Developing milk quality indicators with big dataPublished: 12-11-2015, | Member: Qlip
Testing milk is a core activity at the Qlip laboratory. Every day, this company tests thousands of milk samples. Qlip has developed a grazing indicator based on milk samples and grazing data. The laboratory is also working on other milk quality indicators, which it plans to introduce in the next few years.
Pastures dotted with grazing cows: this image will always be part of the Dutch landscape. Consumers want it to stay that way, too. Worldwide, the same image is used to promote Dutch milk and dairy. However, some modern dairy farmers find it impractical to allow cows to graze from spring until fall. This is why dairy suppliers’ milk is regularly tested to determine whether it is probable that their cows are spending enough time grazing.
Qlip, a laboratory specialized in quality assurance of dairy products, has developed a novel grazing indicator. This indicator shows whether the milk tested was produced by cows nourished by fresh grazed grass. The composition of milk is affected by what a cow eats, making it possible to see whether they were fed fresh grazed grass or other feed such as grass or corn silage. The grazing indicator provides a new method for monitoring and safeguarding sufficient grazing.
The lab analyzes more than 50,000 raw milk samples every day. The analyses are used by dairy companies for payment purposes to the farmers which get paid for their fresh milk and for dairy herd improvement programs. The milksamples are routinely analyzed for quality and composition. Dairy farmers use these data to make farm management decisions. The same data enable the dairy sector to assure the safety and quality of milk, while dairy herd improvement organizations use the information to breed better milk cows and to generate management data for dairy farmers.
The milk is analyzed by means of infrared technology. This results in a unique spectrum for every milk sample, supplying information about the specific composition of the milk. This information can be related to the intake of freshly grazed grass.
“The spectra and models can also be used for the development of other indicators,” says Jan Rademaker, innovation manager at Qlip. “We’re working on other indicators that use big data from milk to determine animal health, animal welfare and sustainability, for example.”