis of samples from the food chain, it is not feasible to build

a comprehensive quantitative measurement model, since it is not possible to quantify accurately the

contribution of each input quantity, where:

— the analyte is a living organism, whose physiological state can be largely variable;

— the analytical target includes different strains, different species or different genera;

— many input quantities are difficult, if not impossible, to quantify (e.g. physiological state);

— for many input quantities (e.g. temperature, water activity), their effect on the measurand cannot be

described quantitatively with adequate precision.

For the reasons given above, this document mostly uses a top-down or global approach to MU, in which

the contribution of most input quantities is estimated as a standard deviation of reproducibility of the

final result of the measurement process, calculated from experimental results with replication of the

same analyses, as part of the measurement process. These quantities reflect operational variability and

result in technical uncertainty. In food chain quantitative microbiology, assigned values or reference

quantity values are usually not available so bias (which quantitatively expresses the lack of trueness)

cannot be reliably estimated and is not included in the uncertainty estimated by this document.

While reproducibility provides a general estimate of uncertainty associated with the measurement

method, it might not reflect characteristics associated with matrix uncertainty, resulting from the

distribution of microorganisms in the food matrix.

Also, microbiological measurements often depend on counting or detecting quite small numbers of

organisms that are more or less randomly distributed leading to intrinsic variability between replicates

and a corresponding distributional uncertainty. For colony-count techniques, the Poisson uncertainty

is determined, to which may be added, in certain cases, an uncertainty linked to confirmation tests

used to identify isolated organisms. An additional uncertainty component is also required for most

probable number (MPN) determinations. Relevant distributional uncertainty components, estimated

from statistical theory, are calculated from individual experimental data.

These three different kinds of uncertainty (technical, matrix and distributional uncertainties) are

combined using the principles of ISO/IEC Guide 98-3. This approach is similar to that followed by

ISO 29201 in the field of water microbiology.

Technical uncertainty is often the largest of these three kinds and is estimated from a reproducibility

standard deviation, which inevitably includes some contributions from the other two kinds. The

preferred estimate of technical uncertainty is based on intralaboratory reproducibility, in the same

way as ISO 16140-3. If consistent with laboratory protocols and client requirements, a general value of

uncertainty may be reported as based only on a reproducibility standard deviation.

vi © ISO 2019 – All rights reserved
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SIST EN ISO 19036:2020
INTERNATIONAL STANDARD ISO 19036:2019(E)
Microbiology of the food chain — Estimation of
measurement uncertainty for quantitative determinations
1 Scope

This document specifies requirements and gives guidance for the estimation and expression of

measurement uncertainty (MU) associated with quantitative results in microbiology of the food chain.

It is applicable to the quantitative analysis of:
— products intended for human consumption or the feeding of animals;
— environmental samples in the area of food production and food handling;
— samples at the stage of primary production.

The quantitative analysis is typically carried out by enumeration of microorganisms using a colony-

count technique. This document is also generally applicable to other quantitative analyses, including:

— most probable number (MPN) techniques;

— instrumental methods, such as impediometry, adenosine triphosphate (ATP) and flow cytometry;

— molecular methods, such as methods based on quantitative polymerase chain reaction (qPCR).

The uncertainty estimated by this document does not include systematic effects (bias).

2 Normative references
There are no normative references in this document.
3 Terms, definitions and symbols
3.1 Terms and definitions
For the purposes of this document, the following terms and definitions apply.

ISO and IEC maintain terminological databases for use in standardization at the following addresses:

— ISO Online browsing platform: available at https:// www .iso .org/ obp
— IEC Electropedia: available at http:// www .electropedia .org/
3.1.1
sample

one or more items (or a proportion of material) selected in some manner from a population

(or from a large quantity of material) intended to provide information representative of the population,

and, possibly, to serve as a basis for a decision on the population or on the process which had produced it

[SOURCE: ISO/TS 17728:2015, 3.2.2, modified — Note 1 to entry has been deleted.]
3.1.2
laboratory sample

sample (3.1.1) prepared for sending to the laboratory and intended for inspection or testing

[SOURCE: ISO 6887-1:2017, 3.1]
© ISO 2019 – All rights reserved 1
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SIST EN ISO 19036:2020
ISO 19036:2019(E)
3.1.3
test sample

sample (3.1.1) prepared from the laboratory sample (3.1.2) according to the procedure specified in the

method of test and from which test portions (3.1.4) are taken

Note 1 to entry: Preparation of the laboratory sample before the test portion is taken is infrequently used in

microbiological examinations.
[SOURCE: ISO 6887-1:2017, 3.4]
3.1.4
test portion

measured (volume or mass) representative sample (3.1.1) taken from the laboratory sample (3.1.2) for

use in the preparation of the initial suspension

Note 1 to entry: Sometimes preparation of the laboratory sample is required before the test portion is taken, but

this is infrequently the case for microbiological examinations.
[SOURCE: ISO 6887-1:2017, 3.5]
3.1.5
measurand
particular quantity subject to measurement

[SOURCE: ISO/IEC Guide 98-3:2008, B.2.9 modified — The example and the Note 1 to entry have been

deleted.]
3.1.6
trueness
measurement trueness

closeness of agreement between the average of an infinite number of replicate measured quantity

values and a reference quantity value

Note 1 to entry: Trueness is not a quantity and thus cannot be expressed numerically, but measures for closeness

of agreement are given in ISO 5725 (all parts).

Note 2 to entry: Trueness is inversely related to systematic measurement error, but is not related to random

measurement error.

Note 3 to entry: “Measurement accuracy” should not be used for “trueness” and vice versa.

[SOURCE: ISO/IEC Guide 99:2007, 2.14, modified — The preferred term has been changed from

“measurement trueness” to “trueness”.]
3.1.7
bias
measurement bias
estimate of a systematic measurement error

[SOURCE: ISO/IEC Guide 99:2007, 2.18, modified — The preferred term has been changed from

“measurement bias” to “bias”.]
3.1.8
intralaboratory reproducibility
intermediate precision

closeness of agreement between test results obtained with the same method on the same or similar test

materials in the same laboratory with different operators using different equipment

[SOURCE: ISO 8199:2018, 3.6]
2 © ISO 2019 – All rights reserved
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SIST EN ISO 19036:2020
ISO 19036:2019(E)
3.1.9
measurement uncertainty

parameter, associated with the result of a measurement, that characterizes the dispersion of the values

that could reasonably be attributed to the measurand (3.1.5)

Note 1 to entry: The parameter may be, for example, a standard deviation (or a given multiple of it), or the half-

width of an interval having a stated level of confidence.

Note 2 to entry: Measurement uncertainty comprises, in general, many components. Some of these components

may be evaluated from the statistical distribution of the results of a series of measurements and can be

characterized by experimental standard deviations. The other components, which also can be characterized

by standard deviations, are evaluated from assumed probability distributions based on experience or other

information.

Note 3 to entry: It is understood that the result of the measurement is the best estimate of the value of the

measurand and that all components of uncertainty, including those arising from systematic effects, such as

components associated with corrections and reference standards, contribute to the dispersion.

[SOURCE: ISO/IEC Guide 98-3:2008, 2.2.3, modified — The preferred term has been changed from

“uncertainty of measurement” to “measurement uncertainty”.]
3.1.10
standard uncertainty
uncertainty of the result of a measurement expressed as a standard deviation
[SOURCE: ISO/IEC Guide 98-3:2008, 2.3.1, modified — The symbol has been added.]
3.1.11
combined standard uncertainty
u (y)

standard uncertainty (3.1.10) of the result of a measurement when that result is obtained from the values

of a number of other quantities, equal to the positive square root of a sum of terms, the terms being the

...

SLOVENSKI STANDARD
oSIST prEN ISO 19036:2018
01-julij-2018

0LNURELRORJLMDYSUHKUDQVNLYHULJL2FHQDPHULOQHQHJRWRYRVWLSULNYDQWLWDWLYQHP

GRORþDQMX ,62',6

Microbiology of the food chain - Estimation of measurement uncertainty for quantitative

determinations (ISO/DIS 19036:2018)
Mikrobiologie der Lebensmittelkette - Feststellung von Messunsicherheiten bei
quantitativen Bestimmungen (ISO/DIS 19036:2018)

Microbiologie de la chaîne alimentaire - Estimation de l'incertitude de mesure pour les

déterminations quantitatives (ISO/DIS 19036:2018)
Ta slovenski standard je istoveten z: prEN ISO 19036
ICS:
07.100.30 Mikrobiologija živil Food microbiology
oSIST prEN ISO 19036:2018 sl

2003-01.Slovenski inštitut za standardizacijo. Razmnoževanje celote ali delov tega standarda ni dovoljeno.

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oSIST prEN ISO 19036:2018
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oSIST prEN ISO 19036:2018
DRAFT INTERNATIONAL STANDARD
ISO/DIS 19036
ISO/TC 34/SC 9 Secretariat: AFNOR
Voting begins on: Voting terminates on:
2018-05-17 2018-08-09
Microbiology of the food chain — Estimation of
measurement uncertainty for quantitative determinations

Microbiologie de la chaîne alimentaire — Estimation de l'incertitude de mesure pour les déterminations

quantitatives
ICS: 07.100.30
THIS DOCUMENT IS A DRAFT CIRCULATED
This document is circulated as received from the committee secretariat.
FOR COMMENT AND APPROVAL. IT IS
THEREFORE SUBJECT TO CHANGE AND MAY
NOT BE REFERRED TO AS AN INTERNATIONAL
STANDARD UNTIL PUBLISHED AS SUCH.
IN ADDITION TO THEIR EVALUATION AS
ISO/CEN PARALLEL PROCESSING
BEING ACCEPTABLE FOR INDUSTRIAL,
TECHNOLOGICAL, COMMERCIAL AND
USER PURPOSES, DRAFT INTERNATIONAL
STANDARDS MAY ON OCCASION HAVE TO
BE CONSIDERED IN THE LIGHT OF THEIR
POTENTIAL TO BECOME STANDARDS TO
WHICH REFERENCE MAY BE MADE IN
Reference number
NATIONAL REGULATIONS.
ISO/DIS 19036:2018(E)
RECIPIENTS OF THIS DRAFT ARE INVITED
TO SUBMIT, WITH THEIR COMMENTS,
NOTIFICATION OF ANY RELEVANT PATENT
RIGHTS OF WHICH THEY ARE AWARE AND TO
PROVIDE SUPPORTING DOCUMENTATION. ISO 2018
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oSIST prEN ISO 19036:2018
ISO/DIS 19036:2018(E)
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oSIST prEN ISO 19036:2018
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Contents Page

Foreword ........................................................................................................................................................................................................................................iv

Introduction ..................................................................................................................................................................................................................................v

1 Scope ................................................................................................................................................................................................................................. 1

2 Terms and definitions ..................................................................................................................................................................................... 1

3 Sources of uncertainty .................................................................................................................................................................................... 4

4 Technical uncertainty ...................................................................................................................................................................................... 4

4.1 Identification of main sources of technical uncertainty ...................................................................................... 4

4.1.1 General aspects ................................................................................................................................................................. 4

4.1.2 Sampling uncertainty ................................................................................................................................................... 5

4.1.3 Bias .............................................................................................................................................................................................. 5

4.1.4 Critical factors .................................................................................................................................................................... 5

4.2 Estimation of technical uncertainty ...................................................................................................................................... 6

4.2.1 General aspects ................................................................................................................................................................. 6

4.2.2 Reproducibility standard deviation derived from intralaboratory experiments ..... 6

4.2.3 Reproducibility standard deviation derived from interlaboratory studies ...............10

5 Matrix uncertainty; s .....................................................................................................................................................................11

matrix

5.1 General aspects ....................................................................................................................................................................................11

5.2 Laboratory (or test) sample is homogeneous ...........................................................................................................12

5.3 Multiple test portions from laboratory samples .....................................................................................................12

5.4 Known characteristic of the matrix and method ....................................................................................................14

6 Distributional uncertainties .................................................................................................................................................................14

6.1 General aspects ....................................................................................................................................................................................14

6.2 Colony-count technique; “Poisson” uncertainty; s .................................................................................

Poisson 14

6.3 MPN technique, s ......................................................................................................................................................................

MPN 15

6.4 “Binomial” confirmation uncertainty, s .................................................................................................................

conf 15

7 Combined and expanded uncertainty .........................................................................................................................................16

7.1 Calculations .............................................................................................................................................................................................16

7.1.1 Combined uncertainty .............................................................................................................................................16

7.1.2 Expanded uncertainty ..............................................................................................................................................17

7.2 Worked examples ..............................................................................................................................................................................17

8 Expression of measurement uncertainty in the test reports ..............................................................................18

Annex A (informative) Calculation of standard deviations with two or more than two

replicates (intralaboratory reproducibility standard deviation and matrix

uncertainty standard deviation).......................................................................................................................................................20

Annex B (informative) Matrix effect and matrix uncertainty ..................................................................................................23

Annex C (informative) Intrinsic variability (standard uncertainty) of Most Probable

Number estimates ............................................................................................................................................................................................25

Annex D (informative) Subtraction of distributional components from experimental

standard deviations........................................................................................................................................................................................27

Annex E (normative) Averaging test results from multiple test portions ...................................................................29

Bibliography .............................................................................................................................................................................................................................31

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oSIST prEN ISO 19036:2018
ISO/DIS 19036:2018(E)
Foreword

ISO (the International Organization for Standardization) is a worldwide federation of national standards

bodies (ISO member bodies). The work of preparing International Standards is normally carried out

through ISO technical committees. Each member body interested in a subject for which a technical

committee has been established has the right to be represented on that committee. International

organizations, governmental and non-governmental, in liaison with ISO, also take part in the work.

ISO collaborates closely with the International Electrotechnical Commission (IEC) on all matters of

electrotechnical standardization.

The procedures used to develop this document and those intended for its further maintenance are

described in the ISO/IEC Directives, Part 1. In particular the different approval criteria needed for the

different types of ISO documents should be noted. This document was drafted in accordance with the

editorial rules of the ISO/IEC Directives, Part 2 (see www .iso .org/ directives).

Attention is drawn to the possibility that some of the elements of this document may be the subject of

patent rights. ISO shall not be held responsible for identifying any or all such patent rights. Details of

any patent rights identified during the development of the document will be in the Introduction and/or

on the ISO list of patent declarations received (see www .iso .org/ patents).

Any trade name used in this document is information given for the convenience of users and does not

constitute an endorsement.

For an explanation on the meaning of ISO specific terms and expressions related to conformity assessment,

as well as information about ISO's adherence to the World Trade Organization (WTO) principles in the

Technical Barriers to Trade (TBT) see the following URL: www .iso .org/ iso/ foreword .html.

The committee responsible for this document is ISO/TC 34, Food products, Subcommittee SC 9,

Microbiology.

This first edition cancels and replaces ISO/TS 19036:2006, which has been technically revised.

The main changes are as follows.

The standard now includes provision not only for estimation of technical uncertainty but also for other

relevant sources of uncertainty that are involved in quantitative microbiological tests. These additional

sources relate to:

— the matrix uncertainty (i.e. the uncertainty due to dispersion of microbes within the actual test

matrix);
— the Poisson uncertainty that relates to colony count techniques;

— the confirmation uncertainty associated with tests in colony-count and other techniques to confirm

identity of specific organisms following a count for presumptive organisms; and
— the uncertainty associated with Most Probable Number estimates.

Worked examples illustrate ways in which uncertainty estimates should be generated and reported.

Annexes provide details of some of the important, or alternative, procedures and issues associated with

uncertainty estimation.
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Introduction

The term ‘Measurement Uncertainty’ (MU) is used to define the lack of accuracy (trueness and precision)

that can be associated with the results of an analysis. In the context of quantitative microbiology, it

provides an indication of the degree of confidence that can be placed on laboratory estimates of

microbial numbers in foods or other materials.
[1]

The Guide to the expression of uncertainty in measurement (GUM) is a widely adopted reference

document. The principal approach of the GUM is to construct a mathematical or computer measurement

model that quantitatively describes the relationship between the quantity being measured (the

measurand, Y) and every quantity on which it depends (input quantities, X ). That measurement model

is then used to deduce the uncertainty in the measurand from the uncertainties in the input quantities.

The GUM recognises that it might not be feasible to establish a comprehensive mathematical

relationship between the measurand and individual input quantities and that in such cases the effect of

[2]

several input quantities can be evaluated as a group. ISO 17025 also recognises that the nature of the

test method may preclude rigorous, metrologically and statistically valid, calculation of uncertainty of

measurement.

In the case of the microbiological analysis of samples from the food chain, it is not feasible to build

a comprehensive quantitative measurement model since it is not possible to quantify accurately the

contribution of each input quantity, where:

— the analyte is a living organism, whose physiological state can be largely variable; and

— the analytical target includes different strains, different species or different genera; and

— many input quantities are difficult, if not impossible, to quantify (e.g. physiological state); and

— for many input quantities (e.g. temperature, water activity), their effect on the measurand cannot be

described quantitatively with adequate precision.

For these reasons, trueness is not included in the assessment of measurement uncertainty.

For the reasons given above, this International Standard mostly uses a “top-down” or “global” approach

to measurement uncertainty in which the contribution of most input quantities is estimated as a

standard deviation of reproducibility of the final result of the measurement process, calculated from

experimental results with replication of the same analyses, as part of the measurement process. These

quantities reflect operational variability and result in technical uncertainty.

Whilst the technical uncertainty provides a general estimate of uncertainty associated with the

sample(s) tested, it may not reflect characteristics associated with matrix uncertainty, resulting from

the distribution of microorganisms in the food matrix.

Also, microbiological measurements often depend on counting or detecting quite small numbers of

organisms that are more or less randomly distributed leading to intrinsic variability between replicates

and a corresponding distributional uncertainty. For colony-count techniques, the “Poisson” uncertainty

is determined, to which may be added, in certain cases, an uncertainty linked to confirmation tests

used to identify isolated organisms. Additional uncertainty estimate is also required for Most Probable

Number determinations. Relevant distributional uncertainty components, estimated from statistical

theory, are calculated from individual experimental data.

These three different kinds of uncertainty (technical, matrix and distributional uncertainties) are

[1] [3]

combined using the principles of the GUM. This approach is similar to that followed by ISO 29201

in the field of water microbiology.

Technical uncertainty is usually the largest component and, if consistent with laboratory protocols and

client requirements, a general value of uncertainty may be reported as limited to technical uncertainty.

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oSIST prEN ISO 19036:2018
DRAFT INTERNATIONAL STANDARD ISO/DIS 19036:2018(E)
Microbiology of the food chain — Estimation of
measurement uncertainty for quantitative determinations
1 Scope

This International Standard gives requirements and guidance for the estimation and expression of

measurement uncertainty (MU) associated with quantitative results in microbiology of the food chain.

It is applicable to the quantitative analysis of:
— products intended for human consumption or the feeding of animals;
— environmental samples in the area of food production and food handling;
— samples at the stage of primary production.

The quantitative analysis is typically carried out by enumeration of microorganisms using a

colony-count technique. It is also generally applicable to other quantitative analyses, including Most

Probable Number (MPN) techniques and instrumental methods, such as impediometry and flow

cytometry.

The uncertainty estimated by this International Standard does not include systematic effects

(“trueness” or “bias”).
2 Terms a nd definiti ons

For the purposes of this International Standard, the following terms and definitions apply.

ISO and IEC maintain terminological databases for use in standardization at the following addresses:

— IEC Electropedia: available at http://w ww .electropedia .org/
— ISO Online browsing platform: available at http://w ww .iso. org/ obp
2.1
uncertainty of measurement, or measurement uncertainty (MU)

parameter, associated with the result of a measurement, that characterizes the dispersion of the values

that could reasonably be attributed to the measurand

Note 1 to entry: The parameter may be, for example, a standard deviation (or a given multiple of it), or the

half-width of an interval having a stated level of confidence.

Note 2 to entry: Uncertainty of measurement comprises, in general, many components. Some of these

components may be evaluated from the statistical distribution of the results of a series of measurements and can

be characterized by experimental standard deviations. The other components, which also can be characterized

by standard deviations, are evaluated from assumed probability distributions based on experience or other

information.

Note 3 to entry: It is understood that the result of the measurement is the best estimate of the value of the

measurand and that all components of uncertainty, including those arising from systematic effects, such as

components associated with corrections and reference standards, contribute to the dispersion.

[SOURCE: GUM ]
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2.2
standard uncertainty
u(y )

uncertainty of the result of a measurement expressed as a standard deviation[Source: GUM

2.3
expanded uncertainty

quantity defining an interval about the result of a measurement that may be expected to encompass a

large fraction of the distribution of values that could reasonably be attributed to the measurand

Note 1 to entry: The fraction may be regarded as the coverage probability or level of confidence of the interval.

Note 2 to entry: To associate a specific level of confidence with the interval defined by the expanded uncertainty

requires explicit or implicit assumptions regarding the probability distribution characterized by the

measurement result and its combined standard uncertainty. The level of confidence that may be attributed to

this interval can be known only to the extent to which such assumptions may be justified.

Note 3 to entry: An expanded uncertainty U is calculated from a standard uncertainty u(y) and a coverage factor

k (2.4) using:
U = ku(y)
[1]
[Source: GUM ]
2.4
coverage factor

number larger than one by which a combined standard measurement uncertainty is multiplied to

obtain an expanded measurement uncertainty
[SOURCE: GUM ]
2.5
technical uncertainty (operational variability)
uncertainty resulting from operational variability

operational variability is associated with the technical steps of the analytical procedureNote to

1 entry: Technical uncertainty includes the variability of the sub-sampling, mixing, and dilution

of the test portion taken from the laboratory sample to prepare the initial suspension and subsequent

dilutions. It also includes the effects of variability in incubation and media
[SOURCE: Adapted from ISO 29201 ]
2.6
distributional uncertainty (intrinsic variability)
uncertainty resulting from intrinsic variability

Intrinsic variability is the unavoidable variation that is associated with the distribution of

microorganisms in the sample, the initial suspension and subsequent dilutions

Note 1 to entry: In microbiological suspensions intrinsic variability is usually modelled by the Poisson

distribution. When partial confirmation is practised or the MPN principle is used, the resulting distribution may

differ from the Poisson.
[3]
[Adapted from ISO 29201 ]
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2.7
sample (general term)

one or more items (or a proportion of material) selected in some manner from a population (or from

a large quantity of material) intended to provide information representative of the population, and

possibly, to serve as a basis for a decision on the population or on the process which had produced it

[SOURCE: ISO/TS 17728:2015 ]
2.8
laboratory sample

sample prepared for sending to the laboratory and intended for inspection or testing

[SOURCE: ISO 6887-1 ]
2.9
test sample

sample prepared from the laboratory sample according to the procedure specified in the method of test

and from which test portions are taken

Note 1 to entry: Preparation of the laboratory sample before the test portion is taken is infrequently used in

microbiological examinations.
[5]
[Source: ISO 6887-1 ]
2.10
test portion

measured (volume or mass) of representative sample taken from the laboratory sample for use in the

preparation of the initial suspension

Note 1 to entry: Sometimes preparation of the laboratory sample is required before the test portion is taken, but

this is infrequently the case for microbiological examinations.
[5]
[Source: ISO 6887-1 ]
2.11
trueness
measurement trueness

closeness of agreement between the average of an infinite number of replicate measured quantity

values and a reference quantity value

Note 1 to entry: Measurement trueness is not a quantity and thus cannot be expressed numerically, but measures

for closeness of agreement are given in ISO 5725 (all parts).

Note 2 to entry: Measurement trueness is inversely related to systematic measurement error, but is not related to

random measurement error.

Note 3 to entry: Measurement accuracy should not be used for ‘measurement trueness’ and vice versa.

[1]
[Source: GUM ]
2.12
measurand
particular quantity subject to measurement
[SOURCE: GUM ]
2.13
matrix uncertainty

uncertainty resulting from the extent to which the test portion ( 2.11) is not truly representative of the

laboratory sample (2.9)
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3 Sources of uncertainty

It is essential for laboratories to identify and take into account all possible sources of uncertainty that

may affect the final result that is reported.

As indicated in 1, the uncertainty estimated by this International Standard does not include contributions

from systematic effects (trueness (2.11) or “bias”). In food chain quantitative microbiology, assigned

values or reference quantity values are usually not available so bias cannot be estimated.

This International Standard considers three components of uncertainty: technical, matrix and

distributional uncertainties.

As explained in the Introduction, the technical uncertainty arising from operational variability is

estimated, using a “global” approach, as a standard deviation of reproducibility of the final result of

the measurement process. The adoption of this global approach necessitates that results come from

a measurement procedure rather than by calculation using known estimates of variability associated

with every individual stage of the test.

Ongoing estimation of MU is needed to show that the estimate of uncertainty remains relevant and that

the test results are under control. Reassessment is required following changes to any critical factors

(see 4.1.1 and 4.1.4) that are likely to affect the results obtained with that method in any significant way.

[2]

Laboratories following ISO 17025 monitor their results. With appropriate planning, such monitoring

may meet, partially or completely, the data requirements of this International Standard with respect to

technical uncertainty estimation and monitoring.

Technical uncertainty is usually the largest component, and is estimated experimentally for each

method. If consistent with laboratory protocols and in agreement with clients, a general value of MU

may be reported as being limited to technical uncertainty (see 8).

Imperfect mixing of the sample results in poor reproducibility of microbial levels between test portions

and contributes to “matrix uncertainty”, which may be large for solid matrices. Matrix uncertainty is

estimated for each kind of matrix and method (see 5).

Even for homogeneous materials, there are three potential sources of distributional uncertainty, the

relevance of which depends on the method used:
a) For colony-count techniques; “Poisson” uncertainty: s (6.2);
Poisson
b) For Most Probable Number (MPN) techniques: s (6.3);
MPN

c) For colony-count and other techniques with confirmation tests: “Binomial” uncertainty; s (6.4).

conf
The uncertainty for each source is usually estimated mathematically.
4 Technical uncertainty
4.1 Identification of m ain sources of technical uncertainty
4.1.1 General aspects

It can be helpful to consider the sources of technical uncertainty usually associated with the main

stages in a microbiological method. Typical sources for colony-count or MPN techniques are:

— taking a test portion from the laboratory (or test) sample;
— preparation of the initial suspension;
— serial dilution;
— inoculation;
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— incubation;

— counting of colonies in a colony count technique, and/or detection of growth (as in a MPN technique);

— confirmation (if appropriate).

Figure 1 shows the main sources of technical uncertainty in food chain microbiology taken into account

in this International Standard.

Figure 1 — Diagram of the main sources of uncertainty in food chain microbiology covered in this

International Standard. Solid lines indicate the sequential procedures and dotted lines the factors

that affect uncertainty estimation. The symbol ⌀ indicates that these factors are not covered by this

International Standard.
4.1.2 Sampling uncertainty

Sampling uncertainty, i.e. error associated with the drawing of the laboratory sample from a lot

[6]

under investigation, may contribute significantly to the overall error (see ), but it is not part of the

uncertainty linked to the measurement itself and is not covered by this International Standard .

Matrix uncertainty that arises from the inability of the test portion (2.10) to best represent a

heterogeneous laboratory sample (2.8) or test sample (2.9) is covered in 5. The extent of such

heterogeneity may depend, in particular, on the size of the test portion taken for examination (see

[5]
ISO 6887-1 ).
4.1.3 Bias

As indicated in 1 and 3, MU estimated by this International Standard does not include contributions

from systematic effects (“bias” or trueness (2.11)).
4.1.4 Critical factors

Examples of critical technical factors that may influence uncertainty and need to be controlled include:

the source and type of culture media and/or other reagents (such as the ones used for confirmation),

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the dilution, inoculation and incubation procedures, the counting techniqu
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