Chapter 6 Homegardens and the future of food and nutrition security in southwest Uganda Published in Agricultural Systems, March 2017 * Cory W. Whitney a,b,c , John R.S. Tabuti d , Oliver Hensel e , Ching-Hua Yeh f , Jens Gebauer a , Eike Luedeling b,c a Faculty of Life Sciences, Rhine-Waal University of Applied Sciences, Marie-Curie-Straße 1, Kleve 47533, Germany b World Agroforestry Center (ICRAF), United Nations Avenue, Gigiri, Nairobi, Kenya c Center for Development Research (ZEF), University of Bonn, Walter-Flex-Straße 3, Bonn 53113, Germany d Makerere University, College of Agricultural and Environmental Sciences, P.O. Box 7062, Kampala, Uganda e Department of Agricultural Engineering, Faculty of Organic Agricultural Sciences, University of Kassel, Nordbahnhofstr. 1a, Witzenhausen 37213, Germany f Department of Agricultural and Food Market Research, University of Bonn, Nussallee 21, Building 2, Bonn 53115, Germany Keywords Monte Carlo, decision support, probabilistic simulations, cropping systems, uncertainty, EVPI Abstract Governments around the world seek to create programs that will support sustainable agriculture and achieve food security, yet they are faced with uncertainty, system complexity and data scarcity when making such choices. We propose decision modeling as an innovative approach to help meet these challenges and offer a case study to show the effectiveness of the tool. We use decision analysis tools to model the possible nutrition-related outcomes of the Ugandan government’s long-term agricultural development termed ‘Vision 2040’. The analysis indicates potential shifts in household nutritional contributions through the comparison of the current small-scale diverse systems and the envisioned industrial agricultural systems that may replace them. A Monte Carlo simulation revealed that Vision 2040 plans outperform homegardens in terms of energy and some macronutrients, yet homegardens are likely to be better at producing key vitamins and micronutrients, such as Vitamin A. Value of information calculations applied to Monte Carlo outputs further revealed that gathering more data on * Formatted, in part, according to the Agricultural Systems Author Guidelines https://www.elsevier.com/journals/agricultural-systems/0308-521x/guide-for-authors