We use cookies to track visits to this website. We do not store personal details. If you continue to browse this website, you are allowing all third-party services.

Manage your cookies preferences

The cookies we use allow us to count visits and traffic sources, so we can measure and improve the performance of our site. They help us know which pages are the most and least popular and see how visitors move around the site. All information these cookies collect is aggregated and therefore anonymous. If you do not allow these cookies, we will not know when you have visited our site.

Authorize Prohibit

Drone sur champs de vigne

Digital agriculture

Predictive and decisional life sciences engineering

Update : 06/26/2018

Digital and biotechnological revolutions allow the development of new predictive and decisional approaches in the life sciences which are indispensable for efforts to design, develop and steer future biological systems, particularly in a context of sustainable agriculture. New technologies renew our ability to explore the living world, rendering possible the acquisition of biological and environmental data with unprecedented spatial and temporal resolution - from the gene to the watershed, via the cell, organism, field and farm.

The challenge is to develop, design and implement new approaches and methods, drawing from disciplinary and professional knowledge, which can be used to characterize and model phenomena whose complexity has been hitherto difficult to grasp. This strategy also aims to create tools for representation, diagnosis, assessment and decision support covering a wide range of applications...

It also seeks to design new, complex systems by integrating different forms of knowledge to innovate with regard to the type and size of equipment, the development of new crop systems, the creation of varieties that meet new constraints, etc.

This requires:

  • Understanding the structure and functioning of the living world at its different levels of organization
  • Designing new approaches and methods to data acquisition and mining, analysis of “big data”
  • Developing decision-support and assessment tools

For Montpellier SupAgro, the response to these challenges requires a multidisciplinary approach that includes engineering, biological, social and economic sciences. The approach is oriented towards the production of results "for action" adapted to actors’ needs. The approach is part of a training-research-innovation continuum.

  • Focus on...


Montpellier SupAgro
2 place Pierre Viala
34060 Montpellier - France
Tél. : +33 (0)4 99 61 22 00 Tél. : +33 (0)4 99 61 22 00
Fax : +33 (0)4 99 61 29 00

Under the aegis of :

Member of :

Founder of :