4D4F event: Interpreting milk data for improving yields

Author: Jef Aernouts (Farmdesk) - Date: January 4, 2019

This 4D4F event was the second session on the use of technology and data in goat farming and was held on October 24, 2018. Flemish and Dutch goat farmers were brought together in the class room of an agricultural school in Antwerp (Belgium) to exchange their personal experiences, and gauge their needs for automation and data use.

Jef Aernouts (Farmdesk) started off the event with a brief description of the 4D4F project. Next, he discussed the results of the questionnaire at the previous meeting and the follow-up online questionnaire. The main findings with regard to this meeting were: 67,7% of the goat farmers want to have more insights on rationing; 54,4%/46,7% admit not to have enough profound knowledge on technical/economical KPI’s; 90% want to be more occupied with farm data. These findings date back from more than a year ago. It was the trigger for the Farmdesk startup initiative.

After the intro, Jef demonstrated the Farmdesk tool (www.farmdesk.eu), an online tool that:

  • connects to the dairy goat farms milk data
  • interprets this data and gives automatic feedback and alerts
  • has a built-in rationing tool, that allows ration calculation taking milk results into account
  • has a built-in economy module, that allows easy calculation of economic KPI’s by automatic import of milk results.

Wim Govaerts (Wim Govaerts & co) contributed to the workshop by giving an agronomic basis for  the algorithms behind Farmdesk. Wim is co-founder of Farmdesk and an experienced agricultural advisor. During the demo, there were lots of discussion and feedback from the farmers.

Niels van Middelkoop (Dairy goat farmer in Horssen, The Netherlands) ended the workshop by giving personal experiences on using milk data to improve technical performance. First, he discussed what he measures, how it is measured, and why it is so important. Next, he discussed his views on interpreting milk ureum, milk fat and milk protein. He gave some real-life examples on decisions that led to higher yields and higher net profits.