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With the EU-Fertiliser Ring Test, VDLUFA offers a quality assurance program concerning the analysis of nutrients and pollutants in fertilisers. It particularly addresses accredited laboratories which have been notified by the EU-Commission for fertiliser analysis, but the test is also open to any laboratory worldwide. VDLUFA membership is not necessary to participate in the ring test. An important aim of the test is to enable laboratories in all EU countries to test their analysis quality and to document the test results.
The EU-Fertiliser Ring Test is carried out by the VDLUFA section III “Fertiliser Analysis” in co-operation with the head office of VDLUFA.
The main objective of the test is the continuous review of the reproducibility of the test results of participating laboratories involved in the official fertiliser monitoring. This includes the monitoring of legal tolerances.
Identical fertiliser samples are sent to the laboratories which have registered for the current test cycle. The participating laboratories are asked to analyse a specified number of chemical parameters using official or standardised methods within the defined timeline
All data are handled anonymously using assigned laboratory identification numbers. Each institution receives a laboratory identification number, which is necessary for reporting the data.
The statistical evaluation of the test results, including the calculation of laboratory means, analytical uncertainties and a summarising statistical evaluation, is carried out using the validated software package “ProLab”. A robust method is applied (DIN 38402 A45, Q-method, Hampel estimate) and Zu-scores (tolerance limit |Zu| = 2.0) are calculated as a bias estimate using IUPAC guidelines so that laboratories may gauge their performance relative to their peers. Horwitz ratios are calculated, if possible.
Each participating laboratory receives a certificate of participation in the VDLUFA EU-Fertiliser Ring Test. Additionally each participant receives a final report of the ring test in English which includes a statistical evaluation based on the anonymous participant data.
