The study focused on the role of the State and the environment in indigenous livestock farming in Debe Marela in Middledrift. Although communal farmers in the area used ethnoveterinary medicines to treat and prevent animal diseases, they also widely used conventional medicines, as these often provided a remedy to animal diseases. The livestock farmers believed in indigenous knowledge which empowered them in using herbs to a certain extent, but the latter was preferred. The Department of Agriculture has featured as a support institution and although livestock farmers in the area have participated in and benefitted from state programmes, they believe that they needed more interventions such as visits from veterinary surgeons, Extension Officers and Animal Health Technicians. The study therefore attempts to address the gaps highlighted in the work of other researchers.

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, one hundred and fifty 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 only occasionally and did not engage in non-farming activities. Most of the smallholder farmers had less than 10 years of farming experience, had household sizes 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 farmer organisation. Generally, the farmers were involved in dry land farming. Farmers who irrigated their farms, did so on approximately 15 and 45 hectares of land. Farmers also 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 and majority did not have to repay for the inputs. Majority of farmers indicated that infrastructure impacted on their farming enterprises through increases in both productivity and sizes of 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 farmers without agricultural infrastructure available, factors influencing agricultural income were: physical infrastructure availability index (Coef = 0.74; P<0.01); social infrastructure availability index (Coef = 0.77: P<0.01); institutional infrastructure availability index (Coef = 0.61: P<0.01); level of education (Coef = 0.89: P<0.01); access to extension services (Coef=1.24: P<0.01); age of farmers (Coef = 0.06: P<0.01) and assistance of household members in farming enterprises (Coef=0.33: P<0.01). 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). With regards to smallholder farmers without accessible agricultural infrastructure, factors influencing agricultural income were: Physical infrastructure accessibility index (Coef=0.92, P<0.01); Equipment accessibility index (Coef=0.43, P<0.05); Level of education (Coef=1.25: P<0.01P); access to extension services (Coef = 1.63; P<0.01); membership of farming organisations (Coef = 0.86; p<0.01); age of farmers (Coef= 0.07; P<0.01) and assistance of household members in farming enterprises (Coef = 0.34; P<0.05). 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). With regards to farmers not satisfied with agricultural infrastructure, factors influencing agricultural income were: institutional infrastructure satisfaction index (Coef = 0.54: P< 0.05); level of education (Coef=1.25: P<0.01); access to extension services (Coef = 1.77: P<0.01); age of farmers (Coef = 0.06: P<0.01) and assistance of household members in farming enterprises (Coef = 0.34: P<0.01). 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 / D. Litt et Phil. (Agriculture)

Thesis (M.Sc. (Agricultural Economics)) -- University of Limpopo, 2019 / Livestock production is the most important sub-sector in agriculture in South Africa. It contributes a very large proportion to the agricultural gross domestic product. It has been identified as the sub-sector that has potential in improving food security and livelihoods of the rural people. The current study analyses the determinants of market participation and profitability of IDC Nguni smallholder farmers in the Limpopo Province, South Africa. The aim of the study was to contribute to the body of knowledge that exist in the study area, particularly of Limpopo Province livestock marketing by analysing determinants of market participation and profitability. The primary data were collected using structured questionnaires. All IDC Nguni Project beneficiaries (62 famers)were included in the survey. Descriptive data were analysed using Version 23 of SPSS. The logistic regression was used to analyse market participation data, multiple regression was used for profitability data and livelihood model for assessing the contribution of the project to livelihoods. The models were analysed using Stata 14. The results revealed that 59% of the respondents participated in the market and 41% of respondents did not participate. The study revealed that 54% of the respondents indicate that market access was easy and only 38% of respondents indicated that market access was not easy and 8% of respondents revealed that they do not know how the market access was because they were not yet selling. Seventy percent of the farmers perceived their livelihoods being improved after joining IDC Nguni Cattle Project whereas 23% of the farmers perceived their livelihood not improve after joining IDC Nguni Cattle Project. Gross margin computation showed that 52% of the farmers made gross margins ranging between R2 000 and R481 200 during the 2015 production/marketing season. The overall gross margins showed that 46% of the farmers made loss ranging from R7 300 to R170 500 during the 2015 marketing season, and 2% of the smallholder farmers were operating break-even point. The average gross margin for Community Property Associations was R6 031 while for individual farmers it was R16 082. The decision making process, for example to sell vii livestock, may be complex in the CPAs and hence a higher gross margin results for individual farmers than for CPAs. Thirty-six percent of CPAs made a loss, while 49% of individual farmers also made loss during 2015. The results of logistic regression showed that marital status, education level, loan repayment, price of an animal and household income were all significant factors (at various probability levels and with different signs), influencing market participation in the study area. A multiple regression model revealed that empirically the herd size, farm size and distance travelled to the market were significant at various probability levels and with different signs influencing profitability in the study area. Livelihood model results revealed that recent increase in farm income and farm size were all significant at different probability levels and with different signs influencing smallholder farmers' livelihood improvement in the Limpopo Province. The study identified some challenges faced by smallholder farmers in Limpopo Province. The major ones were inadequate access of market information, high transactional costs, poor conditions of the animals and poor access to markets. Policy makers should come up with policies that support the smallholder farmers with formal training, seminars and workshops to improve profitability of the farmers. Basic training of production and marketing may enable the smallholder farmer to increase profits. Other recommendations were formation of farmers' organisations, access to financial resources and private-public collaboration to establish central selling points. / Department of Science and Technology-National Research Foundation (DST-NRF) Centre of Excellence (CoE) in Food Security and National Agricultural Marketing Council (NAMC)

Thesis (M.Sc. Agriculture (Agricultural Economics)) -- University of Limpopo, 2021 / Raising cattle in South Africa and any other developing country in the Southern African region as part of livestock production, is one of the important means through which people sustain their livelihood. Inadequate efforts have been taken by the government to improve the marketing system of cattle, particularly to develop small-scale farming in the Limpopo Province and South Africa as a whole. With that being said, the small-scale sector has not been developed to the extent it is expected to. This study examined the factors affecting the participation of small-scale cattle farmers in livestock auctions in the Capricorn District of the Limpopo Province. The study had three objectives, namely; (i) To describe the socio-economic characteristics of the small scale cattle farmers in the Capricorn District of the Limpopo Province; (ii) To assess the perception of small-scale cattle farmers in the Capricorn District of the Limpopo Province towards livestock auction; (iii) To identify and analyse factors affecting the participation of small-scale cattle farmers in livestock auctions in the Capricorn District of the Limpopo Province. The Multi-stage sampling procedure was used in the selection of the representative sample. Three locations (Lepelle-Nkumpi, Molemole and Polokwane local municipalities) were selected purposively because a large number of small-scale cattle farmers in the Capricorn District rely on the agricultural sector economically. The Logistic Regression Model was used to analyse factors affecting the participation of small-scale cattle farmers in livestock auctions. The results showed that, out of the 120 sample size, 42% of small-scale cattle farmers were auction participants and 58% of small-scale cattle farmers were non-participants . There were 43 male-headed households of the participants and 61 female-headed households of the non-participants . An analysis of the farmers ’ socio-economic characteristics further showed that in order for the farmers to cut the costs of production, the majority of the small-scale cattle farmers preferred using family labourers or household labourers in their cattle farming. Farmers were asked a set of Likert type scale questions about their perceptions on the auctions. The Perception Index score ii was skewed to the left and therefore revealed that the small-scale cattle farmers had a negative perception towards the auction. Farmers who had a positive perception, on the other hand, often sold their cattle at a higher price compared to the non-participants who had a negative perception. Furthermore, small-scale cattle farmers who are participants tend to use the market avenue and through that, their cattle productivity is higher, resulting in a total revenue compared to the non-participants. Consequently, small-scale farmers who participate in auctions acquire valuable production information at the very auctions. Descriptive statistics such as means, minimum and maximum values, frequencies, percentages and standard deviations were used to describe the socioeconomic characteristics of the small-scale cattle farmers in the Capricorn District of the Limpopo Province. The results revealed that only 4 variables were significant. The total herd size, distance to the market, gender of the household head and market information were significant at 1%, 5%, 1%, 5%, respectively and all had a positive effect towards auction participation. The study suggested that the government and other policy makers should increase the marketing information and abilities of small-scale cattle farmers through avenues like mass media, extension service and other means of capacity building. This will help the farmers to minimise transaction costs. Furthermore, farmers will not incur more costs when they participate in the markets, considering that market facilities such as auctions are often hosted far from the farmers, which results in farmers incurring more costs.

Thesis (M.Sc. Agriculture (Agricultural Economics)) -- University of Limpopo, 2022 / Climate change and variability on a global level is one of the most serious environmental challenges which exacerbates the well-known vulnerability of smallholder farmers. To cushion the shock of climate change, risk management plays a crucial role in farming, and in the same context, insurance positions itself as one of the main risk management instruments available to farmers. However, one of the key reasons to the struggles of smallholder farmers in South Africa is the inability to obtain effective insurance. To this end, the study identified and profiled the socio-economic features of smallholder cattle farmers, identified smallholder cattle farmers’ perceptions on components of climate change as sources of risk to cattle production and finally, analysed the determinants of willingness to adopt IBLI among smallholder cattle farmers. A purposive multistage sampling procedure was used to identify 110 smallholder cattle farmers in the Polokwane local Municipality. IBM SPSS version 26 and STATA version 15 was used to analyse the primary cross-sectional data collected through structured questionnaire interviews. Farmers’ perceptions on components of climate change as sources of risk were identified using the Principal Component Analysis (PCA). The PCA revealed three principal components (PCs) explaining almost 61% of the variance of the original variables (climate change components). Furthermore, about 89% of the sampled farmers were willing to adopt IBLI, while about 11% weren’t willing to adopt and the Probit regression model results revealed that marital status, farming experience, access to extension services, off- farm income and land ownership, farmers’ educational level, household size, experience of livestock loss and farm size significantly influenced willingness to adopt IBLI. Based on the findings of this study, the recommended interventions include workshops for raising IBLI awareness, government subsidy on insurance premiums and finally, increased extension service reach to smallholder cattle farmers. / AgriSETA

Thesis (M.Sc.(Agriculture (Agricultural Economics)) -- University of Limpopo, 2022 / Understanding the factors that influence farmers' decisions to take preventive measures against natural hazards provides insight that can be used to develop user-specific interventions to support their adaptation processes. The use of Protection Motivation Theory in analysing climate risk adaptation behaviour is driven by the increase in climate change, which is projected to increase the frequency and severity of climate related risks such as heatwaves, floods, and droughts. Given the importance of livestock in rural communities, information about their adaptation must be prioritised; yet, this is not the case, as most climate change adaptation research focus on crop production. The main aim of the study was to analyse the drought risk preparedness of smallholder livestock farmers in the Limpopo Province's Blouberg Local Municipality. The study's specific objectives were to identify and describe the socioeconomic characteristics of smallholder livestock farmers in the Blouberg Local Municipality, as well as to determine the drought coping and adaptation strategies used by them and to evaluate the protection motivation theory components influencing that coping and adaptation behaviour. The study collected primary cross-sectional data from 130 smallholder livestock farmers in the Blouberg Local Municipality using a semi-structured questionnaire. The farmers' drought risk coping and adaptation strategies were described using descriptive statistics, while multiple linear regression was used to test whether protection motivation theory variables influence the adaptation and coping choices of smallholder livestock farmers in Blouberg Local Municipality. According to the findings, smallholder livestock farmers in Blouberg Local Municipality use four measures on average to protect their livestock against drought. With an R2 adjusted of 0.70, protection motivation theory variables explain 70% of the variation in farmer protection motivation. Perceived risk probability, perceived severity, perceived self-efficacy, and perceived costs were significant variables associated with farmers' protection motive. It is recommended that interventions meant to increase drought risk resilience of the farmers should prioritise early warning signals to increase perceived probability of the farmers, create platforms for information exchange to increase perceived severity, teach farmers methods practically to increase perceived self-efficacy and keep the price of utilising measures low to decrease perceived cost / Risk and Vulnerability Science Centre (RVSC)

Thesis (MDev.) -- University of Limpopo, 2016 / The purpose of this study was to assess the socio-economic effects of farm evictions in Mogale City Local Municipality, Gauteng Province. Most of the land owners do not adhere to the legislations which govern evictions in general and to the Extension of Security of Tenure Act which governs farm eviction on specific. The key objectives of the study were to identify the socio-economic effects of farm evictions and to analyse how the affected communities responded to the phenomenon of evictions. The key questions were what are the socio-economic effects do eviction have on farm dwellers and how have the affected communities responded to the phenomenon of eviction. The literature revealed that evictions around the world started decades ago and to date are still happening. In Zimbabwe, evictions were initiated by white farmers as a way of redressing the imbalance of the land ownership; in China evictions are mainly caused by rapid population growth and expansion of cities, in Namibia, Germans expropriated land and forcefully removed original owners of such land. Since independence, Namibia has no legislation governing evictions and this pose a thread of tenure insecurity. Although South Africa has legislations which govern the evictions, evictions are still taking place and mostly initiated by white land owners. The quantitative survey study was conducted to determine the distribution of socio-economic variables before and after the eviction. The primary data was collected, using semi-structured questionnaires which the interviewer administered to the evicted households. The findings revealed that electricity supply, garbage collection, personal care, household income, access to health facilities are negatively affected and the condition of the households deteriorated after the eviction. The main recommendation on the basis of the findings is that the MCLM, DRDLR and NDHS should adhere to the principles outlined in the article 25(1) of the United Nations Universal Declaration of Human Rights 1948. This would reduce the negative impact of evictions.

College of Agriculture and Environmental Sciences / M. Sc. (Agriculture)

A case study on drought coping mechanisms was conducted among small-scale farmers in the Motheo District of the Free State Province in Republic of South Africa, to determine how farmers cope with drought effects with or without external influence in terms of drought relief packages from the government and non-governmental organizations. Data was collected by administering a semi-structured questionnaire to 200 farmers. The data were captured and analysed using SPSS to obtain frequency, cross-tab, univariate ANOVA as well as logistic regression analysis. Findings of the study revealed that only 12.5 percent of the respondents were aware of drought, while a larger percentage of 87.5 of the respondents were not aware of a drought incidence before its onset, which made them more vulnerable to the drought disaster; 8.5 percent of them protected water sources for livestock while 91.5 percent of the farmers did not protect water sources for their livestock because they farm on a communal land; 42.5 percent provided supplementary feeds to livestock during the drought, but 57.5 percent did not provide supplementary feed for their animals for lack of funds. Ninety-nine (99.0) percent of the respondents shared grazing lands while only 1 per cent did not because most farmers operates on a communal system of farming; 35.5 percent changed cropping systems; 50.5 percent had alternative water sources for crops which included mini and hand irrigation systems while 49.5 percent of the respondents depended solely on streams and rivers available in the villages; 19.3 percent sold or pledged assets in order to be able to cope with drought effects while most farmers did not pledge or sell assets not because they did not want to, but because they did not have assets to sell. / Envornmental Science / Thesis (M.Sc. (Environmental Management))

Land is a major factor in agricultural production, so agricultural land allocated to smallholder farmers through Land Reform Program or by traditional leader need to be actively utilised for enhancement of agricultural business. The study assessed land utilisation by small and emerging farmers in the Greater Tzaneen Municipality. Data was collected from 86 farms and analysed using SPSS Version 23. The results indicate that 74% of the farmers fully utilised their farm lands. Results of Logit model revealed that, the amount received from leasing, value adding to products, annual farm income and savings had positive significant impact on the area of cultivation, while skills pertaining to farming activities and the proportion of farm inputs purchased with the farmer’s own money had negative impact. The significant variables should be considered to influence full farmland utilisation by small and emerging farmers in the study area; farmers need production inputs, affordable loans and other forms of funding to improve farmland utilisation / Agriculture, Animal Health and Human Ecology / M. Sc. (Agriculture)