With some analytical parameters, certified reference materials are lacking and the reference method shows limited performance. Somatic cell counting in milk is a clear example. It is one of the most frequently performed measurements, estimated at over 500 000 000 tests/year world wide. It serves as an indicator for the udder health status of lactating animals, is relevant in food legislation, in payment of raw milk, and also has a considerable impact for farm management and animal-breeding programs. The analytical performance of nowadays fluoro-opto-electronic routine methods in terms of precision is superior to the reference method based on microscopy. Laboratories have therefore adopted various solutions for anchoring their counting level. It is there that a reference system approach can serve to optimally safeguard comparability of routine testing results in laboratories world wide. A reference system is characterized as a systematically developed anchoring system that is fed by different types of information from various sources, that is, measurements on reference materials, reference method analysis, and routine method results. A joint Project Group of the International Dairy Federation and the International Committee on Animal Recording has been given the task to design a workable global reference system for somatic cell counting in milk. This paper describes the structure and the functioning of such a reference system, a plan for the implementation and the responsibilities of the involved stakeholders in safeguarding its functioning. After approval in IDF and ICAR, the resulting proposal is to be offered for adoption by concerned governmental and nongovernmental bodies worldwide.
Fourier-transform mid-infrared spectrometry is an attractive technology for screening adulterated liquid milk products. So far, studies on how infrared spectroscopy can be used to screen spectra for atypical milk composition have either used targeted methods to test for specific adulterants, or have used untargeted screening methods that do not reveal in what way the spectra are atypical. In this study, we evaluate the potential of combining untargeted screening methods with cluster algorithms to indicate in what way a spectrum is atypical and, if possible, why. We found that a combination of untargeted screening methods and cluster algorithms can reveal meaningful and generalizable categories of atypical milk spectra. We demonstrate that spectral information (e.g., the compositional milk profile) and meta-data associated with their acquisition (e.g., at what date and which instrument) can be used to understand in what way the milk is atypical and how it can be used to form hypotheses about the underlying causes. Thereby, it was indicated that atypical milk screening can serve as a valuable complementary quality assurance tool in routine FTIR milk analysis.
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