The aim of the study was to investigate the impact of agricultural infrastructure on agricultural productivity and agricultural income of smallholder farmers in the North West Province, South Africa. Factors that contribute to the availability, accessibility and satisfaction of smallholder farmers with regards to agricultural infrastructure were also assessed in the study. Using cross sectional data from the North West Province of South Africa, 150 smallholder farmers were selected using stratified sampling to group farmers into those who had agricultural infrastructure and those who did not have. Data were collected using a structured questionnaire, divided into six sections as follows: personal socio-economic characteristics of farmers; characteristics of the land; agricultural infrastructure of smallholder farmers; agricultural production and markets; and production activities and financial support rendered to farmers. The data were coded, captured and analysed using STATA 14.0. Data were analysed through descriptive analyses, Principal Components Analysis (PCA), Stochastic Frontier Analysis, Heckman selection procedure and Tobit Regression Models.
This result revealed that most of the farmers were male, aged between 41 and 60 years of age, had contact with extension services, had contact with extension services only occasionally and did not engage in non-farming activities. Smallholder farmers had less than 10 years of farming experience, a household size of less than or equal to five members, had about one household member assisting in the day-to-day farming activities. Most of the farmers did not belong to any organisation. Generally, the farmers indicated that they were involved in dry land farming. Farmers who irrigated their farms, did so on approximately 15 and 45 hectares of land. Farmers also indicated that they received agricultural support from CASP and used commercial seeds, fertilizers and animal vaccines as their production inputs. Furthermore, smallholder farmers in the study area received support for inputs while majority indicated they did not have to repay for the inputs. Majority of farmers indicated that infrastructure impacted on their farming enterprises through increases in productivity in their farming enterprises.
The study found that the factors influencing agricultural income for smallholder farmers with agricultural infrastructure were: Physical infrastructure index (Coef=0.78: P=0.01); Social infrastructure availability index (Coef=0.61: P<0.01); Institutional infrastructure availability index (Coef=1.05: P<0.01); Level of education of farmers (Coef=0.96: P<0.01); Access to extension services (Coef=1.05: P<0.01); Membership of farmers’ organisations (Coef=0.59: P<0.05); Age of smallholder famers in the study area (Coef=0.05: P<0.01); and Household members assisting in farming activities (Coef=0.24: P<0.05).
In terms of smallholder farmers with accessible agricultural infrastructure, factors influencing agricultural income were: Physical infrastructure access index (Coef=1.29: P<0.01); Social infrastructure access index (Coef=0.38: P<0.1); Equipment infrastructure access index (Coef=0.62: P<0.01); Level of education for smallholder farmers (Coef=1.21: P<0.01); Access to agricultural extension services (Coef=1.64: P<0.01); Membership of Farmers’ organisations (Coef=0.77: P<0.05); Age of smallholder farmer (Coef=0.01: P<0.01); and Household members assisting in the farming enterprises (Coef=0.39: P<0.01). In terms of satisfaction of smallholder farmers with agricultural infrastructure, factors influencing agricultural income were: Physical infrastructure satisfaction index (Coef=0.35: P<0.1); Social infrastructure satisfaction index (Coef=0.37: P<0.1); Institutional infrastructure satisfaction index (Coef=1.25: P<0.01); Equipment infrastructure satisfaction index (Coef=1.04: P<0.01); Level of education of respondents (Coef=1.24: P<0.01); Access to extension services (Coef=1.58: P<0.01); Age of smallholder farmers in the study area (Coef=0.05: P<0.01); Number of years farming (Coef = -0.57: P<0.1); and Number of household members assisting in farming (Coef=0.19: P<0.1). The results of the Heckman selection model revealed that the variables impacting on agricultural income were: agricultural infrastructure availability index (Coef=1.12: P<0.01); and access to extension services (Coef=0.62: P<0.05).
Furthermore, those impacting on agricultural production were: infrastructure satisfaction index (Coef=-1.31: P<0.01); infrastructure accessibility index (Coef=-0.59: P<0.05); Level of education of smallholder farmers (Coef=0.64: P<0.01); access to extension services (Coef=1.29: P<0.01); and membership of farmers’ organisations (Coef=0.66: P<0.01). The results of the Tobit Regression Model showed that among others factors influencing availability of agricultural infrastructure, the following variables played a critical role: assistance of household members in farming enterprise (Coef=0.702: P<0.01); farm ownership (Coef=0.962: P<0.01); farm acquisition (Coef=0.323: P<0.01)farmer occupation (Coef=0.785: P<0.01); member of farmers’ organisations (Coef=2.066: P<0.01); sources of labour (Coef=1.283: P<0.01); farming experience (Coef=0.100: P<0.01); and agricultural production inputs (Coef=-0.763: P<0.05).
In terms of accessibility to agricultural infrastructure, the following variables played a critical role: engagement in non-farming activities Coef=1.275: P<0.01); contact with extension services (Coef=1.205: P<0.01); farm ownership (Coef=0.403: P<0.01); farmer occupation (Coef=0.456: P<0.01); membership of farmers’ organisations (Coef=1.111: P<0.01); sources of labour (Coef=0.653: P<0.01); farming experience (Coef=0.045: P<0.05) and land tenure (Coef=0.156: P<0.01). In terms of satisfaction with agricultural infrastructure, among other factors influencing satisfaction with agricultural infrastructure, the following variables played a critical role: organisation for extension services (Coef=1.779: P<0.01); assistance of household members in farming enterprise (Coef=0.411: P<0.01); government agricultural support to farmers (Coef=0.419: P<0.01); farm ownership (Coef=0.464: P<0.01); membership of farmers’ organisations (Coef=1.011: P<0.01); age of farmer (Coef= 0.030: P<0.01); level of education (Coef= 0.483: P<0.01); marital status (Coef=0.290: P<0.01); and gender (Coef= -0.576: P<0.01).
The results of the analysis were used to close the knowledge gap with regards to the impact of agricultural infrastructure, availability, accessibility and satisfaction on the productivity and agricultural income of smallholder farmers in the North West Province. In terms of recommendations, the study highlighted that agricultural industries and government should commit in assisting smallholder farmers to be productive and to participate in economic activities. This could be achieved through collaboration with industries in implementing initiatives that assist and accelerate the development of smallholder farming and also through assisting smallholder farmers access agricultural infrastructure. / Agriculture and Animal Health / Ph. D. (Agriculture)
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:unisa/oai:uir.unisa.ac.za:10500/25201 |
| Date | 01 1900 |
| Creators | Mazibuko, Ndumiso Vusumuzi Ezra |
| Contributors | Antwi, M.A. |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 1 online resource (xvi, 174 leaves) : illustrations (some color), color maps |
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