MEASUREMENT

UNCERTAINTY (MU) FOR

QUANTITATIVE

DETERMINATIONS

Elina Lahti, CRL Campylobacter

Measurement uncertainty (MU) in

baseline study

ISO/TS 19036

Commission Decision concerning

a financial contribution from the

Community towards a survey on

the prevalence and antimicrobial

resistance of Campylobacter spp.

In broiler flocks and on the

prevalence of Campylobacter spp.

and Salmonella spp. In broiler

carcasses to be carried out in the

Member States

2007/516/EC

Microbiology of food and animal

feeding stuffs – Guidelines for the

estimation of measurement

uncertainty for quantitative

determinations

ESTIMATION OF STANDARD DEVIATION OF

REPRODUCIBILITY (SR)

1) Intralaboratory

2) Interlaboratory study

3) Interlaboratory proficiency trial

Possibilities

GLOBAL APPROACH FOR THE ESTIMATION OF MU

Equipment, culture

media, reagents

Sub-sampling/primary

dilution

Bias

Operator/timeResidual

random errors

Matrix

Laboratory

sample

Sampling

Result

GLOBAL APPROACH FOR THE ESTIMATION OF MU

Equipment, culture

media, reagents

Sub-sampling/primary

dilution

Operator/timeResidual

random errorsMatrix

Laboratory

sampleResult

INTRALABORATORY SR

But

different time period

different technicians

different batches, reagents,

incubators,

as routine procedure

Derived from analyses performed at one laboratory

TYPE OF SAMPLES

1) Naturally contaminatedmore realistic estimation

2) Artificially contaminatedshould be tightly controlled

mimic real contamination

stressed organisms

competitive flora

Possibilities

BASELINE STUDY

According to ISO/TS 19036:2006

12 samples

May-September

examined in duplicate

parallel dilutions from the 10 ml initial suspension

In principle

CALCULATIONS

1) Data log transformed

2) Reproducibility standard deviation

sR

3) Expanded uncertainty (U)

U = k * uc (y)

uc combined standard uncertainty

k coverage factor (approx. 2)

EXAMPLE

A1 A1 A2 A2 Result B1 B1 B2 B2 Result Log A Log B

2 684 50 563 67 6200 522 29 452 66 4859 3,792392 3,686547

3 3 0 2 0 25 0 0 1 0 10 1,39794 1

4 3 1 2 0 30 2 2 6 0 48 1,477121 1,681241

7 97 10 115 10 1055 101 12 124 16 1664 3,023252 3,221153

8 229 38 408 45 3273 471 6 368 48 4059 3,514946 3,608419

14 89 0 46 2 650 100 4 175 10 1314 2,812913 3,118595

15 373 23 408 72 3980 292 69 426 51 3809 3,599883 3,580811

16 77 6 61 3 668 68 2 70 5 659 2,824776 2,818885

18 92 13 92 13 950 94 9 99 10 1414 2,977724 3,150449

19 530 69 506 69 5336 548 73 471 64 5255 3,727216 3,720573

20 617 92 887 94 7680 887 88 821 54 8409 3,885361 3,924744

21 7 2 15 4 127 9 1 22 1 150 2,103804 2,176091

SR (n=12) 0,016234

SQ (SR) 0,127414

U (SR*2) 0,254827

Operator A Operator B

MU ESTIMATIONS IN THE BASELINE STUDY

Type of samples

naturally contaminated 11 NRLs

naturally contaminated & spiked 3 NRLs

spiked 1 NRL

No. labs

1 12 NRLs

2 or more 4 NRLs

Starting month

May 5 NRLs

June 5 NRLs

July 1 NRL

Expanded uncertainty

0,11-0,26

PROBLEMS ENCOUNTERED

Naturally contaminated samples few or contain low levels

> 100 cfu/g for the estimation

Time delay between analyses

Campylobacter might decrease to <100 cfu/g

during the storage

Several laboratories in a MS

different policies