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: https://www.ghostery.com/fr/products/

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: http://www.youronlinechoices.com/fr/controler-ses-cookies/, 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

Realytics
Google Analytics
Spoteffects
Optimizely

Targeted advertising cookies

DoubleClick
Mediarithmics

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 cil-dpo@inra.fr or by post at:

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

Dernière mise à jour : Mai 2018

Menu Logo Principal Institut Agro - Agrocampus Ouest

Home page

Post-doctoral position

08 July 2021

Sensitivity analysis of the INRA 2018 feeding system for ruminants.

Research unit

UMR1213 Herbivores is a joint research unit associating INRAE and VetAgroSup. It is situated in Theix, near Clermont-Ferrand, in the Center of France, in one of the main mountain agricultural regions in Europe. UMRH employs about 120 permanent staff and 80 temporary staff and students, and is connected with facilities in 3 locations in Auvergne (Herbipole experimental Unit). UMRH conducts research on cattle and sheep, and their production systems. The Unit has a strong expertise on digestion and CH4 emissions, animal welfare, feeds value, and product qualities. Its work contributes to the design of sustainable farming systems for herbivores that seek to reconcile production efficiency, product quality and socio-economic viability with environmental protection and valuation, and animal welfare. Although mainly located at UMRH (Clermont-Ferrand-Theix), the work will be done in strong collaboration with other INRAE units, mainly UMR Pegase (Rennes) but also UMR MoSAR (Paris) and UMR Selmet (Montpellier).

Context

The model of the INRA 2018 feeding system for ruminants (https://doi.org/10.3920/978-90-8686-292-4) improves the estimation of animal responses to diets and proposes new predictions. The system allows various rationing strategies to be considered by seeking compromises between different objectives, i.e. milk and meat production, management of body reserves, efficiency of protein use…(https://www.inration-ruminal.fr/). It also allows evaluating various other responses of the animal to the diet supplies (e.g. N and CH4 emissions into the environment, risk of acidosis, product composition). These advances were possible for a part because the estimation of the different nutrient supplies by the diet was improved. The reference methods for estimating nutrient supply require the use of animals with permanent digestive cannulas (rumen and/or duodenum) to insert nylon bags and monitor the degradation of incubated feed ("in sacco" methods). With a view to stopping the use of this practice in the short term, the Alterfi project was launched by the INRAE PHASE Division.
Alternative laboratory methods are currently being developed, with the aim that they may eventually replace in sacco methods. At the same time, it is essential to assess the necessary degree of accuracy (or acceptable inaccuracy) on these feed value parameters to ensure sufficient accuracy in the estimation of animal responses to diets, compared to measurements on experimental facilities and/or observation on farms. This work will make it possible to assess alternatives to in sacco measurements in the feeding system.

Objectives and work program of the post-doctoral fellow

The post-doctoral will perform sensitivity analyses of the different animal responses to uncertainty in the estimation of feed values. He/she will have the opportunity to train (or develop his knowledge) on the INRA 2018 feeding system, including both estimation of feed values and animal’s responses to diets. He will use a high throughput simulation application allowing to test the sensitivity of the model to the uncertainties on feed values, on a wide range of nutritional scenarios. He/she will develop datasets required to the tests (enter of the model), and will thus interpret the output of the simulations. This will be done in strong interaction with the different researchers involved in the development of the INRA 2018 system in Theix, Rennes, Paris and Montpellier. The work will first be focused on dairy cows, then on beef cattle, and lastly on small ruminants. The post-doctoral will write a scientific publication based on the main results of this work.

Required qualifications - Candidate skills

Good knowledge of the R statistical software is required. Experience in statistical sensitivity analysis would be useful. The candidate must be able to learn the concepts of the INRA 2018 model, thus previous experience with feeding systems (preferably ruminants) would be a valuable asset. The candidate must be able to work in a network and to report on its results.

Reception conditions

How to apply

Send a motivation letter and CV to :

  • Pierre NOZIERE : pierre.noziere[at]inrae.fr - + 33 (0) 4 73 62 46 86
  • Sophie LEMOSQUET : sophie.lemosquet[at]inrae.fr - + 33 (0) 2 23 48 50 85
  • Tristan SENGA KIESSE : tristan.senga-kiesse[at]inrae.fr - + 33 (0) 2 23 48 54 25

See also