Foisonnement de l'innovation agricole : quelques exemples d'initiatives en élevage herbivore

Les témoignages rassemblés pour illustrer le foisonnement des innovations agricoles émanent d'acteurs différents (agriculteurs, recherche, développement) mais sont tous caractérisés par des approches plutôt systémiques et des dynamiques de co-conception. Les thèmes abordés concernent la production (valorisation des surfaces avec des cultures dérobées, sélection d'espèce prairiales locales), l'appropriation de résultats de recherche (amélioration de la gestion des prairies), la conception d'itinéraires techniques (solutions pour limiter les pertes d'azote en rotation prairie - prairie), l'évaluation de systèmes (repérer des pratiques innovantes en mobilisant des principes de l'agroécologie) mais aussi l'amélioration des conditions de travail et la formation (communication « intergénérationnelle » entre des paysans herbagers et des élèves)

Shared Research Questions On Soil Quality In Organic Farming Systems

"In 2018, a participatory national workshop was organized by ITAB (Organic Food and Farming Technical Institute) and INRA (National Institute for Agricultural Research) in order to highlight issues on soils in Organic Farming (OF) systems. The objectives were: i) to identify the key research questions to be addressed on soils in OF, ii) to make it possible to facilitate network and project building from interactions between academics and stakeholders.Over 150 participants from academic and professional origins attended the workshop which was designed according to The Town Hall Meeting (THM) methodology.High level discussions among participants and panel experts ended up with a list of 20 research questions which confirmed the important lack of knowledge on that topic and the needs for research on the following issues: soils functioning with a focus on biogeochemical cycling and biological interactions; long term effects of agricultural practices, more or less specific to OF; soils protection; tools for soils diagnosis and management.

The value of manure - Manure as co-product in life cycle assessment

Research ArticleLivestock production is important for food security, nutrition, and landscape maintenance, but it is associated with several environmental impacts. To assess the risk and benefits arising from livestock production, transparent and robust indicators are required, such as those offered by life cycle assessment. A central question in such approaches is how environmental burden is allocated to livestock products and to manure that is re-used for agricultural production. To incentivize sustainable use of manure, it should be considered as a co-product as long as it is not disposed of, or wasted, or applied in excess of crop nutrient needs, in which case it should be treated as a waste. This paper proposes a theoretical approach to define nutrient requirements based on nutrient response curves to economic and physical optima and a pragmatic approach based on crop nutrient yield adjusted for nutrient losses to atmosphere and water. Allocation of environmental burden to manure and other livestock products is then based on the nutrient value from manure for crop production using the price of fertilizer nutrients. We illustrate and discuss the proposed method with two case studiesinfo:eu-repo/semantics/publishedVersio

The Kerbernez long-term experiment: A dataset on crop yield and soil organic matter evolution in forage crop rotations and permanent grasslands in a temperate oceanic climateData Gouv

Forage crop rotations including grasslands, common in dairy systems, are known to ensure good productivity and limit the decrease of soil organic matter frequently observed in permanent arable land. A dataset was built to compile data from the Kerbernez long-term experiment, conducted in Brittany(France) from 1978 to 2005. This experiment compared the effect of different forage crop rotations fertilized with ammonium nitrate and/or slurry, with or without grassland, on forage production (quantity, quality) and changes in soil physio-chemical characteristics. These forage crop rotations were based on silage maize and cut monospecific grasslands of Italian ryegrass (Lolium multiflorum L.) or perennial ryegrass (Lolium perenne L.). More precisely, the experiment compared silage maize monocultures, rotations with silage maize and Italian ryegrass established for 6 to 18 months, and rotations with silage maize and perennial ryegrass established for three to more than 10 years. They are representative of the forage crop rotations and permanent grasslands that were at the heart of Brittany's forage revolution in the 1970s. The dataset includes information about the climate and soil conditions, the management of crops and grasslands, the evolution of topsoil organic carbon and nitrogen stocks, the inter-annual variations in crop and grassland dry matter yields and nitrogen contents. The dataset also includes characterisation of soil structural stability, particle-size soil organic matter fractions and potential soil carbon and nitrogen mineralisation at the end of the trial. It consists of fourteen csv files. This dataset can be used for a variety of purposes, namely for assessing the ability of mechanistic models to simulate soil organic matter dynamics and associated fluxes, and to estimate the influence of grassland presence and duration in forage crop rotations on such fluxes

Evaluation of SPOT imagery for the estimation of grassland biomass.

International audienc

Agricultural practices in grasslands detected by spatial remote sensing

International audienceThe major decrease in grassland surfaces associated with changes in their management that has been observed in many regions of the earth during the last half century has major impacts on environmental and socio-economic systems. This study focuses on the identification of grassland management practices in an intensive agricultural watershed located in Brittany, France, by analyzing the intra-annual dynamics of the surface condition of vegetation using remotely sensed and field data. We studied the relationship between one vegetation index (NDVI) and two biophysical variables (LAI and fCOVER) derived from a series of three SPOT images on one hand and measurements collected during field campaigns achieved on 120 grasslands on the other. The results show that the LAI appears as the best predictor for monitoring grassland mowing and grazing. Indeed, because of its ability to characterize vegetation status, LAI estimated from remote sensing data is a relevant variable to identify these practices. LAI values derived from the SPOT images were then classified based on the K-Nearest Neighbor (KNN) supervised algorithm. The results points out that the distribution of grassland management practices such as grazing and mowing can be mapped very accurately (Kappa index = 0.82) at a field scale over large agricultural areas using a series of satellite images