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The impact of TGF-β on the genital immune environment associated with HIV risk in young women.
No full textMasters Degree. University of KwaZulu- Natal, Durban.Background: The HIV pandemic has disproportionally affected young women living in sub-Saharan Africa, with most new infections transmitted via condomless sex. Semen exposure is shown to increase several cytokines, cellular and barrier-related biomarkers of inflammation associated with HIV acquisition in women. The predominance of the anti-inflammatory transforming growth factor-beta (TGF-β) cytokine is well established in semen, and regulation of the cervical immune response is meant to facilitate conception. In this study, we investigated the contribution of TGF-β to the genital inflammatory profile linked to HIV risk in women.
Methods: This study included a subset of 132 CAPRISA 008 trial participants with a biannual sampling of genital specimens (N=641 visits). The presence of prostate-specific antigen (PSA) in cervicovaginal lavage (CVL) was determined by ELISA and indicated the likelihood of condomless sex and semen exposure within 48 hours of genital sampling. Multiplex ELISA assays were used to determine the concentrations of TGF-β isoforms 1, 2, 3 and 48 other cytokines in CVL specimens. Flow cytometrywas conducted to identify activated (CD38+, HLA-DR+, CCR5+ and/or Ki67+) CD4+ T cell populations among cervical mononuclear cells collected from cytobrushes. Multivariable linear mixed models assessed associations between TGF-β concentrations and semen exposure and with cellular and cytokine biomarkers of inflammation.
Results: TGF-β isoform concentrations were similar in CVL specimens with and without evidence of recent semen exposure. Further, independent of semen exposure, TGF-β1 detection and TGF-β3
concentrations were associated with significant decreases in multiple FRT cytokine concentrations. TGF-β1 detection and TGF-β2 concentrations significantly reduced multiple populations of activated CD4+ T cells at the FRT.
Conclusion: Although TGF-β isoforms were differentially expressed in the FRT and differed in the nature of their individual associations with local cytokine concentrations and cellular frequencies, their general relationship with reduced levels of genital cytokines and immune cells attests to their documented immunomodulatory effects. TGF-β concentrations were not associated with PSA detection, which likely indicates a normalisation of TGF-β levels in genital fluid within 48 hours after intromission. Although TGF-β concentrations were independently associated with dampening local cellular and cytokine levels, the previously observed relationship between semen exposure and increased levels of inflammatory biomarkers was maintained in the cohort. Further interrogation is required to determine the dynamics of intromitted or endogenous TGF-β and inflammatory biomarkers, the persistence of their immune impact, and the relation to HIV risk
Measuring the economic costs of trade protection in South Africa.
No full textMasters Degree. University of KwaZulu-Natal, Durban.This dissertation investigates the economic cost of trade protection on South Africa's economy through a panel analysis from 2010 to 2022, focusing on South Africa’s trade with 127 partner countries. The Gravity model serves as the main estimation framework for the study as it provides a detailed observation of international trade. The Poisson Pseudo Maximum Likelihood (PPML) and Ordinary Least Squares (OLS) estimation approaches serve as the main methods used to measure the effectiveness of the gravity model in the study. Through comparisons between OLS and PPML the study observes the elasticities of the determinants of trade across the OLS and PPML and affirms the need to focus on the PPML which reveals more reliable estimates which are neither underestimated nor overestimated the study confirms that trade protection leads to less trade activity, it will result to a reduction in gains from exports which is important in influencing the economic growth of South Africa. The research includes an in-depth analysis of tariffs, both as a standalone measure and as a variable within the gravity model as the main form of protectionism in international trade. The study highlights the evolving role of tariffs in trade protection and concludes that tariffs may have been overstated as a standalone measure of trade protection in studies of international trade. The study shows that tariffs have a more significant influence on trade in the PPML model as opposed to the OLS and the study shows that the PPML explains a larger degree of the effects on trade flows than the OLS does. The findings in the study suggest that the PPML method should be used for South Africa’s gravity model simulations due to the reliable elasticities that the model returns
The role of trees and the dynamics of tree planting as a climate change adaptation strategy for addressing food and nutrition security challenges in KwaZulu-Natal.
No full textDoctoral Degree. University of KwaZulu-Natal, PietermaritzburgOne of the major environmental problems faced by the modern world is climate change, and its impacts are rapidly escalating. Future predictions indicate that climate change will result in lower rainfall and higher temperatures with increased flooding and drought events in South Africa. Most studies report that the source of livelihood affected mainly by climate change is agriculture, especially crop productivity. Moreover, the agricultural sector is among the most significant contributors to changing climate. Globally, the sector contributes about 20% to greenhouse gas emissions. The effect of climate change on the agricultural sector, combined with the impact of agriculture on greenhouse gas emissions, requires adaptation strategies that will lessen the effects of agricultural production while mitigating climate change. Agroforestry is recognized as the most appropriate adaptation strategy to achieve these objectives due to its high potential for addressing food insecurity, climate change challenges, and ecosystem management. It is defined as a farming system that integrates trees and shrubs with agricultural crops and/or livestock, or both. Rural communities in South Africa have been planting trees, but what they deem important in trees is not well-known. Hence, identifying the different types of trees currently beneficial to them is essential for tree-planting programs to be successful. Moreover, there is insufficient empirical research on the following: the impact of fruit trees on food and nutrition security; the role and plantation of trees as a long-term and sustainable climate change adaptation strategy; and the role of knowledge, attitudes, perceptions, and extrinsic factors in the uptake of agroforestry practices among rural households. The objectives of the study were: to identify the different types of trees beneficial to rural communities and the main beneficial uses of these trees; to evaluate the potential contribution of trees towards food and nutrition security of rural communities; to investigate tree planting as a climate change adaptation strategy; and to examine the role of knowledge, attitudes, and perceptions in the uptake of agroforestry practices among rural households.
The study was conducted in Swayimane, Umbumbulu, and Richmond, located in the KwaZulu-Natal province, South Africa. The survey used a random sampling method to select and interview a total sample of 317 rural households from the three study locations. However, only 305 questionnaires were valid and used for analysis: Swayimane (92), Umbumbulu (103), and Richmond (110). The data were collected by trained enumerators in person using a structured and pre-tested questionnaire. In addition, focus group discussions were conducted to complement information collected during the household survey. Both descriptive and inferential statistics were employed in this study. Descriptive statistics included percentages, means, standard deviations, and standard errors. For the inferential statistics, a chi-square test, F-test, principal component analysis, binary logistic, multivariate probit, and ordered logit regression models were employed. The International Business Machines (IBM) Statistical Package for Social Sciences (SPSS) version 28 and STATA SE version 17 were used to analyze the survey data.
Moreover, bar charts were created using Microsoft Excel 2019 to organize and summarise data. The results showed that fruit tree species such as banana, peach, and orange played a vital role in improving food, medicinal, and financial security among rural households. Other tree species, such as Melia azedarach L., were used to adapt to climate change. For example, they function as windbreaks during windy weather. Medicinal tree species were used to treat human illnesses such as toothache, fever, and earache. Therefore, this study recommends the implementation of tree-planting programs and the distribution of fast-growing tree species across rural communities to improve their livelihoods. Improved allocation of resources to tree planting and maintenance by the public and private sectors can be a sound decision based on the benefits provided by trees. Regardless of the benefits of various trees, some respondents mentioned the disservices that result from trees. The results showed that ‘attracting snakes’ and ‘littering the yard’ were the dominant disservices across most fruit trees. It is recommended that rural households involved in tree planting be educated about methods of preventing snake invasion. Planting trees was the most common adaptation strategy in the study locations. Compared to other strategies, it emerged as a long-term and sustainable strategy. The multivariate probit model results showed that access to training and climate change information, land size, and psychological capital influence the adoption of tree planting as a climate change adaptation. This indicated the importance of agricultural-related training in climate change adaptation. Raising awareness of the benefits of trees through training programs is crucial in encouraging farming rural households to adopt tree planting as an adaptive measure. Moreover, most rural households indicated a lack of access to training on climate change adaptation strategies. It is recommended that extension officers, non-governmental organizations, policymakers, and other stakeholders support local-level knowledge of climate change adaptation and turn it into effective and sustainable action.
The ordered logit regression model findings showed that growing fruit trees and consuming wild fruits influenced household food insecurity and nutrition security. Households practicing fruit farming are more likely to have better access to food and consume acceptable diets. Growing fruit trees was negatively associated with household food insecurity and positively associated with nutrition security. This suggests that households practicing fruit farming are more likely to have better access to food and consume acceptable diets. To improve the plantation of fruit trees in rural households, this study recommends the dissemination of information on the benefits of fruit trees. The level of wild fruits consumption among the sampled rural households was low. This indicates a need for awareness campaigns promoting the utilization and consumption of wild fruits. Encouraging rural households to consume wild fruits may reduce food insecurity through improved dietary diversity. It may also reduce reliance on purchased food items. Knowledge, attitudes, and perceptions towards agroforestry were found to positively influence the adoption of agroforestry practices. The results showed that the likelihood of adopting agroforestry was higher among knowledgeable household heads than those without knowledge. Thus, educating rural households about trees’ economic and environmental benefits could increase tree cover in the agricultural landscape. Implementing training programs with practical demonstration is recommended to increase awareness of the benefits of agroforestry practices and encourage households to protect onfarm trees. Extension officers, climate change champions, researchers, policymakers, and other stakeholders need to join forces in public-private partnerships to collectively participate in distributing adequate knowledge on agroforestry practices and their advantages to rural households. Moreover, addressing institutional and service constraints such as access to tree saplings and agricultural equipment, financial constraints, and water availability is vital to enhance the adoption and expansion of agroforestry practices
Integration of educational technology resources in the teaching of grade 10-12 life sciences.
No full textMasters Degree. University of KwaZulu-Natal, Durban.The use of Educational Technology resources has brought numerous benefits in the education system such as enhancing the teaching and learning process. Furthermore, integrating educational technology resources fosters inclusive education and offers an engaged learning environment where learners acquire the 21st century skills relevant in this digital age. This study explored the integration of Educational Technology resources in the teaching of grade 10-12 Life Sciences. The study was carried out in four different high schools in the urban, rural and township of Eshowe town. This qualitative case study adopted the interpretive paradigm, involving four teachers purposively and conveniently selected. The study used reflective activities, one-on-one semistructured interviews and observations to generate data. The generated data was analysed using thematic analysis. The emerging themes formed the main findings of the study. In addition, Connectivism was employed as a philosophical lens to guide this study.
The findings of the study indicated that participants integrated similar hardware and software resources to teach Life Sciences. These included textbooks, overhead projectors, anatomical models, charts, laptops, videos and WhatsApp. The findings further reveal that participants were integrating these successfully in conjunction with the whole-class strategy but for different personal reasons. For instance, while some participants were using textbooks for assessing, others used them for visuals, and while other teachers were using OHPs to display notes some used them to display videos or pictures. Based on the study findings, it is recommended that teachers be equipped with more knowledge of other software and hardware resources such as YouTube, and apparatus. In addition, the study also recommends that teachers draw from the curriculum policies to integrate relevant educational technologies as formally prescribed
The role played by religion and spirituality in the rehabilitation of former gang members in the Durban Metropolitan.
No full textMasters Degree. University of KwaZulu-Natal, Durban.Gangsterism is not a new problem and is not inherent to South Africa alone. However, the problem is widespread in South Africa and within the city of Durban and it is surrounding areas. Durban has been plagued by the overwhelming and increasing number of gang-based crimes. Minimal studies addressing this problem in Durban have been published. Most studies have been on the gangs of the Western-cape and the prison number gang system. It is not uncommon that active and former gang members try to desist from gang life and pursue a path of rehabilitation and reintegration into society. Nor is it uncommon for them try to re-invent themselves to achieve pro-social identities. Religiosity has always been a powerful desister in combatting criminality. It has served as a platform for gang rehabilitation and disassociation amongst gang members globally. This study intricately studies the role of religion/spirituality in the lives of former gang-members by reflecting on the lives of people who had once adopted this aspect of criminality. This study adopted a qualitative approach embedded within the interpretivist paradigm. This study is founded on the Desistance theory of criminology. Data was collected using in-dept interviews with 10 purposively selected participants. The approach and techniques utilized in this study are described concisely to provide a clear picture of how data is collated, and the researcher has used what academics refer to as the “journey motif” to accurately and rationally describe the research setting as well as provide grounds for the research design considered ideal for this study. The findings have shown that each participant had life changing experiences that served as a precursor for desistance and that religion was at the core, filling in the gaps of the lives they once pursued. Findings revealed that life-changing experiences, alongside spirituality and religious practices, played a key role in gang disengagement. Psycho-social factors contributed to initial gang involvement, while desistance was met with challenges such as fear for safety, estrangement from family, and financial loss. Some participants maintained ties with former gang associates despite leaving the lifestyle. Spirituality facilitated identity reconstruction and personal growth. The study highlighted the significance of faith-based interventions in promoting long-term desistance and reintegration
The impact of the collaboration between University of the Free State ideas lab and the Free State Department of Education on the academic achievement by Grade 12 learners.
No full textDoctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.This study was conducted to determine the impact of the collaboration between the University of the Free State ideas lab and the Free State Department of Education on the academic achievement by Grade 12 learners. A dominantly post-positivist paradigm was adopted, using the combined (quantitative and qualitative) approaches. The quantitative part of the study made use of historical secondary data representing the pass marks of the selected Grade 12 learners in the Free State Province, which spans a five-year period (2014-2018). The qualitative part used interview data drawn from interactions with teachers from the selected schools (Further Education and Training Band) within the Motheo District of the Mangaung Metropolitan, the Motheo FET schools’ district subject specialists in three selected Grade 12 subjects under study, Free State Department of Education (FSDoE) head office FET schools’ subject specialists in three Grade 12 subjects that formed part of the study and staff from the University of the Free State’s (UFS) Internet Broadcasting Project (IBP). Data collected in the form of the secondary data representing pass marks of Grade 12 learners between 2014 and 2018, was analysed using the statistical Package for Social Sciences (SPSS 29.0) to generate descriptive and inferential statistics, two-way ANOVA (Univariate Analysis of Variance, Descriptive statistical Dependent Variable, Levene’s Test of Equality of Error Variances and Profile Plots) for all the three selected subjects (English First Additional Language, Mathematics and Physical Science). The qualitative data in the form of interviews (teachers, FSDoE district, FSDoE head office specialist and UFS ideas lab staff) was analyzed, using content analysis and thematic analyses using the NVivo, a software that analyses qualitative data. The adopted theoretical framework was the original Unified Theory of Acceptance and Use of Technology (UTAUT) by Venkatesh, Morris, Davis and Davis (2003). The model’s constructs were aligned to the results obtained from the qualitative data to make sense of the impact the IBP has on achievement of the Grade 12 learners in the Free State Province. Ethical considerations were made regarding informed consent forms, approval seeking, permission and confidentiality. The response from the teachers showed that they were not only comfortable with the use of IBP, but also the commitment of their learners made it easier to integrate the technology in teaching and learning. Social influence like the other three constructs (PE, EE and FC) was equally influencing behavioural intention and ultimate usage of the IBP in teaching and learning. There was also a positive relationship between the UTAUT constructs and the dependent variable (achievement). The findings also showed that there was a better performance by IBP schools in comparison to the non-IBP, thus confirming that the technology had a significant impact on the Grade 12 learners’ achievement. The findings further indicated that the IBP service was evolving and increasing its portfolio to respond to the ever-changing times, thus ensuring that performance was sustainable, and the service was on par with the rest of the world. The study recommended that the focus should shift from the quantity or high number of passes to quality or improvement in Bachelor passes at higher levels of performance. Another recommendation is to consider expanding access to the IBP to all public high schools to ensure that all leaners have equal chances to achieve at higher levels, due to equal access to similar quality education that is offered through the integration of the IBP in teaching and learning.Abstract only available in English in PDF document
A critical evaluation of some of the unintended consequences of the mandatory minimum sentencing legislation in South Africa.
No full textMasters Degree. University of KwaZulu-Natal, Pietermaritzburg.The Criminal Law Amendment Act 105 of 19971 (the Act) requires the imposition of mandatory minimum penalties for specific criminal offences. However, it also allows the presiding officer of the court to depart where is it determined that substantial and compelling circumstances are present. This research seeks to evaluate the diverging interpretations of substantial and compelling
circumstances by our courts as an unintended consequence of the mandatory minimum sentencing scheme. Although the legislature has not defined substantial and compelling circumstances, the case of S v Malgas2 provided guidelines that can be used by courts whenever faced with the question of what are substantial and compelling circumstances. Despite the guidelines provided, some cases still show uncertainty regarding this phrase and some judgements tend to completely disregard the importance of the constitutional considerations of proportionality and the need to still consider the traditional sentencing principles, this is an unintended consequence of the Act owing to the lack of clarity regarding substantial and compelling circumstances. The Minimum sentences scheme contains unexplained inconsistencies which have resulted in the diverging interpretations of compelling and substantial circumstances by our courts, this inconsistency can be seen in the lack of gradation for increasing levels of offence severity (sentencing cliffs) that are evident in the prescribed sentences for rape, some courts have required a higher showing of violence in order to not depart from the prescribed sentences. Some cases have used the prospect of rehabilitation as justification for a departure. This is problematic because the latter factor is present in most cases, as a result, this would lead to unnecessary and unexplainable departures which would then circumvent the legislatures intention in ensuring consistent sentences. This raises questions of whether courts are paying attention to some of the inconsistencies that result from their judgements. This research also looks at prison overcrowding as an unintended consequence of the Act, this is because the Act limits the individualisation of cases thus leading to more offenders receiving lengthy sentences. Courts are expected to consider the relevant factors of each individual case however this is not properly adhered to because the act uses few sentences for different crimes without proper explanation thus affecting prison overcrowding
The implementation of the monitoring and evaluation (M&E) system in government departments: a case study of the KwaZulu-Natal department of social development.
No full textMasters Degree. University of KwaZulu-Natal, Pietermaritzburg.The study is centred on “The Implementation of the Monitoring and Evaluation (M&E) System
in Government Departments: A case study of the KwaZulu-Natal Department of Social
Development”. The Ministry of Performance Monitoring and Evaluation began in 2009, and
the Department of Performance Monitoring and Evaluation (DPME) was established in January
2010. The Department of Social Development (DSD) Annual Reports for 2017/18 and 2018/19
contained the Auditor General’s audit outcomes of the Department of Social Development
performance information. The audit/s revealed undesirable audit outcomes, with the
department. Government departments should be effective in service delivery and efficient in
allocating funds for service delivery programmes. The government is expected to report on its
budget, programmes and achievements. The South African government has instituted a range
of legislative and policy changes. The KwaZulu-Natal Department of Social Development’s
mandate is to be delivered according to the South African Constitution and provide an effective,
transparent, accountable and coherent intergovernmental system for provincial governments.
This study seeks to understand the implementation of the Monitoring and Evaluation System
in the KwaZulu Natal Department of Social Development. The study objectives examine the
implementation of the M&E system in the KwaZulu-Natal Department of Social Development
and understand the role of monitoring and evaluation in the KwaZulu-Natal Department of
Social Development. The qualitative research study employed the qualitative research design.
This included interviews for data collection and a thematic strategy for data analysis. The study
employed the theory of change. The findings show capacity gap between national, provincial,
and local government organizations influences evaluations' credibility.The study
recommendations support the assertion that M&E contributes to effective programme
implementation and a level of good governance; an integrated approach is recommended and
emphasised to recognise the multi-faceted nature of social problems
Application of unmanned aerial systems for crop discrimination in smallholder farms.
No full textDoctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.Agriculture is the cornerstone of global food security, serving as humanity’s principal source of sustenance and the primary supplier of critical crops. A crucial challenge facing society is ensuring food security for a rapidly growing population, projected to exceed nine billion by 2050. With limited opportunities to expand arable land, improving agricultural productivity has become indispensable to meet escalating global food demand. Thus, there is a need for robust, precise, holistic agricultural intelligence systems to monitor and optimise crop production. This is particularly so, in regions characterised by heterogeneous smallholder farming systems dominated by mixed cropping. The ability to identify and monitor individual crop types is fundamental for optimising resource allocation, informing targeted interventions, and ultimately enhancing agricultural productivity. Unfortunately, the use of traditional groundbased methods for crop identification has been deemed labour-intensive, time-consuming, and spatially limited, rendering them inadequate for large-scale or frequently updated crop assessments. Thus, the efficacy of remote sensing technologies has been proven in acquiring synoptic and multi-temporal data that is crucial for agricultural monitoring and management. Among the suite of remote sensing platforms, unmanned aerial systems (UASs) have garnered significant attention due to their capacity for near-real-time data acquisition at high spatial resolutions. Equipped with increasingly sophisticated yet miniaturised and lightweight sensors, UAS offers a flexible and cost-effective alternative to traditional aerial and satellite imagery, particularly for localised agricultural applications. The advancements in geospatial technologies have facilitated critical data collection on various farm tasks, with crop discrimination and classification as key focus areas. However, despite the evident potential of UAS in agriculture, several bottlenecks have been identified, including lack of comprehensive information regarding optimal UAS configuration, sensor characteristics tailored for specific crop discrimination, and robust data processing and analytical methodologies applicable across diverse cropping systems. Given this background, this study sought to (i) systematically review the current state, challenges and opportunities in the application of unmanned aerial systems for crop discrimination, (ii) determine the optimal field parameters, specifically the number of crop species and crop row widths, that facilitate accurate crop discrimination and (iii) develop techniques that distinguish crop types in a mixed cropping setting, owing to the flexibility and cost-effectiveness of UASs particularly for localised agricultural applications. This thesis addresses the overarching challenge of achieving accurate and reliable crop discrimination, explicitly focusing on the prevalent mixed-cropping system of maize (Zea mays) and soybean (Glycine max), which are of significant economic and nutritional importance in regions of sub-Saharan Africa. The thesis focused on multiple investigations employing a range of remote sensing data modalities and analytical techniques to tackle the complexities inherent in distinguishing spectrally and structurally similar crops within heterogeneous agricultural environments. The first objective was to systematically review the current state, challenges and opportunities in the application of unmanned aerial systems for crop discrimination. This was followed by examining the spectral separability of maize and soybean across different growth stages using hyperspectral data. Thirdly, the thesis evaluated the utility of spectral, textural and morphological features derived from UAS-based RGB imagery to distinguish maize and soybean from other objects. This was followed by developing a novel technique for shadow detection in RGB datasets. Lastly, the thesis developed a hybrid approach by integrating segmentation and pixel-based classification to provide a comprehensive understanding of effective remote sensing strategies for enhanced crop discrimination in mixedcropping systems. The ultimate goal is to contribute to advancing precision agriculture practices, particularly in resource-constrained settings, where accurate and timely information on crop distribution is paramount for sustainable agricultural development. This explores different facets of crop discrimination in mixed-cropping systems, which are a characteristic of smallholder farming systems in most developing countries. The second objective sought to investigate the spectral separability of maize and soybean at different phenological stages based on field experiments. To achieve this, hyperspectral data spanning the visible to near-infrared spectrum (400–1100 nm) were employed to evaluate the spectral signatures of these two crops across five critical growth stages. The integration of statistical analysis (ANOVA), distance (Jeffries-Matusita distance) and divergence metrics (Transform Divergence, Kullback-Leibler Divergence), and machine learning algorithms (Partial Least Squares-Discriminant Analysis (PLS-DA)) provided a robust framework for optimising band selection and identifying critical phenological stages for discrimination. The key findings of this study revealed that peak spectral separability occurred during the reproductive stages (85– 110 days after planting), with the red spectral region (600–700 nm) exhibiting maximum divergence, attributed to differences in chlorophyll dynamics. Notably, PLS-DA achieved nearperfect classification accuracy (100% F1-score) at the mid-grain filling stage (DAP 85), highlighting the efficacy of leveraging red-edge (680–750 nm) and near-infrared (700–1100 m) bands during this period. Conversely, minimal separability was observed during early vegetative stages due to spectral overlap. This research underscores the need to consider phenological timing and specific spectral regions for effective crop discrimination using hyperspectral data, offering valuable insights for designing targeted remote sensing surveys. The third objective leveraged the increasing accessibility and affordability of UAS-based RGB imagery to evaluate the utility of spectral, textural, and morphological features for distinguishing maize and soybean in a mixed-cropping environment. High-spatial-resolution RGB images were captured during the tasselling stage of maize (48 days after planting) using a DJI Matrice 300 drone. Due to persistent cloud cover and rainfall during the summer, data acquisition was constrained; consequently, only DAP48 observations were obtained during the reproductive and maturity stages. By extracting a comprehensive set of 26 variables encompassing spectral indices, textural features, and morphological transformations, the study employed a random forest (RF) algorithm for supervised classification. The results emphatically demonstrated the superior performance of morphological features, achieving the highest classification accuracy (0.93) and F1-score (92%), followed by a combination of textural and morphological features. Spectral features alone proved to be the least effective. Morphological features, capturing canopy structure and plant geometry, outperformed spectral and textural traits, highlighting the limitations of spectral-only approaches in mixed-cropping systems. Although these features focusing on the structural and geometrical features of maize and soybean were successful, the results revealed that RGB datasets in smallholder farms were compromised by shadows, which disproportionately increase spectral overlap. To address the problem of shadows that are prevalent due to mixed cropping with varying plant heights, particularly in smallholder farming systems, the fourth objective developed a novel hue-intensity-green-blue (HIGB) difference technique. The performance of this new technique was rigorously compared against established methods (C3 and normalised saturation-value difference index) using RGB datasets from experimentally manipulated maize and soybean mixtures. The HIGB technique, based on the differences between hue and intensity and the green and blue channels, consistently outperformed the benchmark models (C3 and NSVDI) across various shadow conditions, achieving overall accuracies ranging from 77% to 95%. This robust performance, even in scenarios with dark or obscured shadows, underscored the practical utility of the HIGB technique for improving the reliability of crop discrimination efforts using RGB imagery. The HIGB technique performs robustly under varying lighting conditions, nderscoring its value as a critical preprocessing tool for improving crop discrimination. Furthermore, the thesis proposed an alternative light intensity ratio-based (LIRB) approach for shadow removal using RGB imagery. This method is applicable in areas where shadow pixels are sparse; however, it did not fully meet expectations. The approach struggled to reconstruct or eliminate dense shadows, resulting in the introduction of blurry artefacts. These artefacts significantly compromised the overall objective of accurately detecting actual crop acreage within a mixed cropping system. By understanding the limitations of LIRB, the last chapter focused on developing a hybrid classification framework integrating region-based segmentation and pixel-based machine learning. This approach was proposed to tackle the spectral and structural complexity of heterogeneous agro-ecological landscapes by focusing on vegetation pixels only. This method leverages simple linear iterative clustering (SLIC) superpixels to group spectrally similar pixels into meaningful and targeted regions, followed by extracting texture and structural features from these segments. These multi-faceted features were then used to train robust machine learning classifiers: Random Forest and Extreme Gradient Boosting. The experimental results demonstrated remarkably high detection accuracy, with precision, recall, and F1-scores exceeding 0.98 for both classifiers. Feature contribution analysis revealed that mean intensity and standard deviation features derived from SLIC were the most influential, followed by textural and morphological traits. Integrating diverse features substantially reduced error rates from 8% (SLIC-only) to 1% with multi-feature integration, demonstrating the synergistic benefits of combining segmentation, feature fusion, and ensemble learning. This research strongly suggests the benefits of employing such a robust hybrid approach, combining the strengths of segmentation and pixel-based methods and advanced machine learning classifiers to achieve scalable and high-resolution crop mapping in complex agricultural environments. In conclusion, these findings provide actionable strategies for mapping and monitoring crops in smallholder systems, where technical and financial constraints limit multispectral adoption. By prioritising accessible RGB sensors, simple algorithms, and phenological timing, this work supports scalable precision agriculture in developing countries, ultimately aiding food security and sustainable land management. The research highlights the importance of considering the phenological stage and leveraging specific spectral regions, as demonstrated by the hyperspectral analysis. It also underscores the significant role of morphological features derivable from UAS-based RGB imagery for effective crop differentiation. Finally, the proposed hybrid segmentation-classification approach showcases the potential for integrating diverse features and advanced machine learning algorithms for achieving high accuracy in heterogeneous landscapes. The collective insights from these investigations contribute significantly to precision agriculture, offering valuable methodologies and findings that can be further developed and implemented for improved crop monitoring and management, especially in resource-constrained agricultural systems prevalent in regions like sub-Saharan Africa (SSA) and similar environments worldwide. Future research should focus on translating these ground and UAS-based insights to satellite platforms, enabling broader regional scalability while maintaining accuracy in complex cropping systems. Further research could also focus on integrating these diverse approaches, exploring the transferability of these techniques across different crop types and geographical locations, and developing user-friendly tools for practical implementation by agricultural stakeholders
Characterization of groundwater quality in Small Island developing states (SIDS): a case study in the island of Mauritius.
No full textDoctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.This thesis presents a systematic investigation of groundwater systems in Mauritius through three interconnected studies examining temporal patterns, climate impacts, and flow dynamics. The research addresses the knowledge gaps regarding groundwater vulnerability in Small Island Developing States (SIDS) while developing a framework for sustainable resource management. The temporal analysis spanning 2010-2021 revealed significant trends in groundwater quality across Mauritius's five major aquifers (Aquifer I: Curepipe-Vacoas-Flic en Flac; Aquifer II: Phoenix-Beau Bassin-Albion-Moka-Coromandel; Aquifer III: Nouvelle France-Rose Belle- Plaisance; Aquifer IV: Nouvelle Découverte-Plaine des Roches-Midlands-Trou d'Eau Douce; and Aquifer V: Northern Aquifer). Conductivity showed decreasing trends in four aquifers (- 0.09 to -0.40 μS/cm per month), while pH demonstrated significant changes in Aquifers II and V. Total Dissolved Solids decreased notably in Aquifers I and II (-0.12 and -0.18 units/month respectively), indicating spatially variable water quality evolution. The investigation of climate impacts revealed generally weak correlations between groundwater quality and climate indices. The 12-month Standardized Precipitation Index showed strongest correlations with sulphate in Aquifers II and III (r = -0.40 and -0.33), while global climate modes demonstrated minimal influence. Analysis of Cyclone Esami (January 2020) indicated short-term impacts on water quality parameters, though data limitations prevented a complete statistical analysis of extreme event impacts. Isotopic analysis conducted during 2022-2023 using 67 boreholes across all five aquifer systems revealed distinct spatial and temporal patterns in groundwater composition. Results showed δ2H values ranging from -22.8per mil to -5.6per mil and δ18O values from -4.2per mil to -1.56per mil, with systematic variations corresponding to elevation and aquifer characteristics. Inter-aquifer connectivity was evident between Aquifers I and II, while Aquifer V showed clear evidence of marine influence with elevated chloride concentrations (42 mg/L) and enriched isotopic signatures in coastal areas. The research provides a framework for assessing groundwater vulnerability in SIDS through integration of temporal trend analysis, climate correlation studies, and isotopic characterization. Key findings include the importance of spatial heterogeneity in system response, the primacy of local hydrogeological conditions over regional climate patterns, and the need for spatially targeted management approaches. These insights enable development of evidence-based strategies for sustainable groundwater management in SIDS contexts