PhD researcher "Data-based modelling of recovery from mastitis in dairy cows"
For Bioengineering Technology TC, Technology Campus Geel we are looking for a Optimization and intensification of livestock production is widely encouraged to meet the increasing demands for livestock products and to contribute to improving the livelihoods of rural households. To this end, sustainable animal production which guarantees welfare for both the animal and the farmer requires automation of the production process in combination with thorough health monitoring of the individual animals. The research team “Livestock Technology”, under the lead of Prof. Ben Aernouts, develops, implements and validates innovative sensor technology and data processing algorithms to support the animal management in livestock production. Our research lab is hosted by the KU Leuven Technology campus in Geel, located in a green and rural environment, in close collaboration with the industry and the livestock sector.
Udder health is the most important factor affecting theincome of modern dairy farmers. However, good management limits the impact ofmastitis, and so, mastitis losses are very farm-dependent. A key factor affectingthese differences is the consequent and profound monitoring of the udder healthstatus on farm.
Online measured milk parameters contain information on theudder health status, and are potentially very valuable to monitor infection andcure. However, to extract this information reliably and to interpret the datacorrectly, advanced data management techniques are needed. Using smart datatechniques, combining different parameters and their physiology-basedbackground, explicit information can be extracted from the data, in which theimpact of each mastitis case on the udder tissue, the milk losses and sufferingof the cow can be quantified. This information can be conferred with thecurrent management and the administered treatments to give feedback and aconcrete plan concerning mastitis to the farmers.
The goal of this project is (1) to quantify therelation between milk losses and the (mastitis) management; (2) to optimize andvalidate a model based on milk parameters to quantify the udder health status,including recovery and cure.
This job comes from a partnership with Science Magazine and