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

Home page

Project presentation

The main objective of the Deffilait project is to provide the essential and necessary elements for improving the feed efficiency of dairy cows through new phenotyping tools.

Presentation

    The livestock sector is highly concerned by the global food system, both by an expected increase in the demand for animal products such as milk, and by the ecological footprint of animal production, which must be minimized. Increasing feed efficiency (FE) in dairy cows would reduce some of the direct emissions (methane and ammonia) from livestock production but would also have a substantial positive impact on the induced emissions associated with crop production, due to the better feed conversion. Genetic improvement of FE is a particularly attractive strategy because it would impact most of the dairy farms for a limited cost. The decreased use of feed inputs implied by such an efficiency gain would give a competitive advantage to dairy production, but will also contribute to reducing environmental impacts. Thus, this project is expected to provide the essential elements needed for genetic selection strategies to improve FE in dairy cows. It fits with the fifth of the major societal challenges of ANR and the first research theme of the Apis-Gene company on FE and limitation of N pollution and methane emission by ruminants to improve the overall efficiency of ruminants. Selecting for FE is not as straightforward as it might first seem, there is evidence to suggest that robustness and adaptive capacity, especially for reproductive females, can be adversely affected by short-sighted strategies to improve efficiency. Thus, the choice of indicators used to assess FE is of great important, and it is essential to verify and validate the anticipated benefits of any such strategies to improve efficiency for their long-term consequences. Another key issue is to be able to better exploit new possibilities to target specific characteristics that contribute in part to FE. Such characters have rarely been studied because they have been very difficult to phenotype. The project will use new phenotyping technologies and the newly available information from them to develop selection for efficient use of body reserves whilst limiting the risks of undesirable trade-offs with other life functions that have been associated with high levels of production in dairy cows. Deffilait aims to elucidate ways by which to improve the FE of dairy cows without decreasing their robustness, to build strategies for doing this, and models to predict the future increases in FE attainableby selection programs, and directly on farm. The project will first involve developing new tools for large-scale phenotyping of the major biological characteristics that are directly involved in FE. Theproject will produce new tools to better estimate body condition, morphology, and digestive efficiency in large scale studies. These phenotypic measures will also impact on our capabilities for on-farm advising, and monitoring in livestock, which are also levers for improving efficiency at farm level. Then, to study the major determinants of FE, the project will also build an original database of dairycow lactations with a large set of phenotypes to describe the main sources of energy transformation, thus explaining the observed between-animal variability in FE. This dataset will then be used to quantify the contribution of the different mechanisms to the variability in FE, and to test different indicators and strategies to improve FE. A specific focus will be made on body reserves mobilization in early lactation to assess its genetic components and correlation with other traits with a larger dataset involving commercial farms. The project will then develop simulation tools to predict the short- and long-term consequences of different selection strategies in different environments. The expected results will contribute to the definition of strategies of selection to combine efficiency and robustness. The project will provide a coherent framework to undertake a balanced genetic selection on these traits, and thereby make a significant - and lasting - contribution to improving FE.

The project was retained by the ANR for a total amount of aid requested of € 703,429 and a duration of 4 years (2016-2019). The project is funded by € 448,000 by ApisGene.