Journal of Food, Agriculture and Environment

Using a linear discriminant analysis approach of baseline conditions to develop household categories in the Sudan savanna (KKM PLS SSA CP) ^1†, Nigeria

Author(s):

Luke O. Olarinde ^1*, Tahirou Abdoulaye ², Alpha Kamara ², Joachim Binam ¹, Adewale Adekunle ³

Recieved Date: 2009-11-16, Accepted Date: 2010-04-13

Abstract:

To 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 (SSACP) 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: (1) 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.

Keywords:

Discriminant analysis, Integrated Agricultural Research for Development (IAR4D), Kano-Katsina-Maradi (KKM), Sudan savanna, Nigeria

---

Journal: Journal of Food, Agriculture and Environment
Year: 2010
Volume: 8
Issue: 2
Category: Agriculture
Pages: 805-812

---

Full text for Subscribers

---

Information:

Note to users

The requested document is freely available only to subscribers/registered users with an online subscription to the Journal of Food, Agriculture & Environment. If you have set up a personal subscription to this title please enter your user name and password. All abstracts are available for free.

Article purchasing

If you like to purchase this specific document such as article, review or this journal issue, contact us. Specify the title of the article or review, issue, number, volume and date of the publication. Software and compilation, Science & Technology, all rights reserved. Your use of this website details or service is governed by terms of use. Authors are invited to check from time to time news or information.

---

Purchase this Article:   20 Purchase PDF Order Reprints for 15

---

Share this article :