Improvement of an event detection tool (reproductive, sanitary, malfunction) in a herd of dairy cows and several groups of sows

Job Type: 
Stage Master 2

Context & Team

Precision farming tools now allow individual and automated tracking of dairy cows and sows. This follow-up, combined with the breeder's observations, can lead to an earlier detection of a large number of events in which a breeder's response is required (calving, health problems, malfunction). The UMR PEGASE validated connected water troughs able to record individual water consumption. From these water consumption data, an analysis method made it possible to detect disturbances related to health, reproduction or technical dysfunction events. This method is more than 95% specific for cows and sows, however its sensitivity is at best around 70% for cows and remains lower for sows (<50%). The objective of this internship is to improve this method of identifying disturbances. The main hypothesis of this internship is that certain variables are dependent on each other (eg amount of water consumption and amount of feed ingested for cows) and that the structure of dependence between these variables will change during a disturbance event. The combined study of the dependent variables should make it possible to improve the sensitivity of our method of identifying disturbances. This internship will be carried out at INRAE UMR PEGASE, Saint-Gilles, in collaboration with UMR GenPhySE from INRAE and will be co-supervised by a nutritionist researcher in cattle breeding (Anne Boudon, PEGASE), a nutritionist-modeler researcher in pig breeding (Charlotte Gaillard, PEGASE) and a statistician researcher (Tom Rohmer, GenPhySE). A follow-up committee of the internship will bring together researchers competent in the physiological regulations of water consumption and in the processing of dynamic data in livestock.


At the beginning of the internship, the databases will be available as well as a first version of an event detection program based on a differential smoothing method. The first step of the internship will consist in determining pairs of dependent variables specific to each species. The second step will consist of improving the event detection process by applying it to these pairs. This internship proposal has been submitted to the call “AAP Master 2 #DIGITAG”, Institute Convergences Digital Agriculture, ).

Profile & level required

Master 2 or last year of Engineer school, competences in animal sciences, in statistics and R.

Encadrement et personne à contacter

Anne Boudon, Charlotte Gaillard, Tom Rohmer. Contact :

Place of work & conditions

Place of work: INRAE, UMR Pegase – 16 le Clos – 35590 Saint-Gilles, France. On-site corporate restaurant. Duration and starting date: 6 months from the 1st of February 2022. Internship compensation based on the INRAE standard rate (around 550 euros per month).


Tom Rohmer

Tom dot Rohmer at inra dot fr