This document is on the Programma sull'Innovazione e lo Sviluppo Agroindustriale (PISA), which is an international program whose general objective is to support innovative projects of agroindustrial development aimed at generating value-added and employment in the rural sector of developing countries.
This is a chapter of the book Innovation platforms for agricultural development edited by Iddo Dror, Jean-Joseph Cadilhon, Marc Schut, Michael Misiko and Shreya Maheshwari.
As calls for bolstering environmental services on croplands have grown more insistent during the past two decades, the search for ways to foster sustainable, reduced input agriculture has become more urgent. In this context authors re-examine by means of a meta-analysis the argument, first proposed by Robert McC. Netting, that small scale, mixed crop – livestock farming, a common livelihood among poor rural peoples, encourages environmentally sustainable agricultural practices.
This paper describes the learning selection approach to enabling innovation that capitalizes on the complexity of social systems at different scales of analysis. The first part of the paper describes the approach and how it can be used to guide the early stages of setting up a “grassroots” innovation process. The second part of the paper looks at how the learn selection model can be used “top-down” to guide research investments to trigger large-scale systemic change.
Rapid appraisal of agricultural innovation systems (RAAIS) is a participatory, diagnostic tool for integrated analysis of complex agricultural problems. RAAIS facilitates interaction between different groups of stakeholders in collecting and analysing data. The poster briefs what RAAIS is, when to use it, what is available and where it has been used.
Research, extension, and advisory services are some of the most knowledge-intensive elements of agricultural innovation systems. They are also among the heaviest users of information communication technologies (ICTs). This module introduces ICT developments in the wider innovation and knowledge systems as well as explores drivers of ICT use in research and extension.
The presentation was given in January 2009 and introduced why a new approach for livestock development for poverty alleviation was desirable, innovation, innovation systems and value chains, building of innovation platforms, learning-oriented monitoring and evaluation, and scaling up and out.
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).
This assessment has been conducted over December 2015 to May 2016 under the Powering Agriculture Support Task Order (PASTO). PASTO is funded by USAID and implemented by Tetra Tech ES, Inc. PASTO provides support services to the Powering Agriculture: An Energy Grand Challenge for Development (PAEGC) and its Founding Partners to enable their effective management, monitoring and evaluation of the program.
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.