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Using a linear discriminant analysis approach of baseline conditions to develop household categories in the Sudan Savanna ( KKM PLS SSA CP ), Nigeria

dc.contributor.authorOlarinde, L.O.
dc.contributor.authorAbdoulaye, Tahirou
dc.contributor.authorKamara, A.
dc.contributor.authorBinam, J.
dc.contributor.authorAdekunle, A.
dc.date.accessioned2019-12-04T11:10:26Z
dc.date.available2019-12-04T11:10:26Z
dc.date.issued2010
dc.identifier.citationOlarinde, L.O., Abdoulaye, T., Kamara, A., Binam, J. & Adekunle, A. (2010). Using a linear discriminant analysis approach of baseline conditions to develop household categories in the Sudan savanna (KKM PLS SSA CP), Nigeria. Journal of Food, Agriculture & Environment, 8(2), 805-812.
dc.identifier.issn1459-0255
dc.identifier.urihttps://hdl.handle.net/20.500.12478/2137
dc.description.abstractTo address the problem of the continued deterioration of livelihood and food security in the sub Saharan Africa, the Forum for Agricultural Research in Africa (FARA) through the sub Saharan Africa Challenge Programme (SSA CP) is implementing the Integrated Agricultural Research for Development (IAR4D). The IAR4D is a multistakeholder agricultural research approach which is currently being implemented at Pilot Learning Sites (PLSs) in three regions of Africa: (I) the Kano-Katsina-Maradi (KKM) PLS in West Africa, (2) the Lake Kivu (LK) PLS in East and Central Africa and (3) the Zimbabwe-Malawi-Mozambique (ZMM) PLS in Southern Africa. The objective of this paper was to employ some baseline data of the Sudan Savanna Task Force of the KKM PLS in West Africa, in a linear discriminant analysis to investigate some of the factors that characterised the farmers based on some starting conditions. The study was also to show whether the farmers that have been baselined have common characteristics that can hypothetically separate them on the basis of belonging to three distinct groups for the implementation of the IAR4D. The sampled respondents were initially classified into three groups of baseline farmers. The grouping was done on the basis of whether the farmers are IAR4D (intervention) or conventional (ARD) or clean sites farmers. This is necessary for the end line survey and for the impact evaluation of the programme. Data on a sub-sample of 300 baselined respondents were used for analysis (92-IAR4D/intervention farmers, 96-ARD/conventional farmers and 112-clean farmers). Results indicated an overall rate of 99% of farmers correctly classified into their respective sites. A number of indicative baseline variables (about 67% of the hypothesized variables) which can be regarded as those which distinguish farmers into those which predictably belong to IAR4D/intervention farmers, ARD/conventional farmers and clean farmers were identified to be significantly important. The different villages chosen for the program evaluation are also correctly identified within their groups. Therefore, three distinct categories of villages are available for evaluating the programme impact.
dc.description.sponsorshipEuropean Union
dc.description.sponsorshipDepartment for International Development, United Kingdom
dc.description.sponsorshipGovernment of Italy
dc.description.sponsorshipGovernment of Norway
dc.format.extent805-812
dc.language.isoen
dc.subjectDiscriminant Analysis
dc.subjectLegumes
dc.subjectGrain Legumes
dc.subjectFood Security
dc.subjectLivelihoods
dc.subjectIntegrated Agriculture
dc.titleUsing a linear discriminant analysis approach of baseline conditions to develop household categories in the Sudan Savanna ( KKM PLS SSA CP ), Nigeria
dc.typeJournal Article
dc.description.versionPeer Review
cg.contributor.affiliationAhmadu Bello University
cg.contributor.affiliationInternational Institute of Tropical Agriculture
cg.contributor.affiliationForum for Agricultural Research in Africa
cg.coverage.regionAfrica
cg.coverage.regionWest Africa
cg.coverage.countryNigeria
cg.identifier.urlhttp://www.isfae.org/scientificjournal.php
cg.isijournalISI Journal
cg.authorship.typesCGIAR and developing country institute
cg.iitasubjectCapacity Development
cg.iitasubjectGrain Legumes
cg.iitasubjectLivelihoods
cg.journalJournal of Food, Agriculture & Environment
cg.howpublishedFormally Published
cg.accessibilitystatusLimited Access
local.dspaceid90708
cg.targetaudienceScientists


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