This report compiles country-reports that describe the agri-food research landscape in 2006/2007 in 33 countries associated to the 6th Framework Programme (FP6), which defined the European for the period from 2002 to 2006. Each country-report presents information about the main research players in 2006/2007 and about the current trends and the future needs for research topics and for the organisation of the agri-food research system.
This document provides a review of existing reports regarding the agri-food research landscape in 2006/2007 for 14 EU countries (Bulgaria, Croatia, Cyprus, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Romania, Slovakia, Slovenia, Turkey) and also explores trends and needs in other EU or associated countries (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Israel, Italy, Luxembourg, Norway, Portugal, Spain, Sweden, Switzerland, The Netherlands, United Kingdom).
The ‘Mapping Report’ is the synthesis of the statistical information and the survey results available to describe agrifood research in European countries. The main source of information was the results of a bibliometric analysis (in the EU-33 countries), a web-assisted survey (in the EU-12+2 countries) and the country reports (for the EU-15 countries) prepared in the AgriMapping project frame in 2006 and 2007. When relevant, available complementary statistics were also used.
This report presents the results of a study that shall contribute to provide information on the national organisation of agricultural research and an overall picture of developments in agricultural research in 33 selected countries (current EU28 plus Iceland, Israel, Norway, Switzerland and Turkey). The study covers all areas related to agricultural and food research research including research dedicated to emerging challenges of the European agricultural and food sector in 2006/2007.
L’une des avancées les plus importantes dans le domaine de l’observation de la terre est la découverte des indices spectraux, ils ont notamment prouvé leur efficacité dans la caractérisation des surfaces agricoles, mais ils sont généralement définis de manière empirique. Cette étude basée sur l’intelligence artificielle et le traitement du signal, propose une méthode pour trouver un indice optimal. Et porte sur l’analyse d’images issues d’une caméra multi-spectrale, utilisée dans un contexte agricole pour l’acquisition en champ proche de végétation.
Cet article présente une nouvelle approche à base de logique floue pour évaluer le risque phytosanitaire dans une serre produisant des roses. Le but de cette étude est de fournir à l’agriculteur un indice représentant le risque de présence de nuisible : Western Flower Thrips (WFT) ou Frankliniella Occidentalis, et d’enlever la phase decomptage manuel. Un systéme d’aide à la décision modulaire basé sur la connaissance d’experts a été conçu. Le systéme proposé fournit un facteur de risque en fonction des données météorologiques et statiques.
Boll guard I & II were introduced in 2002 and 2006 by Mahyco Monsanto with Genetic Engineering Appraisal Committee, Govt. of India. Indian cotton farmers adopted Bt hybrid cotton between 2002-2013 reaching 92% of the cotton area and 95% of the production, replacing conventional hybrids/ varieties of all the species in both rainfed and irrigated conditions. Bt hybrid cotton was presumed to produce record highest average productivities in India and other major cotton growing countries also in 2007 and 2012 with a decline after 2008 due to excess rains. Farmers invested Rs.
La stratégie de Lisbonne met en avant la nécessité de stimuler la croissance et de créer des emplois dans les zones rurales, elle vise à renouveler les bases de la compétitivité européenne, à augmenter son potentiel de croissance ainsi que sa productivité et à renforcer la cohésion sociale en misant principalement sur la connaissance, l’innovation et la valorisation du capital humain.
The purpose of this Guidance Note is to help countries to assess the quality of public spending on science, technology, and innovation (STI). It adopts a results-oriented framework, combining the consolidation of STI expenditures with the analysis of their main outputs, intermediate outcomes, and developmental impact. The framework proposes the analysis of three main sources of deficiencies: (i) program design/implementation; (ii) institutional conditions; and the (iii) composition and level of public expenditure.
This data article contains annotation data characterizing Multi Criteria Assessment (MCA) Methods proposed in the agri-food sector by researchers from INRA, Europe's largest agricultural research institute (INRA, https://institut.inra.fr/en). MCA can be used to assess and compare agricultural and food systems, and support multi-actor decision making and design of innovative systems for crop production, animal production and processing of agricultural products.