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



Short description of the tool:

STICS is a soil-crop model which has been developed at INRA (Brisson et al. 1998; Brisson et al. 2002; Brisson et al. 2003; Brisson et al. 2008). It simulates the C, water and N balances of the soil-crop system and can simultaneously estimate agricultural and environmental variables (e.g. crop yield, N content of harvested organs, soil water and mineral N contents).

It was conceived as a generic model able to adapt easily to various kind of crops and environmental conditions. To do so, the specificity of each crop is defined using eco-physiological options (for example, photoperiod action and/or cold requirements on crop phenology) and plant (namely species and cultivar) specific parameters which are delivered with the model and can be used without further parameterization by users.

STICS has two other sets of parameters: a constant set of base parameters used for describing physical and biological processes occurring in the soil-crop system and a set of soil and crop management input parameters that are site specific and are the only ones that must be filled in by the users. Lastly, daily weather variables and the initial values for state variables must be provided to the model for each unit of simulation.

The latest version of the STICS model (v8.2.2) has recently included new developments to tackle emerging societal issues, such as the effect of CO2 concentration on radiation use efficiency or the parameters for energy crops. The effect of high temperatures was implemented since the beginning of model development, such as the simulation of nitrate pollution or N2O emissions (Bergez et al., 2014).

It is one of the tested soil-crop model in the international AgMIP project where 20 to 30 models were used for simulating production in various world countries under IPCC climatic scenarios. The STICS team participated in the work of model inter-comparison for the pilots working on crop production of wheat, rice and maize (Bassu et al. 2014; with colleagues of INRA co-authors) and uncertainties studies (Asseng et al. 2013; with colleagues of INRA co-authors), and also in the FACCE-MACSUR modelling work (publications under construction).