MISTEA: Mathematics, Informatics, STatistics for Environment and Agronomy

modelling – simulation – big data – ontologies – knowledge representation – databases – decision support – environment – microbial ecosystems – population dynamics – ecosystems – resources preservation – food industry – phenotype – climate change – sustainable plants and trees management – agro-food and environmental process management

The Joint Unit Research MISTEA brings to #DigitAg its expertise in mathematical modeling and simulation for understanding and decision support in agriculture;Optimization in particular for precision farming; design and production of Information systems for massive information; Analysis of multi-scale and temporal data in agriculture.

 Research axis #DigitAg:  4 – 5 – 6 
 Contact the MISTEA Staff

One of the challenges for MISTEA is to develop digital models based on observations for understanding and decision-making for topics of Agriculture and the environment.  For this purpose are used mathematics,Statistics in data processing and validation, as well as information technologies for the processing of masses of data. The systems studied are dynamic, complex and often require the development of adapted tools to the problem studied

.The unit is structured in two teams that work in complementarity:

GAMMA team (Management, Analysis and Models for Data in Agronomy)

It aims at the development of automated data processing toolsWhich are massive, heterogeneous and complex.In particular, one of the specificities of the team is the taking into account of the dimension of data and their evolutionary character at different scales and interaction with the environment.

The GAMMA team is a part of the phenotyping infrastructure Phenome, as well as the LACCAVE project, which focuses on the impacts of Climate in viticulture and oenology.

MOCAS Team

The research activities of the MOCAS team focus on thedevelopment of deterministic and stochastic mathematical methodsfor the analysis and management of agro-ecosystems. The work ofThe modeling, simulation and optimization ofDynamical systems representing the functioning of agro-ecosystems.This work is based on collaborations withresearch in agronomy, ecology and sylviculture.