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 AgroParisTech

Welcome to ECOSYS

UMR ECOSYS - Ecologie fonctionnelle et écotoxicologie des agroécosystèmes

Exposé : CN-Wheat_RBARILLOT

Exposé
Romain BARILLOT, Camille CHAMBON & Bruno ANDRIEU

CN-Wheat: a Functional-Structural Plant Model of CN Metabolism in Wheat

 

The model proposed here, called CN Wheat, is based on a fully mechanistic approach for the integration of Carbon (C) and Nitrogen (N) metabolisms within wheat plants. CN Wheat is defined at culm scale; the crop is represented as a population of individual culms that compete for light and soil N. Culm structure is composed of a root compartment, a set of photosynthetic organs and the grains. Each module includes structural, storage and mobile materials. Fluxes of C-N among modules take place through a common pool and/or through the transpiration flow. The modelled physiological activities are the acquisition of C and N, the synthesis and degradation of primary metabolites, C respiration, C-N exudation and tissue growth and death. A central role is given to metabolite concentrations as drivers of physiological activities. Thus, the integration within the plant results from that all processes act in parallel on interconnected metabolite pools, which is represented as a set of differential equations. Model behavior was evaluated against a field experimentation with three N fertilizations applied at anthesis. For each N treatment, CN-Wheat accurately predicted the post-anthesis kinetics of (i) C-N distribution among organs, (ii) green areas of laminae and (iii) dry mass and N content of grains. Whereas the use of response functions to metabolite concentration is accepted for each of the processes described in the model, here we show that it can be used for an integrative modelling of the whole plant.

Document à télécharger (sécurisé)