Nutritional Elements in Canned Meat Quality Control Material

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Product Specification

QC/RM information
Product Code Material Matrix Approx. Size
FCNE6-MRP12QC

T1883QC

Canned Meat

150g

Analytes

Phosphorus, Zinc

Validity Date

18/02/2025

Test Description

Within this quality control material the nutritional elements of Calcium, Phosphorus and Zinc are included. This quality control material is ideal for ensuring high quality testing practices are maintained to satisfy your customers and regulators.

As nutritional legislation increases, the proficiency of laboratories to provide accurate results to food manufacturers for labelling is critical, to help consumers make informed choices about the food they eat. Fapas offers the widest range of analyte/matrix proficiency test combinations for the food sector.

Proximates inform a variety of characteristics of food products, such as quality and composition. As such effective testing is required to highlight any misleading claims or inaccurate nutritional values. Quality control materials are ideal to highlight any poor analysis practices or areas for improvement, from which to ensure high quality test results are offered to your customers. Manufacturers may also make bold labelling claims that should be verified to determine their accuracy, something which requires extensive, flexible techniques.

Canned meat is being consumed in increasingly large quantities worldwide. This is due to the valuable advantages offered to consumers such as cost savings due to the large storage times compared to fresh equivalents. This increased quantity of consumption can add pressure on global supply chains. This therefore requires high levels of testing abilities from your laboratory to ensure products are sold as claimed.

Quality control materials are invaluable in maintaining the high quality testing required to maintain the high testing standards expected by both your customers and regulators. Fapas quality control materials make use of real food matrices, which can allow you to highlight areas of bias within your current routine analysis arrangement. This could be in the form of staff training measures, or instrumentation verification activities.

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