This study identifies entry points for innovation for sustainable intensification of agricultural systems. An agricultural innovation systems approach is used to provide a holistic image of (relations between) constraints faced by different stakeholder groups, the dimensions and causes of these constraints, and intervention levels, timeframes and types of innovations needed. The authors aim at showing that constraints for sustainable intensification of agricultural systems are mainly of economic and institutional nature.
Poor farmers seldom benefit from new agricultural technologies. In response, research and extension approaches based on agricultural innovation systems are popular. Often agricultural research organisations are the network brokers, facilitating the emergence of the innovation system. Based on an analysis of the Sustainable Modernization of Traditional Agriculture (MasAgro) initiative in Mexico, this viewpoint suggests that such organisations are more often suitable network brokers when the objective is the development and scaling out of a technology by itself.
This paper describes the research path followed by a team of researchers who had investigated the nitrate problem in a case study area, and who became aware of the low impact of their data on the policy debate and on the practices that – as the research team saw it – had given rise to the problem in the first place. They embarked on a series of interactions first with participatory action researchers from the SLIM project (see Fig.
Many small-scale irrigation systems are characterized by low yields and deteriorating infrastructure. Interventions often erroneously focus on increasing yields and rehabilitating infrastructure. Small-scale irrigation systems have many of the characteristics of complex socio-ecological systems, with many different actors and numerous interconnected subsystems. However, the limited interaction between the different subsystems and their agents prevents learning and the emergence of more beneficial outcomes.
In order for agricultural development to fulfill its potential role as a source of growth and reducer of poverty, it must be constantly renewed through knowledge and innovation. Getting resources into the hands of innovators and providing incentives for producers, agricultural service providers, and entrepreneurs to collaborate in developing and applying new methods and technologies is a priority among institutions concerned with agricultural knowledge.
There have been repeated calls for a ‘new professionalism’ for carrying out agricultural research for development since the 1990s. At the centre of these calls is a recognition that for agricultural research to support the capacities required to face global patterns of change and their implications on rural livelihoods, requires a more systemic, learning focused and reflexive practice that bridges epistemologies and methodologies.
The development of effective agricultural monitoring networks is essential to track, anticipate and manage changes in the social, economic and environmental aspects of agriculture. The authors welcome the perspective of Lindenmayer and Likens (J. Environ. Monit., 2011, 13, 1559) as published in the Journal of Environmental Monitoring on their earlier paper, “Monitoring the World's Agriculture” (Sachs et al., Nature, 2010, 466, 558–560).
Understanding spatial patterns of land use and land cover is essential for studies addressing biodiversity, climate change and environmental modeling as well as for the design and monitoring of land use policies. The aim of this study was to create a detailed map of land use land cover of the deforested areas of the Brazilian Legal Amazon up to 2008.
One of the most important challenges for the researchers in the 21st Century is related to global heating and climate change that can have as consequence the intensification of natural hazards. Another problem of changes in the Earth's climate is its impact in the agriculture production. In this scenario, application of statistical models as well as development of new methods become very important to aid in the analyses of climate from ground-based stations and outputs of forecasting models. Additionally, remote sensing images have been used to improve the monitoring of crop yields.
There is increasing evidence that public organizations dedicated exclusively to research and development (R&D) in agribusiness need systematic management tools to incorporate the uncertainties and complexities of technological and nontechnological factors of external environments in its long-term strategic plans. The major issues are: What will be the agribusiness science and technology (S&T) needs be in the future? How to prepare in order to meet these needs?