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Article: A spatial explicit assessment of food security in Africa based on simulated crop production and distribution

TitleA spatial explicit assessment of food security in Africa based on simulated crop production and distribution
Authors
KeywordsAfrica
Crop
Crop Choice Decision Model (CCDM)
Food security
GEPIC model
Undernourished population
Issue Date2017
Citation
Journal of Cleaner Production, 2017, v. 147, p. 628-636 How to Cite?
AbstractThe continent of Africa has the highest prevalence of hunger and poverty in the world. In this paper, an Environmental Policy Integrated Climate (EPIC) model combined with a Crop Choice Decision Model (CCDM) is applied to simulate the production and spatial distribution of rice, wheat, millet, maize, sorghum and cassava in Africa from 1993 to 2012 converted into calories. From this, we calculate the size of the undernourished population according to the Average Dietary Energy Requirement index of the Food and Agriculture Organization of the United Nations (FAO) and study the trends experienced in different countries. The results show that (1) the distribution of different crops has a horizontal zonality from north to south; (2) although the distribution of different crops in Africa did not change significantly from 1993 to 2012, the total crop planting area declined, especially in the middle part of Africa; (3) the undernourished population has increased, while the proportion of undernourished people decreased; and (4) land tenure reform and international food aid has made a great contribution to improved food security in Africa. A GIS-based EPIC (GEPIC) model combined with a CCDM can enable the spatial explicit assessment of food security and the microscopic study of food security on large scale, providing more accurate decision-making information for policy makers.
Persistent Identifierhttp://hdl.handle.net/10722/333260
ISSN
2023 Impact Factor: 9.7
2023 SCImago Journal Rankings: 2.058
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, Huan-
dc.contributor.authorZhang, Xiaoling-
dc.date.accessioned2023-10-06T05:17:57Z-
dc.date.available2023-10-06T05:17:57Z-
dc.date.issued2017-
dc.identifier.citationJournal of Cleaner Production, 2017, v. 147, p. 628-636-
dc.identifier.issn0959-6526-
dc.identifier.urihttp://hdl.handle.net/10722/333260-
dc.description.abstractThe continent of Africa has the highest prevalence of hunger and poverty in the world. In this paper, an Environmental Policy Integrated Climate (EPIC) model combined with a Crop Choice Decision Model (CCDM) is applied to simulate the production and spatial distribution of rice, wheat, millet, maize, sorghum and cassava in Africa from 1993 to 2012 converted into calories. From this, we calculate the size of the undernourished population according to the Average Dietary Energy Requirement index of the Food and Agriculture Organization of the United Nations (FAO) and study the trends experienced in different countries. The results show that (1) the distribution of different crops has a horizontal zonality from north to south; (2) although the distribution of different crops in Africa did not change significantly from 1993 to 2012, the total crop planting area declined, especially in the middle part of Africa; (3) the undernourished population has increased, while the proportion of undernourished people decreased; and (4) land tenure reform and international food aid has made a great contribution to improved food security in Africa. A GIS-based EPIC (GEPIC) model combined with a CCDM can enable the spatial explicit assessment of food security and the microscopic study of food security on large scale, providing more accurate decision-making information for policy makers.-
dc.languageeng-
dc.relation.ispartofJournal of Cleaner Production-
dc.subjectAfrica-
dc.subjectCrop-
dc.subjectCrop Choice Decision Model (CCDM)-
dc.subjectFood security-
dc.subjectGEPIC model-
dc.subjectUndernourished population-
dc.titleA spatial explicit assessment of food security in Africa based on simulated crop production and distribution-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.jclepro.2017.01.124-
dc.identifier.scopuseid_2-s2.0-85013821595-
dc.identifier.volume147-
dc.identifier.spage628-
dc.identifier.epage636-
dc.identifier.isiWOS:000395602600057-

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