<p>Validerat; 20110830 (anonymous)</p>

Thesis (M. Sc. (Animal Production)) -- University of Limpopo, 2020 / South African dairy cattle industry is characterized by a dual production system, comprising of a high input commercial production system and low input smallholder and emerging dairy herds. Performance data from both systems are included in national genetic evaluations, with models that assume homogeneous variances. If variances are heterogeneous, above average animals in more variable herds will be favoured over high performing animals in the less variable herds. This may result in biased selection and inaccurate estimation of breeding values. With intensified selection, genetically inferior animals could be chosen, thereby decreasing the realised genetic gain, resulting in lower productivity. The aim of the study was to investigate the extent of heterogeneity of variance between the two dairy production systems South African Holstein cattle. Milk production data were obtained from the Integrated Registration and Genetic Information System of South Africa (INTERGIS).High input production system data set consisted of 68 000 lactation records from 741 herds, recorded between 2006 and 2018.Pedigree file comprised of 38 126 daughters of 2 472 sires and 4 305 dams. Data for the low input production system comprised of 32 388 lactation records of 3 325 daughters of 134 sires and 253 dams from 59 herds recorded from 2006 to 2018. Hartley’s Fmax test was used to test for heterogeneity of variances for 305 day yields of milk, fat and protein between the high and low input production systems. Non-genetic factors affecting these traits were then determined by the Proc GLM procedure of SAS. Genetic and phenotypic parameters among these traits were estimated, for each production system, by the Restricted Maximum Likelihood (REML) procedure in the ASREML software.vHeritability estimates for milk, fat and protein yield, respectively, were 0.70 ± 0.027, 0.55 ± 0.35 and 0.64 ± 0.03 for the low input production system compared to 0.16 ± 0.014, 0.11 ± 0.012 and 0.145 ± 0.013 for the high input production system. Estimates for genetic correlation between milk and fat, milk and protein and fat and protein were 0.68 (0.03), 0.81(0.01) and 0.81(0.02) in the high input production system and 0.80(0.34), 0.90(0.02) and 0.91(0.01) in the low input production system respectively. Phenotypic correlations in the high input dairy production system were 0.85(0.00), 0.92(0.00) and 0.88(0.00) for milk and fat, milk and protein and protein and fat and 0.82(0.08), 0.91(0.01) and 0.91(0.34) in the low input production system, respectively. Genetic prediction models for milk production traits, in South African Holstein cattle, shouldaccount for heterogeneous variances between the high and low production systems. Herd year-season of calving, parity and linear and quadratic effects of age at calving should beincluded on the models. There is a need to increase selection pressure in the low input production system, in order to improve genetic merit for milk production traits / National Research Foundation (NRF)-VLIR and University of Limpopo

Thesis (MSc. (Agricultural Economics)) -- University of Limpopo, 2018 / The avocado industry is a major industry in South Africa and this can be seen by its economic contribution. Limpopo Province is one of the major avocado producing areas in South Africa, and avocado production within the province ranges from smallholder to commercial production. Smallholder avocado producers within the province have a significant role to play, especially if their full potential is unleashed. For smallholder farmers to play such a role they need to be competitive. The concept of competitiveness can be defined as the ability of an industry or firm to compete successfully in order to achieve sustainable growth while earning at least the opportunity cost on resources employed. The main aim of this study was to analyse the determinants of competitiveness of smallholder avocado farmers in the Vhembe District of the Limpopo Province based on the Porter’s Diamond model framework in order to assess the level of competitiveness of farmers and to establish how the farmers can be assisted to reach their full potential. The study was conducted in the Vhembe District Municipality and a sample of 60 farmers was interviewed. SPSS (SPSS 26.0) was used to analyse the data. Three analytical techniques were used in the analysis for this study. Firstly, factor analysis was used to reduce and group the number of variables associated with competitiveness of the farmers. Secondly, profitability analysis through enterprise budgeting was used to categorise the farmers into two groups; competitive and noncompetitive. Thirdly, Logistic regression was used to establish the socio-economic and Porter’s Diamond model determinants that could be linked to the competitiveness of the farmers. From the factor analysis, 5 factors were extracted, namely; “chance”, “government, related and supporting industries”, “factor conditions”, “firm strategy structure and rivalry” and “demand conditions”. From the profitability analysis the farmers were grouped into competitive and non-competitive categories with 22 farmers classified as being competitive and 38 farmers as being non-competitive. From the results of logistic regression, 7 out of 12 hypothesised variables were found to be statistically significant, these were; age of farmer, number of trees planted, related and supporting industries, firm strategy structure and rivalry, chance, demand conditions and factor conditions. Chance was the only variable with a statistically significant v negative influence on the competitiveness of the farmers, this was because factors that were tested for their influence on the competitiveness of the farmers are among others: Crime, HIV/AIDS, fires, frost and floods. Based on the research findings, several policy suggestions were made, these include; mentorship and encouragement of youth participation in farming, provision of agricultural land, capacity building for farmers, government support and stakeholder mobilization, specialized extension service and formation of cooperatives as well as encouraging commercialization.

The baobab tree represents a major contribution to rural communities of the south-east lowveld of Zimbabwe. The livelihood base of the study area was largely rain-fed subsistence farming whose production has declined due to frequent droughts. Harvesting of baobab tree products; leaves, fruits and bark fibre, has prospered due to poverty. These products are harvested for food, medicinal use, cash and animal harness. A mixed method approach on collection of data was employed through questionnaires, semi-structured interviews, 48-hour dietary recall and Household Food Insecurity Access Prevalence (HFIAP) template. Sixty-eight households from Wengezi and Gudyanga communities participated in this study. All the respondents from the study area indicated they were involved in using baobab products in one way or the other. According to the information collected by the HFIAP template, 76% of the households were moderate to severe food insecure. Baobab bark harvesting was common in the Gudyanga and harvesters were aware of sustainable way of harvesting it. Value-addition on baobab fruit pulp to make ice-lollies and seeds roasted to produce a coffee substitute was practised by youth projects with the help of a non-governmental organisation. Ninety-five percent of the households in the study area were in support of the idea of possible baobab tree commercial cultivation in the community. The support was in anticipation of job opportunities and reduced food insecurity. / Agriculture and  Animal Health / M. Sc. (Agriculture)