Nutritional Information Panels (NIPs) are an important source of information that enable consumers to make their purchases based on their individual needs. With state-of-the-art facilities, Symbio Laboratories is NATA accredited to provide this important information on behalf of food manufacturers. However, some confusion surrounds measurement uncertainties in the results of analysis for samples submitted for NIP testing.
What is Measurement Uncertainty?
Measurement Uncertainty (MU) describes the confidence interval always present in results of analysis in which the true value of a measured property is expected to lie. This varies depending on the:
- type of the sample,
- test being conducted,
- equipment used, and
- concentration of the parameter being measured.
It’s important to note that this uncertainty is perfectly normal, and can in fact be beneficial to the customer.
What are the causes of Measurement Uncertainty?
As mentioned above, the causes of measurement uncertainty include the type of the sample, the test conducted, equipment used and the concentration of the parameter measured.
Other variances in measurement conditions, such as different individuals performing the collection of samples, can also lead to changes in the true values of samples. For example, when samples are collected and prepared by a customer whose methods differ from those used by the laboratory, measurement uncertainty can take those potential differences into account in the final reporting.
In relation to the food industry, and NIPs in particular, another common cause of measurement uncertainty is when different macronutrients in a product interact during the cooking/baking/mixing process. This can result in the macronutrient levels differing from what is expected of each one present in the individual ingredients.
Listed below is a table of attributes including nutrients (most are mandatory requirements) listed on all NIPs, with reasons as to why any variations and measurement uncertainty may occur.
|Test Analysis||Variation Reason|
|Ash||Variation in Ash can be due to salt content. More salt will give higher Ash.|
|Avail Carbohydrate#||Carbohydrate value can vary due to the different values in %protein, %fat, %moisture, %ash, %alcohol, %Total Dietary Fibre. Where available carbohydrate % = 100 – (%protein + %fat + %moisture + %ash + %alcohol + %Total Dietary Fibre). Total carbohydrate is also determined by calculation, with fibre not included in the calculation.|
|Iron (Fe)||Variation in Iron can be due to other ingredients e.g. flour content in the case of bakery items.|
|Sodium (Na)||May be due to salt content added during manufacturing. Not all salts are sodium based either.|
|Energy #||Energy value can vary due to the difference in %protein, %fat, %moisture, %ash, %alcohol, % Total Dietary Fibre from different batches/production runs. Where energy (kJ/100g) = (CHO x 17) + (P x 17) + (F x 37) + (DF x 8) + (ALC x 29)|
|Fat||Where there are high levels of sugar and low levels of fat, sugar can have an impact in the total fat result (but only very minor).|
|Dietary Fibre (Insoluble)||Variation can be due to fortification of ingredients e.g. flour in the case of bakery items|
|Dietary Fibre (Soluble)||Variation can be due to fortification of ingredients e.g. flour in the case of bakery items|
|Dietary Fibre (Total)||Variation can be due to fortification of ingredients e.g. flour in the case of bakery items|
|Total Moisture||Cooking time, drying time, baking time and the like which was applied to a sample prior to submission and the time/temperature protocols in the laboratory. Also any added water content can vary from the specification the manufacturer believes they have set.|
|Protein||The protein content variation can be from various natural sources in a range of ingredients, even ones that are normally seen as having protein – in bakery for example the wheat, gluten or other protein content & baker’s yeast ingredients all impact the results. The amount intended to be added as an ingredient may vary from targets in a given sample.|
|Total Sugar||Variation may be due to the various forms of carbohydrate that have been added, and the different types and amounts and sugar added.|
Standardising changes to minimise variations and deviations
To determine that the test method used for analysis is capable and effective in achieving a quality result, reference standards of known concentrations are used. This is for both the method overall and for individual batch runs, with a minimum of 7 replicates of quality control standards analysed, and results checked against the mean (average) value.
Validation is required to ensure that the results produced with the method used are both accurate and precise within a reasonable measurement of uncertainty, and that reliability and repeatability are assured for the same sample analysed by different operators at different times. Test methods are also verified to demonstrate that the performance characteristics of an existing standard method can be achieved under the laboratory’s test conditions.
With a commitment to excellence, Symbio Laboratories has implemented wide-ranging internal proficiency programs, and participates in a large number of external proficiency programs to ensure a high level of accuracy and service. Customers can be assured that all our test methods are based on Australian Standards or recognised international references (e.g. AOAC, AOCS, AACC, APHA, USEPA).