Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/6825
Title: DETERMINANTS OF ARABLE CROP PRODUCTIVITY UNDER THE GORONYO IRRIGATION PROJECT, NORTH-WEST NIGERIA
Authors: Mohammed, U. S
Baba, K.M
Nmadu, J.N
Olaleye, R.S
Keywords: Irrigation
Arable crops
productivity indices
data envelopment analysis
Issue Date: 2017
Abstract: The study evaluated the determinants of arable crop productivity under the Goronyo irrigation project located in the North-Western Nigeria. Multi-stage sampling technique was used to select 246 farmers from whom data were collected with the aid of an interview schedule. Descriptive statistics such as mean, frequency tables and percentages were used to describe the socioeconomic characteristics of the farmers. Data envelopment analysis (DEA) approach was used to obtain the productivity indices for the major arable crop and ordinary least squares regression model was used in evaluating the factors that determine productivity. The results revealed mean age, formal schooling and irrigation experience of 43, 2,5 and 7 years, respectively. The mean household size was five persons. Furthermore, mean farm size in hectares of the irrigation farmers was highest in rice (0.9) compared to 0.76, 0.62 and 0.45 for tomato, cowpea and maize, respectively. Productivity was positively and significantly influenced by household size, extension contact, nonfarm income, location of farm in relation to source of irrigation water and scale of operation. Based on the results, it was concluded that opportunities exist in the area for increasing productivity of resources by increasing contact of farmers with extension workers and other conventional inputs. The scale efficiency analysis result confirmed increasing return to scale and therefore more output will be produced if additional improved conventional inputs are used.
URI: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/6825
ISSN: 1190-3375
Appears in Collections:Agricultural Economics and Farm Management

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