- Title
- Determinants of smallholder vegetable farmers' participation on post-harvest practices and market access : evidence from Mashonaland East Province of Zimbabwe
- Creator
- Mukarumbwa, Peter
- Subject
- Farms, Small -- Zimbabwe Vegetables -- Zimbabwe -- Marketing Vegetable trade -- Zimbabwe
- Date
- 2017
- Type
- Thesis
- Type
- Doctoral
- Type
- PhD
- Identifier
- http://hdl.handle.net/10353/8703
- Identifier
- vital:33431
- Description
- Smallholder vegetable production is very vital in enhancing livelihoods in Zimbabwe’s rural areas. Vegetable production generates household income and improves household food security. Despite this, smallholder vegetable farmers in Zimbabwe suffer huge post-harvest losses which reduce their profits and market competiveness. Post-harvest losses of vegetables are a major dilemma faced by smallholder farmers. They not only represent waste of scare resources such as farm inputs but they also entail wasted investment in terms of time, human effort and food. Furthermore, there are also a myriad of other challenges which constrain smallholder vegetable farmers in Zimbabwe from accessing lucrative markets. The broad objective of the study was to assess smallholder vegetable farmers` preferred post-harvest practices for value addition as well as factors that condition their selection choices, adoption and product market access. The study was conducted in four districts: Seke, Goromonzi, Murehwa and Mutoko, in the Mashonaland East Province of Zimbabwe. A multistage sampling procedure was adopted in the selection of villages and households. A total of 385 smallholder vegetable farmers were interviewed. The survey was undertaken from August–October 2016. Descriptive statistics were employed to analyse the socio-economic and demographic characteristics of households that were sampled in Mashonaland East Province. Age of household head, gender, educational level, household size, farming experience, main sources of income, land ownership, main vegetables produced and main causes of post-harvest losses were some of the statistics that were analysed. The average age of the farmers varied significantly across districts and it was generally high (average of 50 years). Moreover, the average household size was about six (6) individuals, which is an indication of high dependency ratio. The study also revealed the major causes of post-harvest losses across all vegetables predominantly cultivated in the study area were pests and diseases, followed by decay. Most of the underlying causes of huge post-harvest losses were within the control of the farmer. Therefore, the study recommends strategies from policymakers and Non-Governmental Organisations (NGOs) which enhance post-harvest management. These can result in substantial reduction in losses which can increase farmers’ income without necessarily expanding land under cultivation. The Poisson count regression model (PCRM) was used to analyse factors influencing number of post-harvest techniques adopted by smallholder vegetable farmers in the study area. The results of the PCRM revealed that the following variables were significant in influencing number of post-harvest practices adopted by smallholder vegetable growers: gender, education level, household size, age, farming experience, distance to market, market information, group membership, credit, and hired labour. The study recommends concerted efforts through public private partnerships (PPP) to provide active extension about post-harvest education. This will promote the adoption of simple, uncomplicated and innovative low-cost technologies for post-harvest management. The binary logit model was employed to analyse factors that influence smallholder vegetable farmers’ decisions to select a specific post-harvest practice for value addition. This was based on the three major post-harvest practices which were mainly being adopted by smallholder vegetable farmers’ in the study area which were drying, grading and washing. The results of the binary model showed that nine (9) variables were significant in influencing smallholder vegetable farmers’ decisions to select post-harvest practice for value addition. These were: gender, land size, distance to market, market information, family labour, training, target market, quantity produced and storage facilities. Policymakers and other stakeholders need to provide productive resources such as inputs to improve productivity and ultimately selection of basic post-harvest management techniques along the vegetable supply chain. The multinomial logit model was used in the study to analyse factors that influence market channel choice of smallholder vegetable farmers in the study area. The results from the multinomial logistic regression model revealed that distance to market, group membership, adding value, road infrastructure and quantity produced influenced participation in informal markets. On the other hand, gender, distance to market, market information, group membership, producer price, adding value, road infrastructure, quantity produced and market infrastructure influenced farmers’ participation in formal markets. Policies aimed at assisting resources for improved productivity of vegetables should be gender sensitive. Establishment of irrigation schemes as well as provision of credit for smallholder vegetable production are vital interventions. In the same way, crafting of appropriate policies and programmes which foster collective action amongst smallholder vegetable farmers are required. This will enable them to produce larger volumes as well as participate in more lucrative markets. Finally, smallholder vegetable farmers’ transaction costs can be reduced by investment in infrastructure such as roads.
- Format
- 197 leaves
- Format
- Publisher
- University of Fort Hare
- Publisher
- Faculty of Science and Agriculture
- Language
- English
- Rights
- University of Fort Hare
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UFH Department of Agricultural Economics and Extension
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details | SOURCE1 | PhD Agric (Agric Economics) MUKARUMBWA - May 2018.pdf | 2 MB | Adobe Acrobat PDF | View Details |