The central aim of this study was to investigate the determinants of South Africa's export growth and the challenges associated with agri-food products. To satisfactorily achieve this central aim, two specific objectives were set and addressed differently in this research work. Porter’s Diamond framework was followed to identify factors that influence the export performance of South Africa’s agri-food products, thereby identifying major challenges and opportunities for sustained growth, and the gravity model was applied to examine the main factors influencing South Africa’s agri-food exports to its major trading partners in Africa for the period 1996–2017. The study analyzed and interpreted the results using both primary and secondary data. The study aimed to pinpoint the elements that impact the export performance of South Africa's agri-food products, thereby pinpointing significant obstacles and prospects for long-term expansion. We collected primary data using a structured questionnaire, randomly selecting and interviewing 117 out of 137 respondents. The findings revealed that a scarcity of skilled labor, the expense of skilled labor, the availability of electricity, the cost of raw materials, the cost of advanced technology, transportation expenses, scientific research institutions, pricing, tariffs, language barriers, and crime are the primary barriers to the exportation of agri-food by South African firms. The researcher used 28 countries as export markets to examine factors influencing South Africa's agri-food exports, and the results showed that the size of the economy, geographical proximity, and currency devaluation had a huge effect on exports of agri-food products.

Purpose: This study aimed to investigate factors affecting cattle herd size in the Lepelle-Nkumpi Municipality, Limpopo Province. Method: A proportionate random sampling technique was used and a total of 261 smallholder cattle farmers were selected as participants in this study. Primary data were obtained using a well-structured questionnaire, where the participants were interviewed face to face. The data obtained were captured and analysed using Statistical Package for Social Sciences (SPSS) version 28.0. Descriptive statistics and ordinary least squares (OLS), using a multiple linear regression model, were employed to analyse factors affecting cattle herd size in the study area. Results and conclusion: Descriptive statistics results revealed that the prevailing factors that affect cattle herd size in the study area included the following: draught; practical knowledge; no/lack of; maintenance; water circulation; access to good breeding stock; poor market prices; grazing land; stock theft; insufficient or no breeding stock and pests/parasites. The OLS regression results, derived from a multiple linear regression model, revealed the variables that significantly affected cattle herd size, and this included age, household size, sales per year, livestock keeping, and planted pasture. Most farmers (91.4%) would like to increase their livestock numbers. It was recommended that extension services should be encouraged, training should be provided, and stakeholders should be engaged to help cattle farmers in the study area. Policies aimed at improving livestock production among smallholder farmers should be informed by the factors and determinates found in this study. Value: This study contributes useful information for potential livestock farmers. In addition, the outcome of this study could be used as the basis for informed policy formulation to improve livestock production which will ultimately improve food security status of farmers.

Background: The economic performance of any sector is measured by the level of its competitiveness against its competitors. The South African sugar industry, as a member of the Tripartite Free Trade Area (TFTA), faces stiff competition and is therefore challenged to improve its production and export performance to survive and dominate in the market in the long term. Aim: This study aimed to assess the competitiveness of the South African sugarcane industry by looking at the economic drivers of sugar production and export. Methods: The study employed Michael Porter`s Diamond Model to assess the competitiveness of the South African sugarcane industry, using primary data collected from a total of 123 sugarcane farmers and 100 key stakeholders. A 7-point Likert scale was applied to indicate the degree to which each of the determining factors is perceived to affect the performance and resulting competitiveness of the sugar industry. Results: The findings revealed that the major constraints experienced by respondents are the availability of skilled labour; cost of doing business; level of infrastructure development; cost of infrastructure; water availability; climatic conditions; rainfall patterns; availability of financial services; access to credit; crime; and HIV/AIDS. In terms of exports, tariffs were found to be the major constraint along with some of the aforementioned factors. Several factors that are experienced as having a positive effect on competitive success also emerged. These include product design; packaging; labelling and pricing; manager’s willingness to export; level of education and training; length of time in the business; experience; and language.

Purpose: This study aimed to determine the socioeconomic characteristics of small-scale farmers that have an impact on their access to high-value livestock markets in Greater Giyani Local Municipality (GGLM) and make recommendations for improving their access. Theoretical reference: Many studie conducted indicate that high-value livestock market access by small-scale farmers requires a Consideration of global trends in the economic transformation that have a direct bearing on the current small-scale market access situation from a holistic standpoint, which is influenced by the socioeconomic status of livestock farmers. Method: The study adopted a quantitative research approach and employed clustered proportional random sampling. Two hundred and fifteen (215) Greater Giyani Local Municipality livestock small-scale farmers were randomly selected. Results and conclusion: The study revealed that the majority of the small-scale livestock farmers in the GGLM were male (62.8%) and elderly people (above 65 years) (45.1%). The study further revealed that the majority (67.9%) of the livestock farmers in the GGLM had no formal education. Youth participation in livestock farming was disappointing (12.1%). Inferential statistical analysis revealed that young adults and elderly small-scale livestock farmers were all significant and had a direct influence on access to high-value markets. Farmers will be encouraged to enrol on an adult learning center and youth will be encouranged to participate in livestock farming. Research implication: Based on the results of previous research, fewer youth are usually participating in farming when compared with older farmers. Originality/value: The study revealed that socioeconomic characteristics play a vital role on access to high-value livestock markets. However previous study has not covered much on the role of socioeconomic status.

This paper was prompted by the observation that although access to high-value markets for emerging farmers has received extensive attention regarding income generation and food security, a gap existed with regard to associated communication channels, especially in the Greater Giyani Local Municipality (GGLM). A sample of 215 farmers was extracted from a population of 482 emerging farmers in the GGLM using clustered random selection techniques. Descriptive and inferential statistical analyses were used to assess the communication channels used. The study's general findings were that most farmers had no formal education, with very few acquiring tertiary education. Elderly farmers (above 55 years) dominated the emerging livestock farming sector, with minimal youth participation. In terms of utilisation of the various channels, the study uncovered substantial reliance on cell phones (84.2 %), farmers' unions (74.9 %), and radio (56.7 %). Inferential statistical results revealed that the use of television had a significant but negative influence on access to high-value markets. Farmer unions and other farmers had positive attributes (10% significance) in accessing high-value markets. The paper recommends promoting cell phone usage by other farmers and farmer unions to enhance the participation of emerging livestock farmers in high-value markets, especially in the GGLM. More youth participation also needs to be encouraged to prevent succession crises.

This article investigates the trends in South Africa`s sugar production and exports and determines the drift rate within the Tripartite Free Trade Area (TFTA) between 1996 and 2024. Trend analysis is crucial for informing policy to ensure that the competitiveness of the sugarcane industry is enhanced. To achieve this objective, it was, therefore, hypothesized that there were no trends in South Africa’s sugar production and exports within the TFTA member states, there was no drift rate variation in South Africa’s sugar exports within the TFTA member states and there was a significant positive correlation between South Africa’s sugar production and exports between 1996 and 2024. Secondary data used in this study were obtained from the Economic Analysis and Agricultural Statistics Directorate of the Department of Agriculture, Land Reform and Rural Development (DALRRD) as well as the TradeMap database. Using time series data, the trend analysis results revealed that there were regular fluctuations in sugar production in South Africa during the period under review. Similar fluctuations were concurrently noted for the raw and refined sugar exports. It is important to note that factors of a seasonal nature generally explain such fluctuations, hence, it was concluded that seasonal variations accounted for these fluctuations in the sugar industry. The Johansen test model was employed to determine the drift rate and the results revealed a drift rate variation of 32% for raw sugar and 56% for refined sugar indicating potential for growth in South Africa’s sugar exports. The Pearson correlation test results revealed that there was a positive correlation between sugar production and export in South Africa at the time. Further analysis using bivariate correlation analysis between sugar production and exports confirmed the results, clearly indicating a positive relationship. Improving productivity through appropriate government interventions can be expected to have a positive impact on sugar exports and South Africa’s balance of payments. Key words: drift rate, exports, Johansen test, production, South Africa, sugarcane, trend analysis