FFAST aims at describing wheat genotypes functioning through an innovative model-assisted phenotyping strategy. Currently, studies on field phenotyping are mostly focused on exploiting directly structural traits observations (e.g. leaf area, height) to establish statistical models with genetic characteristics. However, structural traits are highly determined by the environment, and such empirical models are insufficient to describe genotypes functioning. FFAST proposes an alternative approach using functional plant models (FPM, also known as crop process-based models) to describe the eco-physiological mechanisms that produce a differentiated response of the genotype to the environment (GxE). This model-assisted strategy consists in assimilating large observational datasets of multiple structural traits over different growing environments to retrieve, for each genotype, a set of varietal parameters of a FPM. These varietal parameters describe the genotype functioning and constitute functional traits, closely linked to its genetic characteristics. The model-assisted phenotyping method will be evaluated in a panel of ten bread wheat genotypes that will be monitored on phenotyping experiments and by satellite. The phenotyping experiments will be conducted in the Toulouse, Clermont-Ferrand and Montpellier sites –part of the PHENOME-EMPHASIS phenotyping infrastructure– during three years. That will permit to acquire high-throughput observations of multiple structural traits (leaf area, canopy height, heading date, ears density…) in different environments. Nevertheless, as a large environmental variability is essential to retrieve accurately functional traits, FFAST will investigate the use of high-resolution satellite platforms to provide additional cost-efficient observations of structural traits for specific genotypes over contrasted environments. Three genotypes of the panel will be monitored by satellite on 40 distant commercial fields over a climatic gradient in eastern France. Images from Sentinel 2 and PlanetScope satellite constellations will be used to retrieve frequent observations of some essential traits like the leaf green area index (GAI) and the fraction of absorbed photosynthetically active radiation (fAPAR). The estimation of functional traits from the observations will rely on a data assimilation framework based on the Sirius Quality FPM, specifically developed for wheat, which will be linked to the architectural model Adel Wheat. This will permit to improve the description of structure-driven processes such as light interception/absorption or evapotranspiration. Bayesian Monte Carlo methods will be used to retrieve varietal parameters of Sirius Quality from the structural traits observations for each genotype. The resulting posterior distribution of varietal parameters for all the genotypes will be analysed to identify those parameters –or groups of parameters characterizing the same mechanism– presenting statistically different posterior distributions among genotypes. Those parameters will constitute functional traits. The approach proposed by FFAST will be validated evaluating the reliability of the functional traits identified to predict the genotype performance in different environments from those used during the assimilation. This will permit to evaluate as well the role of remote sensing observations over different environments in the FFAST approach, compared to expensive multi-site phenotyping experiments. The project results will be disseminated through scientific papers in different domains: phenomics, eco- physiology, crop modelling and remote sensing. The observational datasets collected for the 10 genotypes will be also made public through a data paper. Moreover, the development of a methodology to produce multi-constellation GAI and fAPAR observations suitable for plant phenotyping will permit HIPHEN –enterprise partner in FFAST– to open new commercial services.

In the context of agriculture increasingly relying on groundwater irrigation, it is crucial to develop reliable and applicable methods for assessing the sustainability of agricultural systems under climate change. A wide variety of models have been developed for ex-ante evaluation of management policies or assessment of the impacts of land-use changes. They are commonly used to support decision making by stakeholders through participatory approaches. However, due to the difficulty in implementing truly trans-disciplinary projects, the models rarely represent both the complex biophysical processes at stake in agricultural watersheds and the farmer adaptation strategies to changes. Consequently, these models are not able to adequately account for the spatial and temporal interactions and feed-backs between these two components. The Indian context is an extreme case where the integration of these components is both essential and challenging: the “groundwater revolution” which started three decades ago and induced a well identified “groundwater crisis” with tremendous impacts on water resources and ecosystems, is being carried out by millions of very small farmers owning individual borewells, with a large diversity of practices and strategies. The ATCHA project aims to accompany the adaptation of farming systems to climate change by combining an integrated biophysical model with a participatory approach in a network of experimental watersheds in the Karnataka state. Through a truly trans-disciplinary approach, involving hydrologists, geochemists, soil scientists, agronomists, geographers, economists and sociologists and with a strong participation of Indian partners including scientists, extension service agents and stakeholders, we aim at demonstrating the ability of integrated models to share knowledge between researchers and stakeholders and to co-build and assess scenarios of sustainable development of agriculture. The ATCHA project is based on (1) the strong partnership initiated with the International Joint Laboratory IFCWS (Indo-French Cell for Water Sciences, involving the Indian Institute of Science, Bangalore) which allowed to build an extensive database in the Berambadi experimental watershed (Critical Zone Observatory, ORE BVET) and (2) a specific Indo-French project (CEFIPRA AICHA, 2013-2016) in which an integrated model combining hydrology (AMBHAS), agronomy (STICS), economy (MoGire) and farmer decision (Namaste) models was developed. The ATCHA project will complement the Sujala III project (2014-2019), led by the Karnataka Watershed Department and in which IFCWS takes part in the coordination of the monitoring carried out in 14 experimental watersheds across the Karnataka state. The ATCHA project is composed of 3 work packages (in addition to the coordination WP): i) development of novel methodologies to gather spatialized information on soils and land use, using both ground and multi-satellite data at high spatial and temporal resolution ii) improvement of the model realism by calibrating a large number of tropical crops and bridging knowledge gaps for modelling nutrient cycles in tropical irrigated agro-systems and iii) development of a participatory approach to build and assess scenarios of adaptation to climate change and its critical assessment. We expect the ATCHA project to produce not only significant scientific advances on the functioning of agro-hydrosystems under high anthropogenic pressure but also to have a strong socio-economic impact, in terms of capacity building for the Indian partners (in particular for crop and agro-system modelling), improving the relevance of advice given to farmers by extension services and the efficiency of public policies.

The CHLOR2NOU project aims to develop new monitoring tools for CLD and its TPs, to provide new knowledge on the fate and risk of CLD TPs, and to explore realistic alternative approaches for pollution remediation. The postulate of the non-degradability of CLDs commonly admitted for several decades has had a strong negative impact on pollution management by ruling out the possibility of CLD degradation. The representation of CLD in the FWI society and in the scientific community is therefore of paramount importance. The CHLOR2NOU project is divided into 7 Work Packages that bring together scientists from various background: the WP1 with the synthesis of CLD TPs, CLD baits and fluorescent macromolecular cages; the WP2 that deals with innovative analytical methods: (i) routine laboratory method for the detection of CLD TPs in environmental and food matrices, (ii) immunoassay using a CLD-selective antibody, (iii) a semi-high-throughput detection protocol based on the recognition of CLD by a fluorescent macromolecular cage; the WP3 dedicated to toxicological and ecotoxicological studies in order to define the toxicity profile of CLD TPs; the WP4 with several analytical campaigns to obtain a first estimate of the possible exposure to CLD TPs; the WP5 that aims at studying the fate of CLD TPs, in particular in FWI soils, while defining degradation indicators; the WP6 that is focused on the study of realistic agronomic and environmental conditions capable to favor CLD degradation; the last WP centered on the representation of CLD in the FWI society at large. A co-construction method will be used to help the population and stakeholders to better assimilate the scientific results.

The effects of increasing global temperatures on soil biodiversity and the resulting effects on the coupling/decoupling of biogeochemical C, N, P cycles are poorly understood. This project attempt to assess the biodiversity and functional composition of soil microbial communities, including soil fauna (earthworms) and plant-soil interactions responses to soil warming using three whole soil warming experiments established in France, USA and China. We will focus our study on whole soil profiles, as in particular subsoil horizons may have a large temperature response to warming and could release carbon to the atmosphere as positive feedback mechanism. The information obtained through the data generated by our project will be used to benchmark an existing simulation model, which includes representation of soil depth, transport, and microbial physiology of functional guilds. The simulations outcomes can then support the formulation of policies to promote adaptation and mitigation strategy.

Ever-increasing waste production has prompted the need for new provisions regarding waste management to ensure sustainable development. There is now a global consensus among scientists, economists, politicians and civil society stakeholders on the necessity to recycle resources and close loops in a circular economy. Agricultural recycling makes it possible to effectively and synergistically use livestock, urban and agro-industrial organic waste (OW). From a waste management standpoint, aerobic digestion (composting) and anaerobic digestion are the most obvious and operational processes for OW treatment prior to soil application. Composting OW is seen as an effective method for diverting organic materials from landfills, while reducing the waste volume, eliminating pathogens and creating a stable product suitable for application in crop fields. Anaerobic digestion has also significantly increased in several European countries and represents an opportunity to convert OW into biogas and organic fertilizer (digestate). The choice of using either raw OW, compost or digestate as fertilizer and soil amendment should be based on a comprehensive assessment of potential benefits and negative effects. Among these negative effects, the lack of understanding regarding the impact of treatments on contaminant speciation, microbial pathogen selection and antimicrobial resistance emergence, and the scarcity of knowledge on the fate of contaminants following soil OW application are key scientific challenges that the DIGESTATE project aims to meet. The overall objective of DIGESTATE is to develop an original environmental assessment of OW treatments and agricultural recycling. Such environmental assessment involves estimation of environmental consequences (positive and negative) expected to result from OW treatment and recycling scenarios prior to decision making. This assessment will include indicators which are: (i) conventional (agronomic quality of the OW; energy recovery of treatment processes) and (ii) non-standard (fate of contaminants following OW application in water-soil-plant systems). We will focus our efforts on the ecodynamics of three main classes of contaminants in water-soil-plant systems: (i) trace elements: Cu and Zn, (ii) organic pollutants: PAHs, nonylphenols and pharmaceuticals and (iii) microbial pathogens and antimicrobial resistance genes. We will compare the impact of two major digestion treatments (composting, anaerobic digestion and their combination) on: (i) the speciation of organic and inorganic contaminants, the selection of particular microbial groups and genetic properties in OW, and (ii) the fate (phytoavailability and transport in soil) of contaminants after soil OW application. The scientific programme is based on laboratory experiments, modeling tools and multidisciplinary approaches. First, contaminant quantification and speciation will be assessed for selected raw and treated OW (WP1). Then fundamental knowledge will be produced on contaminant-bearing phases formed during OW treatment (WP2). After OW spreading on a soil, the proportion of contaminants taken up by plants or transported through the soil will be experimentally quantified (WP3). The experimental and modelling datasets from WP1, 2 and 3 will finally fuel the environmental assessment of OW treatment and recycling based on innovative assessment methodologies (WP4).