Nigeria : Food Smart Country Diagnostic
This study of Nigeria food loss and waste (FLW) analyzes the potential policy impacts of reducing FLW along the value chain for three strategically selected commodities: maize, tomatoes, and catfish. The study takes into account the differences bet...
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World Bank, Washington, DC
2020
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Online Access: | http://documents.worldbank.org/curated/en/703791601302657183/Nigeria-Food-Smart-Country-Diagnostic http://hdl.handle.net/10986/34522 |
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okr-10986-345222021-05-25T09:58:34Z Nigeria : Food Smart Country Diagnostic World Bank FOOD SECURITY NUTRITION FOOD LOSS AND WASTE MAIZE FOOD SYSTEM ENVIRONMENTAL SUSTAINABILITY CATFISH TOMATO DEMOGRAPHIC TRENDS This study of Nigeria food loss and waste (FLW) analyzes the potential policy impacts of reducing FLW along the value chain for three strategically selected commodities: maize, tomatoes, and catfish. The study takes into account the differences between food-producing regions of the north (a poor, rural, closed economy challenged by civil conflict) and largely food-consuming regions of the south (an open economy with an increasingly urbanized population). The study found that reducing FLW for all three commodities will allow Nigeria to address key policy priorities, chief among them improving food security. Other priorities include improving rural, low-income farmer welfare; meeting Nigeria’s international commitments to reduce global greenhouse gas emissions produced by food waste; increasing food exports; and reducing food imports while satisfying the nation’s large urbanized population’s shift towards a more diversified diet. 2020-09-28T18:17:30Z 2020-09-28T18:17:30Z 2020-09-28 Report http://documents.worldbank.org/curated/en/703791601302657183/Nigeria-Food-Smart-Country-Diagnostic http://hdl.handle.net/10986/34522 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 Nigeria |
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 NUTRITION FOOD LOSS AND WASTE MAIZE FOOD SYSTEM ENVIRONMENTAL SUSTAINABILITY CATFISH TOMATO DEMOGRAPHIC TRENDS |
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FOOD SECURITY NUTRITION FOOD LOSS AND WASTE MAIZE FOOD SYSTEM ENVIRONMENTAL SUSTAINABILITY CATFISH TOMATO DEMOGRAPHIC TRENDS World Bank Nigeria : Food Smart Country Diagnostic |
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Africa Nigeria |
description |
This study of Nigeria food loss and
waste (FLW) analyzes the potential policy impacts of
reducing FLW along the value chain for three strategically
selected commodities: maize, tomatoes, and catfish. The
study takes into account the differences between
food-producing regions of the north (a poor, rural, closed
economy challenged by civil conflict) and largely
food-consuming regions of the south (an open economy with an
increasingly urbanized population). The study found that
reducing FLW for all three commodities will allow Nigeria to
address key policy priorities, chief among them improving
food security. Other priorities include improving rural,
low-income farmer welfare; meeting Nigeria’s international
commitments to reduce global greenhouse gas emissions
produced by food waste; increasing food exports; and
reducing food imports while satisfying the nation’s large
urbanized population’s shift towards a more diversified diet. |
format |
Report |
author |
World Bank |
author_facet |
World Bank |
author_sort |
World Bank |
title |
Nigeria : Food Smart Country Diagnostic |
title_short |
Nigeria : Food Smart Country Diagnostic |
title_full |
Nigeria : Food Smart Country Diagnostic |
title_fullStr |
Nigeria : Food Smart Country Diagnostic |
title_full_unstemmed |
Nigeria : Food Smart Country Diagnostic |
title_sort |
nigeria : food smart country diagnostic |
publisher |
World Bank, Washington, DC |
publishDate |
2020 |
url |
http://documents.worldbank.org/curated/en/703791601302657183/Nigeria-Food-Smart-Country-Diagnostic http://hdl.handle.net/10986/34522 |
_version_ |
1764481095093452800 |