Economic development and the successful transformation ofagriculture have been at the core of impressive change in countriessuch as China, India, Indonesia, Brazil, Mexico, and Argentina. This transformation has relied on substantial and effective investment inagriculture, and, in particular, building capacity in all aspects of agricultural change – from technology development and transfer through infrastructural development and the processing of agricultural commodities into consumer products.
Con las nuevas demandas de la sociedad hacia las organizaciones de investigación para contribuir con mayor énfasis a los procesos de innovación, comienza a configurarse una nueva visión sobre el rol de la extensión en el conjunto de procesos innovadores.
The impact of the COVID-19 pandemic will vary for different groups of rural population, with the highest impact expected to be on farmers and other vulnerable groups, especially women and youth. Targeted support is feasible only by activating a network of actors or organizations within agricultural innovation systems (AIS) and promoting customized technologies and practices suitable for location specific contexts.
Agricultural transformation and development are critical to the livelihoods of more than a billion small-scale farmers and other rural people in developing countries. Extension and advisory services play an important role in such transformation and can assist farmers with advice and information, brokering and facilitating innovations and relationships, and dealing with risks and disasters.
The use of technology in agriculture plays an important role in the production chain cycle, as well as in the improvement of processes and productivity. To develop a model for measuring the technological capacity of family agriculture systems, it is necessary to assess the gaps related to indicators and the technological potentialities of these farmer groups, which are often not considered when they require financial support and do not get enough. Thus, the aim of this study is to identify the indicators used to evaluate the technological capacity of farm systems and agriculture.
L’article analyse en quoi et comment la recherche peut être un vecteur de renforcement des dynamiques collectives des territoires par la méthode participative ImpresS (Impact des recherches au Sud). Celle-ci qualifie la façon dont la recherche accompagne les processus d’innovation et y contribue, et la façon dont elle renforce les actions collectives par la création de nouveaux espaces de dialogue et d’échanges entre les chercheurs et les parties prenantes d’un projet d’indication géographique (IG).
Breeding programs for local breeds kept by small farmers in developing countries are a major challenge. Animal recording of pedigree and performance under conditions of subsistence livestock farming is remain difficult or next to impossible. This means that standard genetic evaluations, as well as selection and planning of mating based on estimates of the animals' genotypes, cannot be done at any level in the population of the target breed or genetic group.
These initiatives generated transformative and lasting results and contributed to the strengthening of local public policies and economic growth. Using very few resources and focusing on agroecological and inclusive production methods, these women have become role models in their communities and beyond. Empowered women can participate more actively in their communities and foster inclusive local policies that will ultimately drive more sustainable and just rural development.
This flyer expresses the idea that Agricultural knowledge, science and technology (AKST) cannot be achieved through business as usual and that nstitutions are needed that can drive efforts in the face of unprecedented challenges. The discussed key questions are: How have institutions shaped the development of AKST? What are their impacts on sustainable and equitable development? Which institutional arrangements have the greatest potential to drive and deliver sustainability and development goals?
Georeferenced data are a key factor in many decision-making systems. However, their interpretation is user and context dependent so that, for each situation, data analysts have to interpret them, a time-consuming task. One approach to alleviate this task, is the use of semantic annotations to store the produced information. Annotating data is however hard to perform and prone to errors, especially when executed manually. This difficulty increases with the amount of data to annotate.