Exploratory projects

The KOMOD consortium project seeks to organize a new multidisciplinary community working on the modelling of complex organisms of agronomic or zootechnical interest. Its core focus is the formalization and encoding of biological information to facilitate the transfer and reconstruction of complex biological processes and encourage convergence between the plant and animal research communities through shared modelling methods and frameworks.

Anaerobic digestion is a key biotechnology for ecological transition, transforming organic waste into renewable biogas. To meet European targets for biomethane production, it is essential to optimize existing production plants by developing hybrid models that integrate 4.0 technologies. The GREMLHINS exploratory project plans to develop hybrid models for anaerobic digestion through the integration of meta-omics data, and to devise a pilot model using available biological samples.

The SEED project expands the Metabolomic Semantic Data Lake (MSD), an electronic infrastructure that combines the Semantic Web with Big Data technologies to enable large-scale processing of the scientific literature on metabolomics. First developed to improve access to knowledge on the links between the metabolism and human health, this infrastructure has now been adapted to include plant metabolisms. SEED will refine its use of artificial intelligence, enabling publications to be annotated automatically through the use of ontologies. The project will also expand the range of sources included in the data lake and will draw on four case studies to validate and illustrate the new associations discovered between metabolites, biomarkers and plants.

Functional-structural (FS) models, developed in several INRAE units, provide dynamic 3D representations of plants. Their detailed representations of a plant’s development and of the competitive relationships that emerge, both within the plant and with the environment, make them an ideal tool for understanding and predicting how trees function in an orchard population.

The genetic selection of animals has been revolutionised over the past years by the advent of genomics, making it easier to select for specific essential phenotypes. Nevertheless, the task of understanding the links between observed genetic variations and phenotypic characteristics of interest remains complex. The OBAMA interdisciplinary project proposes to combine AI with genomics to improve our understanding of the influence of genetic factors on phenotypes in pigs.

The control of continuous fermentation during production is a major challenge for manufacturers of fermented vegetable juice drinks. With its proposed development of a digital twin that can continuously predict and control the plant fermentation process, the FermenTwin project could provide food technologies with a valuable solution.

A better understanding of how gonadal cells decode intracellular signalling is essential if we are to improve and better control reproduction.

Understanding how plants defend themselves against pathogens is a major challenge for moving towards an agriculture that uses fewer pesticides.

Today, agriculture faces many challenges, including to avoid the development of certain pathogens resulting from the reduction in the use of inputs with a view to sustainable agriculture as well as the effects of climate change. In this context, many questions arise in the short term about the adaptive capacities of these bio-aggressors. Will an insect pest resist the next heat wave? Or will it instead be greatly affected by rising temperatures and cease to be a threat ?

Emerging arboviruses (e.g. Zika, West Nile virus) represent a global threat to human and veterinary public health. Mostly of zoonotic origin, these viruses are transmitted to vertebrate hosts by arthropod vectors, such as mosquitoes or ticks.