Digitising the Dairy Production Chain

Digitalising steps of the early dairy production chain to improve forage production, feed mixture and management, stable operations and resource efficiency.

 

Concept 

The European dairy sector is currently undergoing a progressive modernisation process, in which digital technologies are becoming increasingly important. Hence, this Flagship Innovation Experiment (FIE) aims to digitise different steps of the early dairy production chain by improving the forage production, feed mixtures and management, stable operations and general resource planning.

To boost the sector to become more cost-efficient and sustainable, the benefits of previously underutilised data, as well as digital technologies, are exploited. This, however, requires a smart use and integration of multiple data sources, models and analytics while incorporating vital knowledge and expertise. Increasing the sustainability of the production processes whilst at the same time improving the profitability of dairy farms with high health and welfare standards is an essential part of this FIE’s services offering to farmers and their cooperatives.

The inherent improvement in the monitoring and management operations and conditions in dairy cattle farms results in more efficient use of natural resources, and thus contributes to an overhaul of the European agricultural sector.

Implementation 

       

Smart mixer that allows the optimization of the mix of forages for a better dairy yield from beef

The FIE operated in the Granxa Campus Terra Experimental Farm and two maize crop plots located on CIAM experimental farm.

The study was carried out for crops, as maize crops, in several small plot trials located on CIAM experimental farm. Relevant environmental, soil and aerial data were collected from different sources. Aerial data was collected from drones. The data was then processed in order to build algorithms for the prediction of crop production and quality based on multispectral images obtained in the critical stages of the development of summer crops, mainly corn.  A decision-making system to optimize organic fertilization of forage for dairy production has been developed, with very high performance. Two classifications were taken into account in order to offer farmers the possibility to maximize production or maximize crude protein based on their needs. It is viable to train the decision-making system using only field measurements that are supposed to be gathered by farmers every year. There is no need to use data gathered from drone flights, so the cost for the farm is considerably reduced.

Lessons Learnt 

One of the main challenge encountered was data harmonization. It has been a challenge of to harmonize the different files, in order to build strong databases for the partners that applied AI in their developments.