La télédétection des infrastructures agro-écologiques : de la promesse aux méthodes opérationnelles (Tél-IAE)

Les infrastructures agro-écologiques comme les haies et les bandes enherbées sont des éléments paysagers clé pour la biodiversité dans les territoires agricoles. Les cartographier est une étape importante pour évaluer la qualité des paysages et prédire l’impact d’aménagements. La télédétection spatiale présente un potentiel important pour atteindre cet objectif à coût raisonnable et sur une surface importante. Le projet « télédétection des infrastructures agroécologiques » regroupant spécialistes de la télédétection et utilisateurs s’est proposé d’évaluer des méthodes existantes dans des cas variés et d’en développer de nouvelles. Un site web présentant les résultats du projet guide l’utilisateur vers des grands types d’options techniques en fonction de son projet et lui donne accès à diverses ressources. La pleine appropriation des méthodes et outils implique toutefois un décloisonnement des métiers au delà des considérations purement techniques

Predicting quantitative host plant resistance against phoma black stem in sunflower

International audiencePhoma black stem is an important disease in sunflower, against which no specific management method is currently deployed in France. Relevant phenotyping methods for quantitative resistance are critical for integration of this trait into breeding programmes. Components of resistance associated with physiological resistance, and morphological traits associated with disease escape were measured on 21 sunflower genotypes under growth chamber (on seedlings), green- house (on adult plants), and field conditions, together with disease intensity in the field. Potential predictors were first selected for sensitivity and robustness from mixed model ANOVA s. Analyses involving ranking tests and logistic regres- sions were then performed to identify predictors for field resistance. The identification of predictors for resistance involved analyses conducted in two broad steps: process-oriented experiments, and epidemic-oriented experiments. This stepwise approach departs from many studies aimed at identifying predictors for field resistance, which rely mainly on the computation of correlation coefficients between predictors and measured field disease variables. Predictors for quan- titative resistance were identified: (i) lesion length and lesion expansion on stems of plants before flowering stage, and (ii) lesion length on first leaf petioles of seedlings. A high number of leaves and tall plants were associated with disease escape. Control genotypes for susceptibility and quantitative resistance were identified, and implications for breeding and improvements were derived from this work

Improving access to research outcomes for innovation in agriculture and forestry: the VALERIE project

Many excellent results are obtained in agricultural and forestry research projects. but their practical adoption is often limited. The aim of the European project VALERIE is to increase the transfer and application of innovations produced by research in agriculture and forestry, by facilitating their integration into management practices. The project is still ongoing and the results illustrated in this paper are still temporary and subject to being improved. Here we present the methodology used in VALF,RIE to extract and summarise knowledge for innovation from research documents with the aim of making it available to final users through ask-Valerie.en; we also report on current progress. The tasks associated with extracting and summarising knowledge are centred on: i) an ontology; ii) a document base; and iii) a system (ask-Valerie.eu) that allows users to effectively search the document base. An ontology defines a set of concepts and the relations between them. The VALERIE ontology is built by experts in the agricultural and forestry domain and contains 6169 concepts (21st October 2016). The document base is the collection of documents in which the system searches. The VALERIE document base includes scientific and practical documents derived from various sources, Written in any of a number of languages. All documents contained in the document base are annotated using the ontology: each term (a word or a short phrase) in the document that matches a concept in the VALERIE-ontology is linked to that concept. Annotation is an automated process that takes place whenever a document is added to the document base. The document base contains 4278 documents (October 2016). Among them, there are 201 minifactsheets written by members of the VALERIE project, each describing an innovation with: a short description of the innovation, a list of correlated projects, and some links to scientific and practical documents. ask-Valerie.eu searches documents and fragments of text from the document base that address the user's query. ask-Vaterie.cu mimics the dialogue between a practitioner and an expert and achieves this functionality by: i) supporting the practitioner in articulating the question (it completes terms that the user starts to type and suggests other possibly relevant terms); ii) expanding the query using synonyms; iii) extracting and ranking text fragments from the documents