Rwanda : Food Smart Country Diagnostic

The term “food smart” refers to a food system that is efficient, meets the food needs of a country, and is environmentally sustainable. Reducing food loss and waste (FLW) is one of the critical pillars of building a smart food system. This diagnostic focuses on the FLW pillar, from farm to fork t...

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Main Author: World Bank
Format: Report
Language:English
Published: World Bank, Washington, DC 2020
Subjects:
Online Access:http://documents.worldbank.org/curated/en/288911601302842762/Rwanda-Food-Smart-Country-Diagnostic
http://hdl.handle.net/10986/34523
id okr-10986-34523
recordtype oai_dc
spelling okr-10986-345232021-05-25T09:49:57Z Rwanda : Food Smart Country Diagnostic World Bank FOOD SECURITY FOOD SYSTEM FOOD LOSS AND WASTE ENVIRONMENTAL SUSTAINABILITY DEMOGRAPHIC TRENDS GREENHOUSE GAS EMISSIONS TOMATO MAIZE RICE The term “food smart” refers to a food system that is efficient, meets the food needs of a country, and is environmentally sustainable. Reducing food loss and waste (FLW) is one of the critical pillars of building a smart food system. This diagnostic focuses on the FLW pillar, from farm to fork to landfill, with the objective of alerting policymakers to the role that addressing food loss and waste can play in meeting their various global and national policy commitments. Across Sub-Saharan Africa, FLW contributes to food insecurity, reduced income to farmers and communities, and greenhouse gas emissions. In Rwanda specifically, a growing population — set to nearly double to 22 million in the next 30 years — will exacerbate the food security challenge. Even today, undernourishment affects 35.6% of Rwanda’s population, and 36.9% of children are stunted. 2020-09-28T18:25:29Z 2020-09-28T18:25:29Z 2020-09-28 Report http://documents.worldbank.org/curated/en/288911601302842762/Rwanda-Food-Smart-Country-Diagnostic http://hdl.handle.net/10986/34523 English CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank World Bank, Washington, DC Economic & Sector Work Economic & Sector Work :: Other Agricultural Study Africa Rwanda
repository_type Digital Repository
institution_category Foreign Institution
institution Digital Repositories
building World Bank Open Knowledge Repository
collection World Bank
language English
topic FOOD SECURITY
FOOD SYSTEM
FOOD LOSS AND WASTE
ENVIRONMENTAL SUSTAINABILITY
DEMOGRAPHIC TRENDS
GREENHOUSE GAS EMISSIONS
TOMATO
MAIZE
RICE
spellingShingle FOOD SECURITY
FOOD SYSTEM
FOOD LOSS AND WASTE
ENVIRONMENTAL SUSTAINABILITY
DEMOGRAPHIC TRENDS
GREENHOUSE GAS EMISSIONS
TOMATO
MAIZE
RICE
World Bank
Rwanda : Food Smart Country Diagnostic
geographic_facet Africa
Rwanda
description The term “food smart” refers to a food system that is efficient, meets the food needs of a country, and is environmentally sustainable. Reducing food loss and waste (FLW) is one of the critical pillars of building a smart food system. This diagnostic focuses on the FLW pillar, from farm to fork to landfill, with the objective of alerting policymakers to the role that addressing food loss and waste can play in meeting their various global and national policy commitments. Across Sub-Saharan Africa, FLW contributes to food insecurity, reduced income to farmers and communities, and greenhouse gas emissions. In Rwanda specifically, a growing population — set to nearly double to 22 million in the next 30 years — will exacerbate the food security challenge. Even today, undernourishment affects 35.6% of Rwanda’s population, and 36.9% of children are stunted.
format Report
author World Bank
author_facet World Bank
author_sort World Bank
title Rwanda : Food Smart Country Diagnostic
title_short Rwanda : Food Smart Country Diagnostic
title_full Rwanda : Food Smart Country Diagnostic
title_fullStr Rwanda : Food Smart Country Diagnostic
title_full_unstemmed Rwanda : Food Smart Country Diagnostic
title_sort rwanda : food smart country diagnostic
publisher World Bank, Washington, DC
publishDate 2020
url http://documents.worldbank.org/curated/en/288911601302842762/Rwanda-Food-Smart-Country-Diagnostic
http://hdl.handle.net/10986/34523
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