The Accuracy of a Reference for Lean Meat Content        some general aspects

Eli Vibeke Olsen, DMRI

Introduction

To estimate the content of some substances you need a measuring method, but very often the substances can only very hardly be measured directly. Instead, you can measure some correlated substances or characteristics.

However, you still need to measure the substance of interest to be able to calibrate your indirect method. If your methods do not produce an outcome, which is known generally and comparable with other methods, you cannot use the results as information to the surrounding world. If the substance is the amount of lean meat – or other characteristics related to meat like water holding capacity, tenderness etc – a lot of technical measuring problems arise. The aim of this text is to suggest a standard to document measuring methods within pig carcass classification. However, the postulate is that the principles can be expanded to nearly all types of measuring methods within meat technology.

The proposal is established as a conclusion based on the experiences from the EUPIGCLASS project.

Uncertainty

Test results obtained from measurements using equipment will always be more or less defective. In general tests performed on presumably identical materials in presumably identical circumstances do not yield identical results. This un-avoidable uncertainty is influenced by several factors and only some of them can be controlled.

The uncertainty or error can either be systematic or random. In this context systematic error (bias) is the possible deviation from a “true” value taken the arithmetic mean of a large number of test results.

Accuracy – definition (International standards: ISO 5725 / GUM)

For many years these problems have been studied for chemical laboratory methods or similar methods in the laboratory. The International Organization for Standardization (ISO) has carried out the so-called ISO 5725 standard: Accuracy (trueness and precision) of measurement methods and results (1995).

The basic definitions can be explained by a statistical model, which describe the test results obtained from a measurement performed on a sample item having a known true value:

Yij - m = d + Bi + eij

m          is the “true” value,

d          express possible deviation from the true value

Bi               express the influence from uncontrolled factors like: operator, equipment, calibration, environment (temperature, humidity, air pollution, etc.), time elapsed

              - this random contribution is assumed to follow a Gauss distribution N(0,sL2)

eij           express unexplained error attached tests performed on identical materials in identical circumstances (same method, same operator, same equipment within short intervals of time) – this random error is assumed to follow a Gauss distribution N(0,sr2) independently of Bi.

The trueness is the closeness of agreement between a test result and the accepted reference value, i.e. in statistical terms we want to test the hypothesis

H0:       d=0

This test will be performed using the reproducibility standard deviation sR, which is defined by the square root of

s2R  = s2L + s2r  

and sr is called the repeatability standard deviation.

In general, Bi can be decomposed in several different factors inclusive interactions between the factors.

The Guide to the expression of Uncertainty in Measurement (GUM) focus on this decomposition. The aim is to evaluate the importance of different factors, which can be used to monitor the method in detail or possibly to improve the methods most efficiently. The method uses the “law of propagation of uncertainty” i.e. express the reproducibility variance as a sum of uncertainties attached the influencing factors. However, it is a big problem is to estimate all contributions - actually, from a “GUM point of view” the best guess made by an expert can be accepted as an estimate.

Accuracy – problems, when measuring meat characteristics

“Identical test items”

A general problem when measuring characteristics attached pig carcasses and pig meat is to obtain identical test items. The time of sampling is important because the meat will change in a time interval of at least 24 hours after killing. The changes are caused by the glycolysis and other biochemical processes dependent on the energy level just before killing and the environment at the slaughterhouse – the chilling for instance.

If the measuring method includes the whole carcass it is impossible to obtain identical items – perhaps cloning can solve this problem. If only a half carcass is used, the left and right side are obvious duplicates. However, pigs are not completely symmetric and probably, the measuring method and/or the manual handling can depend on the side.

The appearance of the whole carcass depends on the slaughtering process – in Denmark for instance the surface of the skin is processed very intensively to be used as crackling pork rind.

Repeated measurements using methods based on insertion of probes into a pig carcass are impossible. A second measurement at the same site will differ because the probe has cut the muscle fibres in the first measurement.

Time intervals

The dissection method is time consuming, but the time used to dissect one half carcass differ from one butcher to another, which can imply different weight loss. Furthermore, only one dissection per day implies that repeated measurement on identical materials within a short period of time is impossible.

Accepted reference value

The ISO standard only concerns certified reference materials or materials whose properties have been established by measurements using an alternative method whose bias is known to be negligible. Possible uncertainty attached to the reference is neglected too.

In pig carcass classification the dissection method is the “accepted reference method”, even though the “quality” of the reference was unknown before the EUPIGCLASS project.

Accuracy in pig carcass classification

There are two main problems:

How accurate is the reference? Is it reproducible from one country to another?

How accurate are on-line measurements? Is it reproducible from one abattoir to another?

It is obvious to try to use the ISO standard to answer the questions above. However some modifications must be considered. By way of introduction the definition of repeatability will be considered. The ISO standard define the concept by a standard deviation describing the distribution of replicates under certain conditions. Another point of view is to consider the repeatability by the correlation between replicates, which has the advantage of being without unit. This estimate can be interpreted as a “signal to noise” estimate i.e. it is possible to evaluate the noise attached to the measuring method in relation to the phenomenon, we want to describe. In other contexts this correlation is described as the reliability of the method. It is proposed to use this term in pig carcass classification.