Much older soils data and soils information lies idle in libraries and archives and is largely unused, especially in developing countries like Kenya. We demonstrated the usefulness of a stepwise approach to bring legacy soils data ‘back to life’ using the 1980 <i>Reconnaissance Soil Map of the Busia Area</i> <i>(quarter degree sheet No. 101)</i> in western Kenya as an example. Three studies were conducted by using agronomic information, field observations, and laboratory data available in the published soil survey report as inputs to several digital soil mapping techniques. In the first study, the agronomic information in the survey report was interpreted to generate 10 land quality maps. The maps represented the ability of the land to perform specific agronomic functions. Nineteen crop suitability maps that were not previously available were also generated. In the second study, a dataset of 76 profile points mined from the survey report was used as input to three spatial prediction models for soil organic carbon (SOC) and texture. The three predictions models were (i) ordinary kriging, (ii) stepwise multiple linear regression, and (iii) the Soil Land Inference Model (SoLIM). Statistically, ordinary kriging performed better than SoLIM and stepwise multiple linear regression in predicting SOC (RMSE = 0.02), clay (RMSE = 0.32), and silt (RMSE = 0.10), whereas stepwise multiple linear regression performed better than SoLIM and ordinary kriging for predicting sand content (RSME = 0.11). Ordinary kriging had the narrowest 95% confidence interval while stepwise multiple linear regression had, the widest. From a pedological standpoint, SoLIM conformed better to the soil forming factors model than ordinary kriging and had a narrower confidence interval compared to stepwise multiple linear regression. In the third study, rules generated from the map legend and map unit descriptions were used to generate a soil class map. Information about soil distribution and parent material from the map unit polygon descriptions were combined with six terrain attributes, to generate a disaggregated fuzzy soil class map. The terrain attributes were multiresolution ridgetop flatness (MRRTF), multiresolution valley bottom flatness (MRVBF), topographic wetness index (TWI), topographic position index (TPI), planform curvature, and profile curvature. The final result was a soil class map with a spatial resolution of 30 m, an overall accuracy of 58% and a Kappa coefficient of 0.54. Motivated by the wealth of soil agronomic information generated by this study, we successfully tested the feasibility of delivering this information in rural western Kenya using the cell phone-based Soil Explorer app (<a href="https://soilexplorer.net/">https://soilexplorer.net/</a>). This study demonstrates that legacy soil data can play a critical role in providing sustainable solutions to some of the most pressing agronomic challenges currently facing Kenya and most African countries.<div><p></p></div>

Thesis (M. Sc. Agriculture (Agricultural Economics)) -- University of Limpopo, 2021 / The President of South Africa signed the National Minimum Wage Act, the amendment of both the Basic Conditions of Employment Act and Labour Relations Act on Friday, 23 November 2018. These Acts, which were with effect from 1 January 2019, oblige all employers to pay at least the national minimum wage of R20.00/hr. and the agricultural sector has been given an exemption to pay 90% respectively of the national minimum wage (Truter, 2018). Employers in the farming sector are expected to pay at least R18.00 per hour to farm workers. However, farmers are different in terms of their characteristics and farming capacities, and they hold different perceptions towards the revised 2018 agricultural minimum wage. According to Sechaba (2017), it is believed that there will always be different views on what constitutes a decent and acceptable minimum wage. This study investigated the perception of both smallholder and commercial farmers towards the 2018 agricultural minimum wage in Bushbuckridge Local Municipality of the Mpumalanga Province, South Africa. The study had three objectives; the first objective was to identify and describe the socio-economic characteristics of farmers, the second one was to assess the perception of farmers on the 2018 agricultural minimum wage and the third one was to analyse socio-economic factors influencing the perception of farmers towards agricultural minimum wage in Bushbuckridge Municipality. Purposive sampling was used to collect primary data from 160 smallholder and commercial farmers (Crop and Livestock) in Bushbuckridge Local Municipality (BLM). For empirical analysis the Multinomial Logistic Model was applied for data analysis based on information generated using the Likert scale and the two formulated assumptions; firstly, farmers do not have negative perceptions towards the 2018 agricultural minimum wage and lastly socioeconomic factors do not influence farmers’ perception towards the 2018 agricultural minimum wage. For empirical analysis, Multinomial logistic regression model was run on spss and the descriptive statistics was used to analyse the perception of famers based on the rank data from the Likert scale. Results from Multinomial regression analysis indicated that demographic factors such as number of hectares, household size, age, farming experience, marital status, and labour productivity were found to be significant vi (at 1, 5 and 10%) in distinguishing between pairs of groups and contribution, which they make to change the odds of being in one dependent variable group rather than the other. About 48.8% sampled farmers in Bushbuckridge Local Municipality showed negative perceptions towards the 2018 agricultural minimum wage and were not likely to comply with the 2018 agricultural minimum wage legislation in a sense that they had not been paying the prescribed agricultural minimum wage to farm workers. Those who had positive perceptions and were willing to comply were only 15.0% and those who were uncertain on whether to comply or not comply with the 2018 agricultural minimum wage were 36.2%. Therefore, it can be concluded from results that smallholder and commercial farmers perceive the agricultural minimum wage differently and with majority of them not willing to comply or pay the prescribed amount. Additionally, several factors influences the perception on whether farmers were likely to comply or not to comply by paying the prescribed minimum wage to farm workers, based on the 2018 agricultural minimum wage. Variables: number of hectares, household size, age, experience, marital status and minimum wage were found to be significant (at different significant levels 1, 5 and 10%) in determining whether farmers were more likely or less likely to comply and pay the 2018 agricultural minimum wage. These variables plays a key role in determining farmers’ decision to comply or not to comply with the 2018 agricultural minimum wage. However, gender, minimum wage for farmers, distance to market, access to mechanisation, co-operative membership, access to news, pensioner and educational status were found to be insignificant (at different significant levels 1%, 5% and 10%) at determining whether farmers were likely to comply or not comply with the 2018 agricultural minimum wage. Thus, it is recommended that farmers, regardless of their production scale should be consulted and given a fair platform to articulate their views during the process of policy formulation. Policy makers and government should refrain from using a blanket approach when formulating a policy and taking into consideration the issue of disparities in the agricultural sector, subsectors, regions and operational scale of farmers when discussing the agricultural minimum wage policy.

No description available.

No description available.

Thesis (M.Dev. (Planning and Management)) -- University of Limpopo, 2022

No description available.

<p>  </p> <p>Plant-parasitic nematodes are amongst the most important pathogens impacting crops. Potatoes and soybean are vital crops for rural livelihoods and essential for food security, but their cyst nematode parasites remain a significant constraint globally. <em>Globodera</em> and <em>Heterodera </em>species are amongst the most damaging and internationally recognized quarantine pests of these crops, causing up to 80% yield loss. Their second stage juveniles (J2s) penetrate the host plant root tips and establish a residence close to the vascular bundle from where they extract nutrients as they complete their life cycle. Restrictions of control chemicals have led to an urgent need for alternative control strategies for cyst nematodes. Biological control is a promising alternative control measure, and fungi possess many characteristics that could make them great biological control agents of cyst nematodes. Most nematode populations are thought to be regulated by their natural enemy community. It is unclear which fungi are best adapted as natural enemies of these parasites and how they might do this. This project aimed to (a) characterize and compare the mycobiome diversity of cyst nematode species; (b) isolate and characterize fungi associated with potato and soybean cyst nematodes (c) screen isolated fungi for their efficacy as biocontrol agents against cyst nematodes; and (d) describe any isolated fungi identified as new and having potential for cyst nematode antagonism. Cyst populations were collected from different regions and screened for fungi using culture-based methods. For our next-generation sequence data analysis, we found differences in fungal community assemblages between center of origin of the potato cyst nematode (Peru; South America) and the regions where these nematodes were introduced such as Europe and North America.  There was no significant difference in fungal community assemblages of cysts collected between the years 2019 and 2020. We characterized fungi associated with the cyst nematodes and found that the most frequently isolated genera were <em>Fusarium, Penicillium, Cylindrocarpon, Phoma, Aspergillus </em>and<em> Verticillium</em>. Filtrates from <em>Trichoderma</em> sp. 2, <em>Alternaria alternata, </em>and <em>Fusarium acaciae-mearnsii </em>were toxic on SCN eggs while <em>Purpureucillium lilacinum, Fusarium proliferatum</em> and <em>Aureobasidium</em> <em>ellingtonae </em>sp. nov. were toxic on PCN eggs and juveniles. A new species of <em>Aureobasidium</em> isolated from the potato cyst nematode (<em>Globodera ellingtonae</em>) for the first time, and having biocontrol potentials against this nematode, was also identified, and described. </p>

Many authors and practitioners involved in rural or local development agree that co-operation and the integration of efforts by the delivery agents is crucial for sustainable development programmes. The delivery of Land Reform as initiated by the new government in South Africa (SA) is one programme that has been faced by a number of challenges including the slow pace of delivery, lack of support and co-operation from the key stakeholders, negligible impact on the improvement in the lives of its beneficiaries and many others. Many Land Reform participants including the government argue that among the challenges facing this programme is a lack of co-operation between the key stakeholders including the different spheres of government involved or impacted upon by the delivery of the Land Reform programme. The Department of Land Affairs (DLA) which is responsible for Land Reform delivery is facing challenges in integrating Land Reform with the rural or local level development which is facilitated by the local and district municipalities through the Integrated Development Planning (IDP) process. This thesis seeks to look at how the Land Reform planning process and the internal spatial data systems within the DLA can be used to integrate Land Reform delivery with the municipal IDP processes to attain integrated rural development. There is a growing realization of the fact that the development of an integrated spatial data is critical for sustainable development in SA. A number of initiatives have been embarked upon by various organizations to establish the spatial data infrastructure. However these efforts have been reported to be often fragmented and isolated in the areas of operation and focus. Thus, the challenge is to develop a strategy to develop an integrated spatial data infrastructure that would be used to support sustainable development programmes such as the Land Reform programme. This thesis therefore proposes to look at the various data sources particularly within the DLA and from other organs of state involved in Land Reform and local development with a view to highlight the limitation and shortcomings that can be addressed in integrated spatial data infrastructure. To assess the current status of the spatial data sources and usage for Land Reform implementation, an analysis of the spatial data sources within the DLA was conducted to determine its suitability for the development of an integrated spatial data infrastructure. Different sections of the DLA responsible for acquiring and providing spatial data were assessed to ascertain whether their data can be shared, transferred or integrated to support the Land Reform implementation. An integrated spatial data infrastructure is then proposed as a solution to forge co-operation and collaboration among all users involved in Land Reform implementation. / Thesis (M.Sc.) - University of KwaZulu-Natal, Pietermaritzburg, 2006.

Land reform in South Africa has not been very successful. The process of land delivery has been slow and livelihoods in South Africa are becoming increasingly vulnerable as land reform fails to meet its objectives. Since 1994, millions have been made homeless due to farm evictions that have counteracted the positive impact of land reform. Intensive debate has been initiated about the approach to land reform; however, current programme-specific information has been unreliable in providing insight into the impact of land reform projects that have been implemented. This thesis exammes the Land Redistribution for Agricultural Development (LRAD) programme, to determine how it can be enhanced to improve the lives of the programme's intended beneficiaries. Monitoring and evaluation is examined as a tool for improving programmes. This research also explores some of the shortcomings of the current monitoring and evaluation mechanisms for land reform. It is proposed that the LRAD programme should have a comprehensive ME promulgation of appropriate new land reform policy. An LRAD project at Loteni in rural KwaZulu-Natal is used as a case study and exposes some of the contextual challenges for LRAD policy. The qualitative analysis given provides insight into some of the problems of implementing the programme and reveals challenges for extension support. As a result of this critique, some recommendations are provided for improving the performance of LRAD. Key among the recommendations made to enhance LRAD is a set of measurable indicators for each of the stated objectives of the LRAD programme. Adopting such indicators will enable the programme to contribute to the improvement ofthe lives and livelihoods of the intended beneficiaries ofLRAD. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2007.

The study focused primarily on the socio-economic benefit(s) of land reform beneficiaries with regard to food security. The study further investigated the socio-economic impact of selected land reform projects in the Limpopo Province which is also very critical for many parts of South Africa. Apart from the traditional output based evaluation of land reform projects, the study managed to identify key significant variables that could be the focus in reforming land reform projects in the future. The study also highlights variables that could contribute positively or negatively to the attainment of socio-economic deliverables of the objectives of land reform. The conclusive data for the study was obtained from 170 beneficiaries of the land reform programme. Beneficiaries have benefited from Land Redistribution and Agricultural Development (LRAD) and Settlement Land Acquisition Grant (SLAG) sub-programmes of land reform in the area of Elias Motsoaledi Local Municipality within the Greater Sekhukhune District Local Municipality. The Multinomial Logic Model (MLM) was regarded as the best model for data analysis and was used to analyse the degree of contribution of socio-economic factors to food security among beneficiaries of LRAD and SLAG. Three categories were selected to determine the level of beneficiaries satisfaction with food security, namely; 1) None; 2) Moderate and 3) High. Dependent variables selected were 1) Number of beneficiaries, 2) Gender, 3) Farm size/ha, 4) Enterprise, 5) Land reform sub programme, 6) Proximity to the project, 7) Decision, 8) Knowledge, 9) Skills, 10) Training, 11) participation in Development organisation, 12) Sustaining production, and 13) Sustaining financial obligation. The study indicated that the participation of beneficiaries in decision making could contribute positively to the attainment of food security. A positive relationship with food security was determined and confirmed the study hypothesis. Knowledge was also found to have a significant relationship with the attainment of household food security. Knowledge was again found linked to training of beneficiaries which in general was inadequate. The study further revealed that almost all beneficiaries were failing to maintain production and financial obligations. Contrary to the hypothesis, enterprise was not found to be significant to the attainment of beneficiaries’ household food security. v The study concluded that land reform is still relevant to food security in the area. It was also concluded that there is a need to develop a comprehensive agricultural development plan to advance the objective of the land reform programme. / Agriculture, Animal Health and Human Ecology / M.Sc. (Agriculture)