DSpace 9

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DSpace is the world leading open source repository platform that enables organisations to:

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Applied Science
Faculty of Applied Science
Built Environment
Faculty of the Built Environment
Business and Economic Sciences
Faculty of Business and Economic Sciences
Communication and Information Science
Faculty of Communication and Information Science
Engineering
Faculty of Engineering

Recent Submissions

Leveraging Internet of Things and Artificial Intelligence in Smart Agriculture to Enhance Food Security and Sustainable Farming: A Systematic Review
(Scientific Journal of Informatics, 2026-08) Ndlovu, B.; Maguraushe, K.
Purpose: Achieving global food security while maintaining environmentally sustainable agricultural systems remains a critical challenge amid population growth, climate variability, and resource constraints. Artificial Intelligence (AI) and the Internet of Things (IoT) have emerged as transformative technologies that support data-driven agricultural practices. This study systematically examines the applications, opportunities, challenges, and adoption factors of AI-IoT integration in smart agriculture, with particular emphasis on its potential contributions to food security and sustainable farming. Methods: A systematic literature review (SLR) was conducted following the PRISMA 2020 guidelines. Publications were retrieved from Scopus, IEEE Xplore, and ScienceDirect covering the period 2020-2024. From an initial 431 records, 17 empirical studies met the inclusion criteria and were analysed using narrative and thematic synthesis. Result: The review shows that AI-IoT technologies are primarily applied in crop disease detection, precision agriculture, environmental monitoring, yield prediction, and livestock health monitoring. These technologies enable real-time decision support, early disease detection, productivity improvement, and resource optimisation. However, challenges remain, including data limitations, infrastructure constraints, integration complexity, and high deployment costs. Novelty: The study proposes a layered smart agriculture framework linking technological infrastructure, application domains, adoption conditions, operational outcomes, and sustainability impacts. The findings highlight key factors necessary for successful implementation, including infrastructure readiness, affordability, technological reliability, and capacity development for farmers. Crucially, the review demonstrates that the field of AI-IoT smart agriculture is technically advanced but socio-technically incomplete: the evidence base is dominated by proof-of-concept studies from Asia, with no empirical representation from Africa or the Americas, creating what this study terms an AI-IoT agricultural equity gap that fundamentally limits the technology’s contribution to global food security. The five-layered framework introduced here provides the first inductively derived organising structure that explicitly connects AI-IoT infrastructure to SDG-aligned food security outcomes, offering a replicable analytical scaffold for future empirical and policy research in this domain.
Where are the mistletoes? Large declines in mistletoes in a savanna ecosystem over 30 years
(Biological Conservation, 2026-05-29) Maponga, T.S.; Muvengwi, J.; Ndagurwa, H.G.T.; Thompson, D.I.; Twine, W.; Witkowski, E.T.
Large trees are vital hosts for aerial hemiparasites, and their decline likely drives declines in mistletoe abundance. In semi-arid savannas, mistletoes provide ecological and economic benefits, by enriching soil nutrients, enhancing understorey diversity, and supporting livelihoods through the sale of woodroses. However, their persistence is threatened by changes in disperser and pollinator behaviour, overharvesting, host tree loss, and climate change. We assessed ∼30 years of change (1994 to 2024) in woody plant density, mistletoe-infected trees, and two woodrose-forming mistletoe species ( Erianthemum dregei and Pedistylis galpinii ) across communal rangelands (CRs) and protected areas (PAs) in a lowveld savanna of South Africa. Over this period, woody plant densities increased by 61%, with CRs supporting 46% higher densities than PAs. In contrast, mistletoe-infected tree densities and richness declined by 33% and 40%, respectively. Although mistletoe-infected tree height, stem diameter, and canopy area did not differ between time periods, PAs had infected trees that were 19% to 38% taller with larger stem diameter and canopy areas than in CRs. Mistletoe density declined by 43%, with medium and large individuals decreasing by 30% and 86%, respectively, and P. galpinii declining by 79%. These declines appear linked to losses of large trees and megaherbivore herbivory in PAs, whereas increases in woody cover likely reflect the proliferation of disturbance-tolerant, coppicing species under sustained human and megaherbivore pressures. Nonetheless, CRs supported higher densities and a greater diversity of mistletoe-infected trees and mistletoes than PAs, emphasising the conservation value of customary management systems in sustaining vulnerable parasitic plant communities.
Evaluating surface water for genomic surveillance of community-linked antimicrobial resistance in ESBL-producing Klebsiella pneumoniae
(Environmental Advances, 2026-07-30) Ayukafangha, E.; Mbanga, J.; Ismail, A.; Essack, S.Y.; Abia, A.L.K.
ABSTRACT A major limitation in wastewater-based epidemiology is its application in communities without centralised sewage systems necessitating alternative approaches. We evaluated surface water as an alternate antimicrobial resistance (AMR) monitoring interface by comparing the resistome, virulome, and phylogeny of extended-spectrum β-lactamase-producing Klebsiella pneumoniae (ESBL-Kp) from surface water (SW), healthy residents (HR), and clinical (CL) settings. Ninety-six (SW=32, HR=32, CL=32) ESBL-Kp isolates collected over eight-months underwent comparative genomic analysis of antibiotic resistance genes (ARGs), virulence determinants, multilocus sequence types, and phylogenetic relatedness. Sixteen sequence types (STs) were identified across all sources. ST983 was shared by all sources, ST25 and ST219 were exclusive to SW-HR, and ST152 to SW-CL. More SW (93.8%) isolates shared STs with HR than with CL (9.4%). Phylogenomic analysis was lineage-driven rather than source-structured, with SW isolates forming stronger subclades with HR through ST25 and ST219. Resistome composition showed substantial overlap with differences ( p  = 0.003). The dominant β-lactamase ARG in all sources was bla CTX-M-15 , alongside non-β-lactam sul2 and dfrA14 . Pairwise exclusive ARGs totalled 20 (CL-HR), seven (SW-HR), and two (SW-CL); source-restricted ARGs totalled fourteen, nine, and none for CL, HR, and SW, respectively. SW-HR. Virulome overlap was driven by ST25/KL2 and ST219/KL114, a limited SW-CL link was observed through ST152/KL149, and source-restricted lineages were concentrated mainly in clinical and healthy resident isolates. SW shared major ESBL-Kp AMR features with both HR and CL, but distribution differed across sources. SW more closely resembled HR, supporting its use as a complementary tool rather than a standalone approach for AMR surveillance.
Artificial Intelligence in Zimbabwean media: ethical concerns, governance issues, and societal impact (2016-2025)
(Southern African Journal of Communication and Information Science, 2025) Dabengwa, I.; Chigamani, P.; Maturure, R.
Artificial Intelligence (AI) has gained attention in Zimbabwean media, with reports highlighting its applications in healthcare, education, parliament, marketing, and agriculture. This study explores how Zimbabwean media reports AI adoption and usage, focusing on socioeconomic impacts, ethical concerns, and regulatory issues. An analysis of 575 news stories using media classification methods, sensitising codes, and grounded theory revealed key themes through Leximancer and RStudio Bibliometrix. The findings show increased AI coverage from to 2023-2024, coinciding with generative AI tools and governance concerns. The media presents utopian views emphasising AI benefits while giving less attention to dystopian concerns such as privacy, bias, and neo-colonialism. The Zimbabwean media emphasises data sovereignty and Ubuntu philosophies in AI development. Dystopian perspectives highlight privacy, bias, access, ethical decision-making, job loss, and neocolonialism issues. The media suggest stakeholder collaboration to address insufficient funding, skills, infrastructure, and connectivity challenges through network expansion, re-skilling, expert consultation, and developing comprehensive AI frameworks aligned with regional policies. This study demonstrates the media's role in raising awareness of AI's benefits and risks of AI and influencing public perception and policy development. Recommendations include an increased coverage of ethical issues and infrastructure upgrades to promote societal readiness. Developing a clear AI framework is essential to govern the adoption of ethical AI in Zimbabwe. This study offers insights to policymakers and researchers in low-resource settings. Future research should explore public AI perception using web scrapping and sentiment analysis, track international AI commitments, and investigate sectoral AI implementations. Amplifying diverse voices and enhancing journalists' training in AI reporting are essential for a balanced, in-depth coverage of ethical and governance issues as AI continues to evolve.
Microfinance and SMEs in Chegutu, Zimbabwe: Borrower experiences and perceived livelihood effects in Zimbabwe
(International Journal of Development and Sustainability, 2026-01-27) Dube, L. Z.; Ncube, M.; Sibanda, M. B.; Moyo, F.; Mashanda, P.
The study explored the contribution of the microfinance sector in poverty reduction among SMEs in Chegutu. Chegutu, like other urban centres in Zimbabwe, has witnessed increases in poverty, despite the growing presence of MFIs. The study employed an exploratory, qualitative-dominant mixed-methods design to capture borrower experiences and perceived livelihood effects, combining semi-structured questionnaires with KIIs; quantitative summaries are reported descriptively only. CA and HDA underpinned the study. Data collection was through fifty (50) semi-structured questionnaires and five KIIs. The sampling frame comprised 1,889 SMEs in Chegutu. The study targeted SME borrowers listed in MFI registers using systematic sampling. Dividing the population by the intended systematic sample produced every sixth SME (k = 6), yielding fifty-five (55) eligible SMEs; fifty (50) participated after refusals/non-response. Five KIIs were conducted with MFI loan officers from five different MFIs. The study unveiled mixed experiences: some SMEs reported positive livelihood stabilisation effects, whereas others reported limited gains and repayment pressure. Participants and loan officers pointed to the need for a more enabling policy environment for SME viability and responsible microfinance delivery.