Electrical resistivity of the soil can be considered as a proxy for the spatial and temporal variability of many other soil physical properties (i.e. structure, water content, or fluid composition). Because the method is non-destructive and very sensitive, it offers a very attractive tool for describing the subsurface properties without digging. It has been already applied in various contexts like : groundwater exploration, landfill and solute transfer delineation, agronomical management by identifying areas of excessive compaction or soil horizon thickness and bedrock depth, and at least assessing the soil hydrological properties. The surveys, depending on the areas heterogeneities can be performed in one-, two-or three-dimensions and also at different scales resolution from the centimetric scale to the regional scale. In this review, based on many electrical resistivity surveys, we expose the theory and the basic principles of the method, we overview the variation of electrical resistivity as a function of soil properties, we listed the main electrical device to performed one-, two-or three-dimensional surveys, and explain the basic principles of the data interpretation. At least, we discuss the main advantages and limits of the method.

-STICS (Simulateur mulTJdiscplinaire pour les Cultures Standard) is a crop model constructed as a simulation tool capable of working under agricultural conditions. Outputs comprise the production (amount and quality) and the environment. Inputs take into account the climate, the soi1 and the cropping system. STICS is presented as a model exhibiting the following qualities: robustness, an easy access to inputs and an uncomplicated f~~t u r e evolution thanks to a modular (easy adaptation to various types of plant) nature and generic. However, STICS is not an entirely new model since most parts use classic formalisms or stem from existing models. The main simulated processes are the growth, the development of the crop and the water and nitrogenous balance of the soil-crop system. The seven modules of STICSdevelopment, shoot growth, yield components, root growth, water balance, thermal environment and nitrogen balanceare presented in tum with a discussion about the theoretical choices in comparison to other models. These choices should render the model capable of exhibiting the announced qualities in classic environmental contexts. However, because some processes (e.g. ammoniac volatilization, clrought resistance, etc.) are not taken into account, the use of STICS is presently limited to several cropping systems. (

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In most current farming system classifications (e.g. "conventional" versus "organic"), each type of farming system encompasses a wide variety of farming practices and performances. Classifying farming systems using concepts such as "ecological", "sustainable intensification" or "agro-ecology" is not satisfactory because the concepts "overlap in…def-initions, principles and practices, thus creating…confusion in their meanings, interpretations and implications". Existing classifications most often focus either on biotechnical functioning or on socio-economic contexts of farming systems. We reviewed the literature to develop an original analytical framework of the diversity of farming systems and agriculture models that deal with these limits. To describe this framework, we first present the main differences between three biotechnical types of farming systems differing in the role of ecosystem services and external inputs: chemical input-, biological inputand biodiversity-based farming systems. Second, we describe four key socio-economic contexts which determine development and functioning of these farming systems: globalised commodity-based food systems, circular economies, alternative food systems and integrated landscape approaches. Third, we present our original analytical framework of agriculture models, defined as biotechnical types of farming systems associated with one or a combination of socio-economic contexts differing in the role of relationships based on global market prices and "territorial embeddedness". We demonstrate the potential of this framework by describing six key agriculture models and reviewing key scientific issues in agronomy associated with each one. We then analyse the added value of our analytical framework and its generic character. Lastly, we discuss transversal research issues of the agriculture models, concerning the technologies required, their function in the bioeconomy, their multi-criteria and multilevel assessments, their co-existence and the transitions between them.