Thesis (M.Sc. Agriculture (Agricultural Economics)) -- University of Limpopo, 2022 / Spinach (Spinacia oleracea) is an important cash crop, which remains one of the largest sources of income and a way of sustaining livelihoods for rural households in South Africa. Smallholder farming in most rural areas of the Limpopo Province contributes to food security. However, the majority of smallholder farmers experience low agricultural productivity, low quantities and poor quality produce which reduce their chances of accessing markets. Hence, this study focused on identifying and analysing factors that determine productivity and market access by smallholder spinach farmers in the Polokwane Local Municipality, Limpopo Province. This area of research is important towards the development of smallholder farming where resources are limited, but high population growth is very common. The overall objective of the study was to examine farm and farmer characteristics that determine the productivity and market access of the smallholder vegetable farmers. In order to achieve the aim and objectives of this study, a multi-stage sampling technique was used to select 80 smallholder spinach farmers to collect primary data from them using structured questionnaires. Cobb-Douglas production function was used to examine factors that determine productivity level and the Two limit Tobit Model was also used to analyse factors that influence market access. The results from the Cobb-Douglas production function indicated that smallholder farmers in the study area are experiencing a decreasing return to scale, which suggests that they are over-utilising factors of production. Two-limit Tobit Model results on the socioeconomic factors that influence market access indicated that household size was statistically significant at 10%, distance to the market, extension contact and farming experience were statistically significant at 5% and educational level, quantity produced and market information was statistically significant at 1%. Based on the findings, several policy suggestions were made. These include strengthening of farmers‟ organisation, provision of market information, regular extension visits and provision of training to the farmers.

In the literature there are mixed results on the link between credit and agricultural output growth. Some authors argue that credit leads to growth in agricultural output. Others view growth as one of the factors that influence credit supply, thus growth leads and credit follows. By and large, studies have not endeavoured to establish the short-run impact of agricultural credit on output. They are generally limited in establishing the long-run relationship between credit and agricultural output and thus present a research gap in this respect. This study contributes to the existing body of literature by focusing on the finance-growth nexus at sectoral level as a departure from extant literature that has focused on the macroeconomic level. Using South African data, the study investigated the causal relationship between the supply of credit and agricultural output as well as whether the two are cointegrated and have a short-run relationship. The study found that bank credit and agricultural output are cointegrated. Using the error correction model (ECM), the results showed that, in the short-run, bank credit has a negative impact on agricultural output, reflecting the uncertainties of institutional credit in South Africa. However, the ECM coefficient shows that the supply of agricultural credit rapidly adjusts to short-term disturbances, indicating that there is no room for tardiness in the agricultural sector. The absence of institutional credit will immediately be replaced by availability of other credit facilities from non-institutional sources. Conventional Granger causality tests show unidirectional causality from (1) bank credit to agricultural output growth, (2) agricultural output to capital formation, (3) agricultural output to labour, (4) capital formation to credit, and (5) capital formation to labour, and a bi-directional causality between credit and labour. Noteworthy and significant for South Africa is that for the agricultural sector, the direction of causality is from finance to growth, in other words supply-leading, whereas at the macroeconomic level, the direction of causality is from economic growth to finance, in other words, demand-leading. Applying a structural equation modelling approach to survey data of smallholder farmers, the positive relationship between bank credit and agricultural output observed from analysis of secondary data was confirmed. / Business Management / DCOM (Business Management)

This study investigates the factors affecting agricultural production of farm households in the National Regional State of Tigray, Ethiopia. The major primary sources of data for the study were farm household surveys, focus group discussions and key informant interviews. The study revealed that the annual average crop production of respondents was found to be below the standard annual food requirement recommended by the international organizations. The proportion of irrigated land to total cultivated land was only 11per cent. The proportion of irrigated land in the two districts is lower than 11.27 per cent at the regional level. The utilization of chemical fertilizers for the majority of the respondents was below the recommended standard for the region. Although the farmers were interested in using improved seeds, the supplied varieties were not based on their preferences. Extension agents were mainly engaged in activities which were not related to their professions. The farm income model result showed that landholding size (p<0.0001), possession of oxen(p<0.0001), amount of fertilizer(p=0.010), improved seeds(p=0.002), irrigation(p=0.028), soil quality(p=0.019), village distance to the district market(p=0.066), average distance of plots from the homestead (p=0.023) and crop rotation(p=0.016) were determinant variables. Farmers were engaged in off-farm activities to fulfill the cash requirements in credit constrained conditions. The laws of the region do not allow farmers to be out of their localities for more than two years and the farmerswere restricted to renting out only half of their land. This discouraged farmers from off-farm participation for fear of land confiscation. In the Probit model, the determinant variables of off-farm participation were: irrigation (p=0.001), age (p=0.007), amount of money borrowed (p=0.078), village distance to the wereda market (p=0.055), fear of land confiscation (p=0.023) and access to electricity (p=0.044). It is recommended that if farmers are to use chemical fertilizers, they should be supplied with High Yielding Varieties (HYV)and enough water through access to irrigation. Furthermore, farmers should be allowed to have long term off-farm employment to augment the farming sector. / Development Studies / D. Litt. et Phil. (Development Studies)

Thesis (MScAgric (Agricultural Economics))--University of Stellenbosch, 2009. / AFRIKAANSE OPSOMMING: Die Wes-Kaapprovinsie van Suid-Afrika beskik oor ’n diverse kapasiteit wat landbouproduksie betref en dit dra tot die sektor se algemene stabiliteit by; vandaar die bevordering van die Wes-Kaap as ’n aantreklike beleggingsektor. Die wynbedryf, wat ’n belangrike integrerende deel van die landbousektor in die Wes-Kaap uitmaak, speel ’n baie belangrike rol in die ekonomie van die Provinsie en bied ontsaglike geleenthede met betrekking tot landboukundige beleggings in die Provinsie. Die Suid-Afrikaanse wynbedryf is bekend vir sy produkte van hoë gehalte. Tans word indirekte aanwysers soos die inkomste van produsente, die aantal nuwe wynkelders, asook die ouderdomsamestelling van wingerdstokke in Suid-Afrika, gebruik om die beleggings- netto toevloeiing in die wynbedryf te bereken. Die hoofdoel van hierdie studie is om die mees algemene bronne van kapitaal van wynplase en die mees algemene doelwitte wat wynboere in die Wes-Kaap probeer om te bereik, te identifiseer. Nog ’n doelwit is om daardie wynplaas- en eienaarskenmerke te identifiseer wat die prestasie van wynplase in die Wes-Kaapprovinsie van Suid-Afrika beïnvloed. Om die ontleding te vergemaklik is die hoofprobleem in drie spesifieke doelwitte of subprobleme verdeel. Die studie het van verskeie metodes en tegnieke gebruik gemaak in ’n poging om relevante en akkurate data te verkry. Die verskillende bronne wat geraadpleeg is het persoonlike beraadslaging met deskundiges in die bedryf, artikels wat in verskeie akademiese vaktydskrifte en boeke gepubliseer is, referate wat by konferensies gelewer is, verhandelings van nagraadse studente, en ander artikels op die Internet ingesluit. Data-ontledings wat met die eerste en tweede subprobleme verband gehou het is met die gebruik van statistiese pakkette soos Excel en Stata in die vorm van veelvoudige kruistabulerings uitgevoer. In die derde probleem, naamlik om wynplaas- en eienaarskenmerke te identifiseer wat die prestasie van wynplase in die Wes-Kaap beïnvloed, is ’n intervalregressiegelykstelling bereken deur van die Stata- statistiese sagtewarepakket gebruik te maak. / ENGLISH ABSTRACT: The Western Cape Province of South Africa has a diverse agricultural production capacity and this contributes to the sector’s general stability, hence its promotion as an attractive investment sector. The wine industry, a significant component of the agricultural sector in the Western Cape, plays a very important role in the economy of the Province and presents enormous opportunities in terms of agricultural investments in the Province. The South Africa’s wine industry is renowned for its high quality products. Currently, indirect indicators such as producer income, the number of new wine cellars, as well as the age composition of vines in South Africa, are used to estimate investment net flows into the wine industry. The main objectives of this study are to identify the most common sources of capital in wine farms and the most common objectives that wine farm owners are trying to achieve in the Western Cape Province. Another objective is to identify those wine farm and owner characteristics that affect the performance of wine farms in the Western Cape Province of South Africa. For ease of analysis, the main problem was divided into three specific objectives or sub-problems. The study employed a number of methods and techniques in an effort to obtain relevant and accurate data. The different sources consulted include personal communications with industry experts, articles published in different academic journals and books, conference papers, postgraduate students’ theses, and other articles from the internet. Data analyses relating to the first and second sub-problems were carried out using Excel and Stata statistical packages and took the form of multiple cross-tabulations. In the third subproblem i.e., to identify wine farm and owner characteristics that affect the performance of wine farms in the Western Cape, an interval regression equation was estimated using Stata statistical software package.

This dissertation is based upon a research project designed to identify and evaluate alternative agricultural systems which are applicable to the arid environment of Saudi Arabia within a multiobjective context. The four systems are: traditional; conventional; aridity-oriented; and, controlled environment. These systems differ in their utilization of basic resources, the the amount and type of food they produce, the profits they generate and their compatibility with Saudi Arabian social traditions. Thus, the environmental and sociological consequences of their implementation were considered along with production and economic aspects. The procedure for evaluating the alternative agricultural systems is a computer program called ESAP (Evaluation and Sensitivity Analysis Program) which uses multi-attribute theory as an aid to decision making. Computations to determine the extent of that achievement are essentially a weighting of the variables identified as subdivisions of the goals. Decision makers are also required to give the relative values to the variables, and to select a particular utility function which describes the relationship between value and utility. The values assigned to each variable are usually presented as a range to express the users' uncertainty. Six consultants (five university professors plus the author) with varying professional backgrounds and knowledge of Saudi Arabian conditions were used as individual and collective decision makers to evaluate the four agricultural systems and their combinations. The procedure resulted in grouping these ten different alternatives (four systems plus combinations of any two) into three independent classes: I, Il and III. The grouping was based upon obtaining a clear distinction in overall score between the classes. The grouping into classes resulted in the aridity-oriented agricultural system being the only alternative in Class I. The consultants felt that this system offered the most favorable tradeoff between the economic benefits and the social and environmental factors. In general, the study indicated that the protection of natural resources and the maintenance of cultural factors should be given significant influence along with the economic factors in evaluating a particular plan of action. In utilizing such a procedure, the need for additional data and research became very evident, if there is to be better allocation of the Kingdom's agricultural resources.

In the literature there are mixed results on the link between credit and agricultural output growth. Some authors argue that credit leads to growth in agricultural output. Others view growth as one of the factors that influence credit supply, thus growth leads and credit follows. By and large, studies have not endeavoured to establish the short-run impact of agricultural credit on output. They are generally limited in establishing the long-run relationship between credit and agricultural output and thus present a research gap in this respect. This study contributes to the existing body of literature by focusing on the finance-growth nexus at sectoral level as a departure from extant literature that has focused on the macroeconomic level. Using South African data, the study investigated the causal relationship between the supply of credit and agricultural output as well as whether the two are cointegrated and have a short-run relationship. The study found that bank credit and agricultural output are cointegrated. Using the error correction model (ECM), the results showed that, in the short-run, bank credit has a negative impact on agricultural output, reflecting the uncertainties of institutional credit in South Africa. However, the ECM coefficient shows that the supply of agricultural credit rapidly adjusts to short-term disturbances, indicating that there is no room for tardiness in the agricultural sector. The absence of institutional credit will immediately be replaced by availability of other credit facilities from non-institutional sources. Conventional Granger causality tests show unidirectional causality from (1) bank credit to agricultural output growth, (2) agricultural output to capital formation, (3) agricultural output to labour, (4) capital formation to credit, and (5) capital formation to labour, and a bi-directional causality between credit and labour. Noteworthy and significant for South Africa is that for the agricultural sector, the direction of causality is from finance to growth, in other words supply-leading, whereas at the macroeconomic level, the direction of causality is from economic growth to finance, in other words, demand-leading. Applying a structural equation modelling approach to survey data of smallholder farmers, the positive relationship between bank credit and agricultural output observed from analysis of secondary data was confirmed. / Business Management / D. Com. (Business Management)

Small-scale farmers rarely get enough yields to sustain themselves to the next harvest. Most of these farmers are located in marginal areas with poor soils and in semi-arid areas which receive little rainfall yet the farmers practice rainfed agriculture. A number of reasons can be attributed to the low yields characterizing these farms. Lack of relevant knowledge for decision-making and climate change are among the major reasons for poor yields. Whilst there is not much the small-scale farmers can do to influence climate, they can at least make informed decisions to improve their yields. The information necessary for agricultural decision-making include the climate forecast information and information about performance of new technologies be it fertilisers, varieties or other practices. The study aimed to answer the primary research question: What is the applicability of the APSIM model in decision-making by small-scale resource constrained farmers? This question was supported by secondary research questions namely: - How useful is the APSIM model in small-scale farmers' adaptation to future climate change? - What are the current farming systems of Lower Gweru farmers with regards to maize production? - What are farmers' perceptions of climate change and what changes have they noticed in the last 10 years? - How do small-scale farmers make crop management decisions? Data was gathered through five methods namely, Focus Group Discussions, resource allocation mapping technique, APSIM simulations, on-farm experimentation, and semi-structured interviews. Data was collected from a group of 30 small-scale farmers of Lower Gweru Communal area. The study concentrated on maize production due to the fact that it is the staple food and was grown by all farmers. All the farmers perceived climate to be changing. The changes noted included late start of the rain season, early cessation of rain season and temperature extremes. The majority of farmers highlighted that they were using local indicators to make decisions about climate or to forecast the nature of the coming season before they were exposed to SCF and APSIM. The data gathered from three selected resource allocation maps were used to run the APSIM model. For which farmers were convinced that the model was credible in yield prediction based on the simulated results which reasonably compared to observed yields. The what if questions raised by farmers during the discussions were also assessed and this further increased the farmers' confidence with the model, as they viewed it as a planning and guiding tool before one can actually commit resources. The semi-structured interviews showed that most farmers will continue to use the model outputs in their decision-making. The reasons being that it was a good planning and budgeting tool, it is cheaper and faster since one can assess a lot of options in a short time and would then decide on which options are viable in a given season. The few farmers who said they would not use the model or its outputs in decision-making cited reasons including lack of a computer to install the model and that it was complex for them. Semi-structured interviews confirmed the data collected in resource allocation mapping, focused group discussions and APSIM sessions. / Thesis (M.Sc.Agric.)-University of KwaZulu-Natal, Pietermaritzburg, 2011.

Land degradation and soil nutrient depletion have become serious threats to agricultural productivity in sub-Saharan Africa. Soil fertility depletion in smallholder areas has been cited as the fundamental biophysical cause of declining per-capita food production in Africa. Manure application is a well established and known practice, but not effectively used among South African smallholders. This study investigated the practice, constraints and perceptions of improving soil quality through manure application through a case study of three smallholder farmer groups. Three groups from rural areas of KwaZulu-Natal (Mkhambatini, Mooi River and Richmond) were selected to participate in the study. Participatory methodologies were used to identify and clarify the study problem. Three participatory focus group discussions, one per area, were conducted with farmers at the study sites to discuss farming methods, experience and perceptions of manure use, manure management practices and constraints farmers experience with manure use. Force Field Analysis was used for each group to explore for forces against and in support for manure use. Random soil and manure samples were collected for laboratory analysis to determine fertility levels. Some farmers indicated that soil fertility was low. However, half the sample perceived the land to be productive to some extent. The study showed that 40 per cent of farmers reported improved soil fertility following the application of manure. Due to the limited availability of livestock manure, farmers prefer to use both livestock manure and commercial fertilisers. Furthermore, the study found that except for young farmers (20 per cent of the sample), farmers had not received formal training and very limited extension advice on composting and manure use and management. The study participants were aware of the consequences of declining soil fertility and were attempting to improve soil quality. However, low livestock numbers and poor management led to inadequate amounts of manure, and, limited access to information on manure and compost use. Unless better knowledge of optimal soil nutrient management practice is acquired by the farmers, soil fertility levels will continue to decline, further reducing production potential and rural household food security. Government needs to revisit extension support to meet the needs of smallholders and offer training on sound soil management, sustainable production methods, composting and livestock management. A handbook with graphic detail should be accompanied to provide smallholders with information and advice on how to manage soil fertility. / Thesis (M.Agric.)-University of KwaZulu-Natal, Pietermaritzburg, 2009.

This study set out to examine the determinants of participation in non-farm economic activities by farming households in rural Zanzibar, using data from the Agriculture Census of 2003. The study goes beyond the traditional focus of non-farm studies that focus on analysing geographical and socio-economic variables on decisions to participate in non-farm activities and in so doing, fills an information gap and contributes to the understanding of determinants of farm household participation in non-farm activities in rural Zanzibar. The survey from which data were drawn, included surveys of 4755 household heads. Descriptive statistics and logistic regression model were applied to investigate the effect of individual characteristics on the decision to participate in non-farm economic activities. Gender, age, family size and level of education were used as variables to explain individual preference with regard to the decision to undertake non-farm economic activities. The analysis also included farm production factors including farm size, planted area and the main source of household income. The results show that gender, age, household size and income sources outside agriculture are the key factors that influence farming household’s decisions to participate in non-farm activities. Women and young farmers were more likely to participate in non-farm activities. Heads of larger households were also more likely to participate in non-farm activities, and undertake more than one activity in this sector. The type of activity engaged in also seems to have a positive influence on the decision to participate in the non-farm sector, with selling of agricultural products, fishing (including seaweed farming and selling of fish), wage employment and petty trade being more popular and attractive activities. Factors like education, landholding size and area of land planted were less important in influencing participation in non-farm activities. All sampled households participated in non-farm economic activities, with 70 per cent of the participants undertaking more than four activities simultaneously. This points to the importance of non-farm economic activities in providing opportunities to sustain household food security and increase the capacity for households to mitigate shocks. However, a strong relationship was found between participation in non-farm activities and the use of forest resources, as a significant number of activities depend on forest resources. The forest-based non-farm activities reported were: beekeeping, charcoal making and tree logging for poles, timber and firewood. This raises significant concern over the over-utilization of forest resources and subsequent sustainability of the related activities. It is recommended that efforts towards promoting non-farm economic activities should be directed towards developing non-farm activities that are not dependent on forest resources. Interventions enabling increased farm productivity or non-forest activities are important in ensuring food security in Zanzibar. More policy and programme attention should be given to the role of women in non-farm activities. / Thesis (M.Agric.)-University of KwaZulu-Natal, Pietermaritzburg, 2011.

The land reform that has unfolded in Zimbabwe since 1980 used different models and had diverse consequences. Since the implementation of the fast tract land reform programme in 2000, Zimbabwe experienced heavy reduction in yield and output at farm level that led to a 70% shortfall in production to meet annual food requirements (Richardson, 2005). The economic crisis in Zimbabwe has been characterized by worsening food insecurity especially in the rural areas where harvests continue to be poor. In the beef sector, Zimbabwe has failed to meet its export quota to the EU. The shortfall in production to meet annual food requirements shows a very grim situation but do not tell us about the performance of resettled farmers who now occupy much of the productive land. The broad objective of the study was to determine and compare the production efficiency of resettled farmers in Zimbabwe across land reform models. In addition, the study determined land use intensity. The study was conducted in the Mashonaland Central Province of Zimbabwe mainly because a wide variety of field crops were grown by resettled farmers. The respondents were stratified into three groups. These were: beneficiaries of land reform before 2000 (resettle scheme), fast track A1 model and fast track A2 model. The three models differ on how they were implemented and supported and this might result in different efficiencies of the models. A total of 245 copies structured questionnaire were administered on the resettled farmers from June to September 2010. Descriptive statistics was applied to the basic characteristics of the sampled households. The effect of model of land reform, gender of the household head, marital status, age of the household head, education, household size, religion, dependence ratio, whether the farmer was fulltime or part-time in farming, experience of the farmers in farming at that environment, total land size owned by the farmers and soil type on revenue per hectare and land use rate were determined using the GLM procedure of SAS (2003). Significance differences between least-square group means were compared using the PDIFF test of SAS (2003). The relationship between Revenue and land utilization was examined using the Pearson‟s correlations analysis. Dependance between response variables that had an effect on either revenue per hectare or land utilization with all the other response variables was tested using the Chi-square test for dependance. To find the effect of arable land used and herd size on revenue per hectare and land use the RSREG Procedure of SAS (2003) was used. Input oriented DEA model under the assumption of constant return to scale was used to estimate efficiency in this study. To identify factors that influence efficiency, a Tobit model censored at zero was selected. The mean land use rate varied significantly (p<0.05) with the land reform model with A2 having highest land use rate of 67%. The A1 and old resettlement households had land use rates of 53% and 46%, respectively. Sex, marital status, age of the household head, education and household size significantly affected land use (P<0.05). Revenue per hectare was not affected by any the factors that were inputted in the model. Results from the DEA approach showed that A2 farmers (large land owners) had an average technical efficiency score of 0.839, while the lowest ranking model (A1) had an average score of 0.618. Small land holders (A1 and the old resettled farmers) are on average less cost-efficient than large land owners, with a score of 0.29 for the former compared with 0.45 for the latter. From the factors that were entered in the Tobit model, age of household head, excellent production knowledge and farmer status affected technical efficiency whereas allocative efficiency was only affected by good production knowledge, farm size, arable land owned and area under cultivation. Factors which affected economic efficiency of the resettled farmers are secondary education, household size, farm size, cultivated area and arable land owned. None of the included socio-economic variables has significant effects on the allocative and economic efficiency of the resettled farmers. Thus, the allocative and economic inefficiencies of the farmers might be accounted for by other natural and environmental factors which were not captured in the model.