HarvestChoice cofounders and principal investigators Stanley Wood and Philip Pardey discuss our mission, our data challenge, and four signature aspects of our innovative approach to more productive and profitable farming in Sub-Saharan Africa.
Two for the Price of One: Training Crop Pest Modelers While Building New Maps
To improve our collective capacity to model and measure the economic costs of pests, weeds and diseases of the major food crops of the world, CSIRO and HarvestChoice-UMN are delivering a series of ecological modeling workshops.
Lablab, Egyptian Bean or Pulse? Reclassifying Crops for SPAM Conformity
Picture it. You're working at HarvestChoice processing incoming crop statistics and you come across some figures for harvested area of dolichos in Kenya.
A group of researchers from the University of Nebraska and Wageningen University are setting out to determine just that through the production of an atlas.
International Association of Agricultural Economists 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia
Pages:
16
Abstract
In order to evaluate food security, technology potential and the environmental impacts of production in a strategic and regional context, it is critical to have reliable information on the spatial distribution and coincidence of people, agricultural production, and environmental services.
Among various ways to sequester CO2 from the atmosphere, increasing soil carbon is an option that could also lead to increased agricultural productivity, especially in developing countries.
HarvestChoice/International Food Policy Research Institute (IFPRI)
Years Covered:
2010 - 2030
Lowest Geographic Unit:
Country
Abstract
Comparative static model used to estimate long-term aggregate potential yield gains and aggregate potential poverty reduction effects from narrowing yield gaps for selected commodities in selected regions. The model allows for differentiated yield gap closure and technology adoption scenarios in focus and non-focus countries and for focus and non-focus crops. The model also accounts for varying "poverty-productivity" elasticities across commodities (a synthetic measure linking productivity gains and poverty reduction).
