Know more

Our use of cookies

Cookies are a set of data stored on a user’s device when the user browses a web site. The data is in a file containing an ID number, the name of the server which deposited it and, in some cases, an expiry date. We use cookies to record information about your visit, language of preference, and other parameters on the site in order to optimise your next visit and make the site even more useful to you.

To improve your experience, we use cookies to store certain browsing information and provide secure navigation, and to collect statistics with a view to improve the site’s features. For a complete list of the cookies we use, download “Ghostery”, a free plug-in for browsers which can detect, and, in some cases, block cookies.

Ghostery is available here for free:

You can also visit the CNIL web site for instructions on how to configure your browser to manage cookie storage on your device.

In the case of third-party advertising cookies, you can also visit the following site:, offered by digital advertising professionals within the European Digital Advertising Alliance (EDAA). From the site, you can deny or accept the cookies used by advertising professionals who are members.

It is also possible to block certain third-party cookies directly via publishers:

Cookie type

Means of blocking

Analytical and performance cookies

Google Analytics

Targeted advertising cookies


The following types of cookies may be used on our websites:

Mandatory cookies

Functional cookies

Social media and advertising cookies

These cookies are needed to ensure the proper functioning of the site and cannot be disabled. They help ensure a secure connection and the basic availability of our website.

These cookies allow us to analyse site use in order to measure and optimise performance. They allow us to store your sign-in information and display the different components of our website in a more coherent way.

These cookies are used by advertising agencies such as Google and by social media sites such as LinkedIn and Facebook. Among other things, they allow pages to be shared on social media, the posting of comments, and the publication (on our site or elsewhere) of ads that reflect your centres of interest.

Our EZPublish content management system (CMS) uses CAS and PHP session cookies and the New Relic cookie for monitoring purposes (IP, response times).

These cookies are deleted at the end of the browsing session (when you log off or close your browser window)

Our EZPublish content management system (CMS) uses the XiTi cookie to measure traffic. Our service provider is AT Internet. This company stores data (IPs, date and time of access, length of the visit and pages viewed) for six months.

Our EZPublish content management system (CMS) does not use this type of cookie.

For more information about the cookies we use, contact INRA’s Data Protection Officer by email at or by post at:

24, chemin de Borde Rouge –Auzeville – CS52627
31326 Castanet Tolosan CEDEX - France

Dernière mise à jour : Mai 2018

Menu Logo Principal Oniris

Home page

Clément Pierre

Informative value of general activity and rumination time for the detection of health disorders and phenotyping in dairy cows

abstract :

In recent years, many monitoring tools have been developed to assist farmers in detecting physiological (calvings, heats) or pathological (mastitis) events. The aim of this Ph.D. thesis was to generate knowledge on the interest of general activity and rumination time measured by a sensor designed for dairy cow monitoring (HR-Tag, SCR Engineers Ltd, Israel), or of alarms generated based on these data.
First of all, the interest of rumination time for dry matter intake prediction during lactation was investigated. The addition of rumination time to an existing dry matter intake prediction model (NRC 2001) significantly improved the prediction, but the gain was not sufficient to enable accurate intake phenotyping. Then, the informative value of alarms generated from activity and rumination data for the detection of health disorders was evaluated. Three complementary reference methods were used successively to determine the health status of the cows: detection of health disorders by visual appraisal by farm staff, identification of major drops in milk production and clinical veterinarian examination of the animals.
The results of this work show that even if heat alarms triggered by the monitoring device are reliable, the performance of the algorithms developed are not good enough for farmers to delegate entirely health disorders detection to the alarm system.

Key words :

Dairy cattle, health monitoring, precision dairy farming, epidemiology, algorithms, cusum, rumination, activity