This report outlines AIIM-Assist activities performed under four components (management of the annual program statement process, building the capacity of AIIM grantees and finalists, technical assistance to other USAID missions in Feed the Future focus countries, technical support to African regional partners outside of AIIM), and highlights qualitative and quantitatvie achievements between August 6, 2012 and November 4, 2016.
The organization of the Nutrition Innovation Labs represents a novel model for focusing U.S.- supported research on food and nutrition issues in developing countries. Their aims are to discover how policy and program interventions can most effectively achieve large-scale improvements in maternal and child nutrition, particularly by leveraging agriculture and build human and institutional capacity for applied policy analysis, research and program implementation.
The Agribusiness and Market Development (AMDe) project is funded through USAID Ethiopia’s Feed the Future program from June 2011 to May 2016. It goal is to sustainably reduce poverty and hunger by improving the productivity and competiveness of agricultural value chains that offer jobs and income activities for rural households.
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.
The Cold Chain Bangladesh Alliance (CCBA) aims to increase the availability, access, and use of domestically‐produced and nutritious foods in an effort to sustainably reduce poverty and hunger.
To ensure that Feed the Future impact evaluations are well-conceived, build on existing evidence, and fill critical evidence gaps, the Bureau for Food Security of USAID is supporting a comprehensive assessment of existing evidence and gaps in knowledge for each of six themes covered by the Feed the Future Learning Agenda. This paper summarizes available evidence that relates to key questions for the Feed the Future Learning Agenda theme on improved gender integration and women’s empowerment.
The Women’s Leadership Program in Paraguay is a three-year (2012-2015) higher education partnership between the National University of Asuncion’s School of Agricultural Sciences in Paraguay and the University of Florida (UF) in the United States.The program supports national and local development goals in Paraguay that promote gender equality and female empowerment in the agricultural sector.
Feed the Future Asia Innovative Farmers Activity (AIFA) is a regional project working to facilitate the scaling of critical agricultural technologies through regional partnership and technology transfer. The project works with a range of agricultural technology stakeholders on a regional basis (private sector, research institutions, governments, networks, etc.) to increase food security, reduce poverty, and improve environmental sustainability by facilitating agricultural innovation and technology diffusion in the Asia region.
The Africa Leadership Training and Capacity Building Program (Africa Lead), aims to support the capacity building program of the US Government’s Feed the Future Initiative, which aligns U.S. Government development assistance with Africa-owned agriculture development plans that are, in turn, aligned with the African Union’s Comprehensive Africa Agriculture Development 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.