The objective of this study is to evaluate the ability of soil physical characteristics (i.e., texture and moisture conditions) to better understand the breeding conditions of desert locust (DL). Though soil moisture and texture are well-known and necessary environmental conditions for DL breeding, in this study, we highlight the ability of model-derived soil moisture estimates to contribute towards broader desert locust monitoring activities.
Smallholder farmers in East Africa need information and knowledge on appropriate climate-smart agriculture (CSA) practices, technologies, and institutional innovations in order to effectively adapt to changing climatic conditions and cope with climate variability. This paper assesses farmer adoption of climate-smart agricultural practices and innovation after being exposed to Farms of the Future Approach (FotF). First; we explore and assess the various CSA technologies and practices; including institutional innovations farmers are adopting.
The challenge of food security in Nigeria hinges on several factors of which poor technical efficiency is key. Using a stochastic frontier framework, we estimated the technical efficiency of agricultural households in Nigeria and tested for the significance of mean technical efficiency of food-secure and food-insecure agricultural households. We further assessed the determinants of agricultural households’ inefficiencies within the stochastic frontier model and adopted a standard probit model to assess the determinants of households’ food security status.
This study examines the influence of farmers’ social capital on their decisions to deal with climate change and climate variability in Burkina Faso. The study is based on a household survey conducted among 450 households, randomly selected from three communities in Burkina Faso.
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).
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.
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.
The creative process that leads to farmers’ innovations is rarely studied or described precisely in agricultural sciences. For academic scientists, obvious limitations of farmers’ experiments are e.g. precision, reliability, robustness, accuracy, validity or the correct analysis of cause and effect. Nevertheless, we propose that ‘farmers’ experiments’ underpin innovations that keep organic farming locally tuned for sustainability and adaptable to changing economic, social and ecological conditions.
This paper shows there is a fundamental significance of Social Learning to agricultural innovation, which can be operationalized by framing agricultural innovation as changes in understanding, practices and relationships. The use of Social Learning as a design framework supports the emergence of agricultural innovations that bring equitable benefits, are sustainable and are innovated in context.