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Vermicomposting of camel (Camelus dromedarius) manure with fly ash and microbial inoculants : effects on nutrients and heavy metals
Mupambwa, Hupenyu A.; Ruben, Elia N.M.; Haneklaus, Nils H.; Handura, Bethold; Howoses, Veronica A.; Brahim, Jamal Ait; Beniazza, Redouane; Roubik, Hynek; Truter, Wayne F.; Van der Merwe, Elizabet Margaretha; Brink, Hendrik Gideon (MDPI, 2026-03)
Please read abstract in the article.
An emulated dynamic framework for evaluating metaheuristic-based load balancing techniques in edge computing networks
Molokomme, Daisy Nkele; Onumanyi, Adeiza James; Abu-Mahfouz, Adnan Mohammed (MDPI, 2026-03)
Edge computing (EC) has emerged as a paradigm to support computation-intensive Internet of Things (IoT) applications by enabling task offloading to nearby servers. Despite its potential, the inherent heterogeneity of edge resources and the dynamic, unpredictable nature of task arrivals present significant challenges for designing and evaluating effective load balancing strategies. Traditional evaluation methods are limited as follows: physical testbeds lack scalability and flexibility, while abstract simulators often oversimplify network behavior, failing to capture realistic system dynamics. To address these limitations, we present an emulated dynamic edge computing framework (EDECF) designed for evaluating load balancing schemes in EC networks. First, we developed dedicated service models for each EC node within the EDECF and implemented them using the common open research emulator (CORE) platform, thereby providing a scalable, flexible, and realistic environment for testing optimization strategies. Second, we introduced a robust fitness function that explicitly models latency, queue stability, and fairness for metaheuristic-based load balancing under dynamic edge conditions. To assess its effectiveness, this function was incorporated and tested using the following methods: the particle swarm optimization, genetic algorithm, differential evolution and simulated annealing-based load balancing algorithms. In addition, baseline methods such as the round robin and shortest queue techniques were also deployed to demonstrate the framework’s capacity to facilitate rigorous analysis in heterogeneous and time-varying scenarios. Overall, results are presented to demonstrate EDECF’s capability to emulate realistic workloads, capture resource variability at the edge, and support comprehensive evaluation of algorithmic performance across diverse network settings. Thus, this work aims to establish a practical and extensible foundation for researchers and practitioners to design, test, and optimize load balancing strategies in EC environments.
Kinship and network analysis of two South African beef cattle breeds using pedigree and high-density SNP markers
Khanyile, Khulekani S.; Maiwashe, Azwihangwisi; Magagula, Nozipho A.; Van Marle-Koster, Este; Zwane, Avhashoni A. (MDPI, 2026-03-19)
Accurate genealogical records are essential in livestock breeding for maintaining genetic diversity, preventing inbreeding, and mapping of economically important traits in beef production. This study aimed to assess parent–offspring relationships within South African Bonsmara and Nguni cattle populations using both traditional pedigree records and genomic data. Hair samples from 119 Nguni and 311 Bonsmara cattle were genotyped using the BovineSNP50 array, and these were imputed to Illumina BovineHD BeadChip using updated SNP coordinates from the assembly genome (ARC—UCSD 1.2). Quality control and data filtering were performed using PLINK v1.9, while relationship inference was conducted using KING v2.2.8 and PLINK v1.9 software for principal component analysis, IBD metrics and Mendelian error-based exclusion. Categories of relatedness through network relationship analysis revealed a predominance of half-sibling relationships in both breeds, with 2317 such relationships identified in Nguni and 1221 in Bonsmara. Inference of parent–offspring pairs showed discrepancies with the recorded pedigrees, with 49 inferred pairs compared to 47 recorded pairs in Nguni, and 62 inferred pairs compared to 75 pairs recorded in Bonsmara. Relationships based on IBD using PLINK with a ‘PI-HAT’ threshold greater than 0.45 revealed unique parent–offspring inferences that differed from those obtained using KING v2.2.8. Phylogenetic network analysis assigned each individual’s genomic origin independent of the pedigree records, supporting the efficiency of SNP data for genetic assignment. These results demonstrated that SNP-based pedigree verification can accurately identify parent–offspring and half-sibling relationships, providing a reliable foundation for recombination analysis and supporting precise trait mapping and informed selection in breeding programs.
Determinants of market choices among beef cattle farmers in uMgungundlovu District of Kwa-Zulu Natal, South Africa
Mkhize, Rachel S.; Mokolopi, Gloria; Chipfupa, Unity; Loki, Olwethu (MDPI, 2026-02-11)
Globally, the demand for beef and beef-related products has significantly escalated over the past decade. This study aimed to evaluate the factors influencing the market participation of smallholder beef cattle farmers in uMgungundlovu, South Africa. The study employed a cross-sectional research design, which followed a mixed-methods approach to collect data. Survey data were collected from smallholder cattle farmers from the uMgungundlovu District in KwaZulu-Natal using a semi-structured questionnaire. Purposive sampling was employed to select four local municipalities from the uMgungundlovu District out of a total of seven, whereas a simple random sampling was used to recruit farmers. The sampling was conducted using Microsoft Excel, whereby each farmer was allocated a random number, and then the required sample was generated from those numbers. To determine factors that influence farmers’ market choice, a multinomial logit regression model was used. A significant proportion of the farmers (43.1%) were aged between 51 and 70, followed by 35.5% aged 31 to 50. Just under half (48.2%) of farmers had received formal training in livestock production. This finding (p < 0.001) reinforces the central role of education in income determination. Better-educated individuals tend to earn more and diversify their income sources. This study underpinned that the livestock farming population is dominated by primarily middle-aged, male, semi-educated, and resource-poor individuals, and they rely significantly on traditional farming methods and government assistance. The multinomial logit regression revealed that farmers’ market choices are influenced by education level, extension service quality, access to quality bulls, and breeding knowledge significantly influenced farmers’ market choices. Specifically, secondary and tertiary education reduced the likelihood of participating in auction markets relative to informal markets, while limited breeding knowledge and poor extension services further constrained participation in formal channels.
Deconstructing the complexity of measuring food security in South Africa : a systematic review and meta-analysis (2000-2024)
Masamha, Blessing; Gwanzura, Owen; Mutanga, Shingirirai S. (BioMed Central, 2026-03)
BACKGROUND : Measuring the non-observable nature of food security has remained complex mainly because of the construct’s complexity and its continuously evolving nature. The main challenges in measuring food security involve determining what is to be measured and how it is measured. In South Africa, various approaches and indicators have led to divergent food security measurement outcomes, leading to inaccurate assessment, monitoring, and targeting of context-specific food security interventions. This study analyses food access, availability, and stability measurement metrics and proposes a clear food security measurement approach for South Africa. Comprehensive reviews of food security indices with a national scope and subsequent meta-analysis to determine these indicators’ effect size, publication bias, and heterogeneity have not been adequately explored. METHODS : A systematic review and meta-analysis using the PRISMA guidelines were used to select the analysed articles. A search strategy was used to retrieve literature from the Web of Science and Scopus Databases, yielding a total of 1155 articles. Rayyan 1.6 software was used for screening articles and duplicate removal, whilst the Newcastle-Ottawa scale was used to qualitatively assess the articles. Perplexity and Quill Bot Artificial Intelligence (AI) tools were used to enhance literature search and paraphrasing, respectively, to improve the validity and reliability of the review. The inclusion and exclusion criteria resulted in a final sample of 82 articles being eligible for analysis. RESULTS : Most studies used Household Food Insecurity Access Score (HFIAS), (n = 45), Household Dietary Diversity Score (HDDS) (n = 24), Coping Strategy Index (CSI), (n = 13), and the Household Hunger Score (HHS) (n = 4). Few studies used a composite of indicators, while most studies used HFIAS alone. The indicators used provide very different estimates of the prevalence of food insecurity in South Africa. Limpopo and KwaZulu-Natal provinces had the most studies distributed across rural communities, while Cape Town City and Gauteng Province had the highest number of urban studies. Meta-analysis was done on HFIAS (n = 16) and HDDS (n = 14) indicators using a Forest plot and Funnel plot, and results showed limited heterogeneity and publication bias across the studies. CONCLUSIONS : More food security studies need to use longitudinal designs, composite indicators across different seasons, and along the urban, peri-urban, and rural settlement gradient, and panel data from national surveys. The routine national surveys need to adopt the full modules of indicators to allow for household and individual food security analysis in South Africa. We recommend the Agency Module, the Women Empowerment in Agriculture Index (WEAI), and the Women Empowerment in Livestock Index (WELI) to measure the sustainability and agency dimensions of food security.