<?xml version="1.0" encoding="UTF-8"?>
<feed xmlns="http://www.w3.org/2005/Atom" xmlns:dc="http://purl.org/dc/elements/1.1/">
<title>College of Agriculture and Environmental Sciences</title>
<link href="https://ir.unisa.ac.za/handle/10500/130" rel="alternate"/>
<subtitle/>
<id>https://ir.unisa.ac.za/handle/10500/130</id>
<updated>2026-05-05T18:22:29Z</updated>
<dc:date>2026-05-05T18:22:29Z</dc:date>
<entry>
<title>Prevalence, characterization and antimicrobial susceptibility patterns of extraintestinal pathogenic Escherichia coli from chicken carcasses in Gauteng Province, South Africa</title>
<link href="https://ir.unisa.ac.za/handle/10500/32402" rel="alternate"/>
<author>
<name>Motau, Mmatau Carol</name>
</author>
<id>https://ir.unisa.ac.za/handle/10500/32402</id>
<updated>2026-04-29T11:54:35Z</updated>
<published>2025-11-01T00:00:00Z</published>
<summary type="text">Prevalence, characterization and antimicrobial susceptibility patterns of extraintestinal pathogenic Escherichia coli from chicken carcasses in Gauteng Province, South Africa
Motau, Mmatau Carol
Extraintestinal pathogenic Escherichia coli (ExPEC) strains are adaptable bacteria often associated with urinary tract, kidney, bloodstream and other extraintestinal infections. Extraintestinal pathogenic Escherichia coli infections pose a global public health threat due to their economic impact and management challenges, with poultry meat and other meat products implicated in the spread of the disease. However, in South Africa, there is scarcity of published data on the contamination level and role that poultry meat plays in transmitting ExPEC. The purpose of the study was to determine the prevalence, genetic characteristics and antimicrobial susceptibility profile of ExPEC from chicken carcasses sampled from the Gauteng Province. The study utilized a stratified proportional sampling method to analyse 404 chicken carcasses collected from four abattoirs across five municipalities in Gauteng Province. An additional 63 historically persevered freeze-dried isolates from poultry were included to strengthen this study. Most Probable Number method was used for detection of Escherichia coli. Antimicrobial susceptibility testing was conducted using the minimum inhibition concentration method against 12 antibiotics. Selected classes of antibiotics include cephalosporin, macrolide, phenicol, tetracycline, penicillin, fluoroquinolone, aminoglycoside, and sulphonamide. This selection is motivated by the necessity to comprehend, monitor, and address the emergence of resistance in a common Gram-negative bacteria including ExPEC. Conventional polymerase chain reaction was used to confirm ExPEC presence, alongside gene characterization through virulence genotyping, phylogenetic grouping, phenotypic resistance, and pathotyping. The overall prevalence of E. coli was 93% with 4% confirmed as ExPEC. The ExPEC isolates predominantly carried multiple virulence genes: ompA (100%), mat (83%), kpsm (65%), both csg and sitA with (57%), sat and traT (52%) virulent genes. The highest antibiotic-resistant rates were observed in tetracycline-32-4mg/L (57%), ciprofloxacin- 32-4mg/L (43%), and gentamicin-16-0.25mg/L (39%). However, ceftriaxone, ceftiofur, and cefoxitin (9%) exhibited the lowest antibiotic resistance. The genes associated with the highest phenotypic resistance were sul3 (43%) and tetA (39%). The phylogenetic groups indicated that majority of the ExPEC isolates belonged to group A (39%), group B2 (35%) lastly both groups B1 and D (13%). Class 3 integron was detected in 74% isolates followed by Class 1 integron (35%) and Class 2 (9%). The NMEC pathotype was rare among these isolates, while 13% and 26% distribution were observed in APEC, UPEC, and SEPEC pathotypes. In conclusion, it is evident that while ExPEC occurrence is rare, E. coli is consistently isolated from chicken meat. Despite its low frequency, ExPEC demonstrated a high prevalence of Class 3 integron and virulence-encoding genes that are crucial for colonization and survival. These factors contribute to the spread of resistance genes and emergence of multidrug resistance. Future research should utilize whole genome sequencing for comprehensive molecular characterization, focusing on plasmids and serotyping to differentiate strains from formal and informal abattoirs, which may reveal sources of contamination.
</summary>
<dc:date>2025-11-01T00:00:00Z</dc:date>
</entry>
<entry>
<title>Beach and dune erosion along the coast of Richards Bay, South Africa and implications for the management of shoreline change</title>
<link href="https://ir.unisa.ac.za/handle/10500/32369" rel="alternate"/>
<author>
<name>Alakram, Suvana</name>
</author>
<id>https://ir.unisa.ac.za/handle/10500/32369</id>
<updated>2026-04-16T11:54:43Z</updated>
<published>2026-01-26T00:00:00Z</published>
<summary type="text">Beach and dune erosion along the coast of Richards Bay, South Africa and implications for the management of shoreline change
Alakram, Suvana
Sandy beaches are dynamic in nature and are subject to natural and anthropogenic processes that influence its evolution. One of the key drivers of coastal evolution is the erosion of the coastline. Sandy beaches are more susceptible to erosion because its fine sand is easily erodible. Since approximately 80% of South Africa’s coastline consists of sandy beaches, including environmentally sensitive dune systems, the impetus is to improve our knowledge and understanding of processes taking place at the coastal zone to aid in coastal zone management and planning for future hazards. This research integrated the use of geographical information systems (GIS), remote sensing, and modelling techniques to contribute knowledge on the interrelationships between the spatial and temporal dynamics of shoreline changes along the coast of Richards Bay, South Africa. Shoreline change rates were quantified over a 45 year period between 1977 and 2022 using the United States Geological Survey’s Digital Shoreline Analysis System. The historical data was then used to estimate future shoreline positions 10 and 20 years into the future. The results of the shoreline analysis revealed consistent erosion north of the Richards Bay harbour with a net shoreline movement of 167.80 m in some areas. The beaches south of the harbour recorded an accretional trend with a net shoreline movement of 98.90 m in some areas. The study verified that the development of the port breakwaters has caused an interruption the longshore sediment transport pattern, resulting in accretion on the updrift side (South), and erosion on the downdrift (North). The shoreline change rate statistics were used to predict future shoreline positions using the Extrapolated Linear Regression method 10 and 20 years into the future. In the context of climate change and associated sea level rise, model based approaches in ArcGIS Pro were used to assess the vulnerability of the study area to inundations caused by storm surges. The inundation screening was initated for four different surge levels using a high resolution DEM as input. The results indicated that during a 9 and 10 m storm surge, 60 and 68% of the study area respectively was inundated which serves as important baseline information for disaster risk assessments. This dissertation also explored possible pathways to coastal resilience and proposed strategies to mitigate coastal erosion and flooding in a changing environment.; Strande is dinamies en onderhewig aan natuurlike en antropogeniese prosesse wat die evolusie daarvan beïnvloed. Een van die belangrikste dryfkragte van kusevolusie is erosie van die kuslyn. Strande is meer vatbaar vir erosie omdat fyn sand maklik erodeerbaar is. Ongeveer 80% van Suid-Afrika se kuslyn bestaan uit hoofsaaklik sand dominante strande wat omgewings belangrikke duinstelsels behels. Dus is die doel van hierdie projek om ons kennis en begrip van kussoonprosesse te verbeter asook om te help met kussonebestuur en beplanning vir toekomstige gevare. Hierdie navorsing maak gebruik van ‘n metode wat geografiese inligtingstelsels (GIS), afstandswaarneming en modelleringstegnieke behels. Met die doel om die onderliggende verband tussen die ruimtelike en temporale dinamika van kuslynveranderinge langs die kus van Richardsbaai, Suid-Afrika, beter te verstaan. Die kuslynveranderingstempo's is oor 'n tydperk van 45 jaar, tussen 1977 en 2022, gekwantifiseer met behulp van die Verenigde State se Geologiese Opname se Digitale Kuslynanalisestelsel (DSAS). Hierdie historiese data was gebruik om die toekomstige kuslynposisies te skat oor 10 en 20 jaar. In sommige gebiede het die studie erosie noord van die Richardsbaai-hawe uitgewys met 'n totale kuslynbeweging van 167.80 m. Strande suid van die hawe het 'n akkresionele tendens vertoon met 'n netto kuslynbeweging van 98.90 m in sommige gebiede. Met klimaatverandering en stygende seevlaktes ingedagte, was ArcGIS Pro gebruik om die kwesbaarheid van die studiegebied vir stormvloede te modeleer en assesseer. Vier verskillende stormvloed scenarios was getoets met behulp van hoë resolusie DEMs. Die resultate wys dat 60 of 68 persent van die studiegebied sal vloed met ‘n 9 of 10 m stormvloed scenario en dien as ‘n belangrikke basislyn for toekomstige ramp en risikoassesering. Verder, ondersoek hierdie navorsing opsies om kusveerkragtigheid te verbeter en stel strategië voor om die impak van kuserosie en vloede te versag in ‘n area wat klimaatverandering ondervind.
Abstracts in English and Afrikaans
</summary>
<dc:date>2026-01-26T00:00:00Z</dc:date>
</entry>
<entry>
<title>Assessing the impacts of Eyethu coal mining activities on the surrounding communities: A case study of Vosman township, Emalahleni Municipality in Mpumalanga Province.</title>
<link href="https://ir.unisa.ac.za/handle/10500/32322" rel="alternate"/>
<author>
<name>Mugagadeli, Phathutshedzo</name>
</author>
<id>https://ir.unisa.ac.za/handle/10500/32322</id>
<updated>2026-05-01T06:59:47Z</updated>
<published>2025-11-01T00:00:00Z</published>
<summary type="text">Assessing the impacts of Eyethu coal mining activities on the surrounding communities: A case study of Vosman township, Emalahleni Municipality in Mpumalanga Province.
Mugagadeli, Phathutshedzo
Mining is economically important. However, the sector often ignores the environmental impacts of mining activites. These impacts can seriously harm the health of local communities and damage water sources and agricultural products. The aim of this study was to investigate the impacts of Eyethu coal mining on the community of Vosman in Emalahleni, in the Mpumalanga Province, South Africa. A mixed research approach was employed, where the use of Remote Sensing to detect land-use and land-cover changes over the years was complemented by a survey (197 respondents) to assess the health impacts of the mine, while water quality assessment and risk assessment were also used to assess the impacts on the nearby river. The key findings suggested that Eyethu coal mining has contributed to the environmental degradation of the study and surrounding area, particularly the destruction of natural vegetation. Inhabitants also reported ground instability (65.9%), health impairment (55.9%, mainly respiratory illnesses), altered air (54.4%) and water quality contamination (55.9%), and this notwithstanding the fact that the people still use the river for domestic and agricultural purposes. These perceptions coincided with objective scientific evaluations of the water quality, which also concluded that the upper river section was highly acidic (pH 3.26), with considerable levels of arsenic (0.024 μg/L) and mercury (0.006 μg/L While formal inferential statistical tests were not conducted, comparative analysis of environmental indicators between the baseline period (T1) and the most recent period (T2) demonstrates a clear increase in land-use disturbance, vegetation loss, and water-quality alteration over time. All heavy metals that were measured were within the threshold of the SANS 241 standards; however, the acidic environment promotes metal solubility and poses a long-term threat to the ecosystem and human health. The Chronic Daily Intake (CDI), Hazard Quotient (HQ) and Hazard Index (HI) were all revealed to be lower than 1, which indicates a low chance of causing non-carcinogenic diseases. In conclusion, the study showed negative impacts attributed by the mine. From changes in land use and land cover, to impacts on human health as well as changes in water quality. Although water quality indices revealed that the impacts of the mine on water quality are not yet severe for assessed heavy metals, this might not be the case with other heavy metals. The study recommends a strong enforcement of environmental regulations, monitoring and rehabilitation, and community engagement in the mining decisions. Moreover, more risk assessments of other heavy metals are encouraged to generalise the quality of the nearby river.; Ngaphandle kokumelana nokubaluleka kwezomnotho wezimayini, lomkhakha uvamise ukukubukela phansi ukuhlolwa komthelela wawo kwezemvelo. Izinhlekelele ezinkulu kwezemvelo zidala ubungozi kwizempilo emiphakathini yasemazweni asafufusa, futhi kuphazamisa izitshalo kanye nemithombo yamanzi ngenxa yemisebenzi yokumba ezimayini. Inhlosonqangi yalesisifundo ukubheka umthelela emphakathini waseVosman eMalahleni, esifundazweni saseMpumalanga, eNinizimu Afrika, umthelela odalwa inkampani emba amalahle i-Eyethu. Indlela yokwenza ucwaningo oluhlanganisile yasetshetshenziswa, lapho kwakusetshenziswa I -remote sensing ukubheka ukusetshenziswa komhlaba,kanye nokuguquguquka komhlaba eminyakeni, (lolucwaningo lwenziwe kubantu abangama-197) ukubheka umthelela yezimayini, khathi kubhekwa futhi isimo samanzi kanye nobungozi emfuleni eseduzane. Imiphumela ebalulekile yaveza ukuthi inkampani yemayini i-Eyethu ibe nomthelela omkhulu ekucekelekeni phansi kwemvelo kulendowo okade kwenziwa kuyo ucwaningo kanye nasezindaweni eziyakhele, ikakhulukazi ukuphazamiseka kwezimila zemvelo. Izakhamizi/ Abahlali baphinda baveza ukungaqini kahle komhlabathi (amaphesenti angama-65.9), okukhubazeka kwezempilo (amaphesenti angama-55.9, ikakhulukazi inkinga yokuphefumula) umoya abawuphefumulayo ongekho ezingeni ngenxa yokungcoliseka (amaphesenti angama-55.4) kanye nokuphazamiseka kwezinga lamanzi ngenxa yokungcoliseka (amaphesenti angama -55.9), ngaphezu kwakho konke lokhu abantu basebenzisa wona umfula ukuthola amanzi okusetshenziswa emakhaya kanye nokuchelela izitshalo. Ngaphandle nje kokuqonda ukuqondana kwezinhloso zokubheka izinga lamanzi ngokwesayensi, okwathola ukuthi amanzi enhla nomfula anesimuncwane(i-acid) eningana (Ph3.26), kanye ne arsenic(ubuthi), obuwu (0.024ug/L) kanye ne-mercury ewu(0.006ug/L), lokkhu kuyinkoba yokuthi indawo la ukungcoliseka kwenzeka khona. Zonke izinsimbi ezisindayo zakalwa kwatholakala ukuthi ziphakathi kombundu ongama-241 SANS, ngokwamazinga, nomakunjalo, imvelo/umhlaba one -acidi kudala ukuncibikala kwensimbi futhi kudala ukuphazamiseka kwimvelo kanye nezimpilo zabantu ekuhambeni kwesikhathi. I- Chronic Daily Intake (CDI), Hazard Quotient (HQ) kanye ne Hazard Index (HI) kwavela ukuthi kungaphansi kuka1, okukhombisa amathuba amancane okuphathwa izifo ezidala umdlavuza. Esiphethweni, lolucwaningo/ lesisifundo sikhombisa umthelela ongemuhle odalwa izimayini, kusukela ekuguqukeni kokusetshenziswa komhlaba kuya ekuphendukeni kwawo, umthelela ezimpilweni zabantu, kanye nokushintsha kwezinga lamanzi. Noma inkomba ivezaukuthi umthelela wezimayini ezingeni lamanzi kawukho mubi kangako ngokocwaningo lwensimbi , lokhu kungenzeka kungafani uma ubheka olunye uhlobo lwensimbi. Lesisifundo siphakamisa kakhulu ukulandelwa kwemithetho elawula ezemvelo, ukuqapha kanye, nokuvuselela kanye,nokuxhumana nemiphakathi kwizinqumo zezimayini. Ngaphezu kwalokho,kugqugquzelwa ukuvamisa ukuhlola ubungozi bezinye izinsimbi ezisindayo emfuleni oseduzane.; Hu sa londwi ndeme ya ikonomi ya migodi, kanzhi sekithara iyi i dzhiela fhasi ṱhoḓisiso ya masiandoitwa ayo kha mupo. Masiandoitwa a mupo a vhaisaho vhukuma na a khombo ane a vhea khomboni mutakalo wa zwitshavha zwapo kha mashango a khou bvelelaho na ane a vhea khomboni zwibveledzwa zwavho zwa vhulimi na zwiko zwa maḓi zwi kolodwa mishumo ya migodi. Ndivho ya ngudo iyi yo vha i ya u sedzulusa masiandoitwa a migodi ya malasha ya Eyethu kha tshitshavha tsha Vosman ngei Emalahleni, kha vunḓu ḽa Mpumalanga, Afrika Tshipembe. Nḓila ya ṱhoḓisiso yo ṱhanganelano yo shumiswaho, hune u shumiswa ha u pfa zwi re kule u itela u vhona tshanduko dza u shumiswa ha mavu na u fukedzwa ha mavu kha miṅwaha zwo ḓadziswa nga tsedzuluso (vhafhinduli vha 197) u itela u ṱola masiandoitwa a mutakalo wa mugodini, ngeno tsedzuluso ya vhuimo ha maḓi na tsedzuluso ya khombo zwo dovha zwa shumiswa u sedzulusa masiandoitwa kha u gonya ha maḓi. Mawanwa a ndeme o sumbedza uri migodi ya malasha ya Eyethu yo shela mulenzhe vhukuma kha u tshinyadza mupo wa ngudo na fhethu ho ṱanganaho na hone, nga maanḓa u tshinyadzwa ha zwimela zwa mvelo. Vhadzulapo vho dovha vha vhiga u sa dzika ha mavu (65.9%), u sa dzika ha mutakalo (55.9%, zwihulusa malwadze a u fema), u shandukiswa ha vhuḓi ha muya (54.4%) na u tshikafhadzwa ha vhuḓi ha maḓi (55.9%), hu sa londwi uri vhathu vha kha ḓi shumisa mulambo kha ndivho dza hayani na dza vhulimi. Hezwi zwine zwa dzhiiwa zwo ṱangana na ṱhoḓisiso dza saintsi dzine dza vha na tshipikwa dza vhuḓi ha maḓi, zwe zwa dovha zwa fhedziswa nga ḽa uri tshipiḓa tsha mulambo wa nṱha tsho vha tshi na dungi nnzhi (pH 3.26), na zwikalo zwihulwane zwa aseniki (0.024 μg/L) na mekhuuri (0.006 μg/L), na uri zwi vhidzwa tshikafhadzo ya u fhisa i khalini. Tsimbi dzoṱhe dzi lemelaho dze dza kaliwa dzo vha dzi nga ngomu ha tshikalo tsha zwilinganyo zwa SANS 241; fhedzi fhethu hune ha vha na dungi zwi ṱuṱuwedza u ṱangana ha tsimbi nahone zwi vhea khombo ya tshifhinga tshilapfu kha fhethu hune zwimela, zwipuka na zwiṅwe zwivhumbiwa, khathihi na mutsho na mbonalo ya shango, zwa shumisana u itela u vhumba mapulo a vhutshilo na mutakalo wa vhathu. Chronic Daily Intake (CDI), Hazard Quotient (HQ) and Hazard Index (HI) zwoṱhe zwo dzumbululwa zwi fhasi ha 1, zwine zwa sumbedza khombo ya fhasi ya u vhanga malwadze a sa ḓivhei uri a nga vhanga pfuko.&#13;
&#13;
Musi hu tshi pendelwa, ngudo yo sumbedza masiandoitwa mavhi o ṱanganedzwaho nga mugodini, u bva kha tshanduko kha tshumiso ya mavu na u fukedzwa ha mavu, u ya kha masiandoitwa kha mutakalo wa vhathu, khathihi na tshanduko kha vhuimo ha maḓi. Naho vhuimo ha maḓi nga nomboro ṱhukhu ine ya papamala ine ya bvisela khagala uri masiandoitwa a mugodini kha vhuḓi ha maḓi ha athu vha mahulwane kha tsimbi dzi lemelaho dzo senguluswaho, hezwi zwi nga kha ḓi sa vha zwone kha dziṅwe tsimbi dzi lemelaho. Ngudo i themendela u kombetshedzwa ho khwaṱhaho ha milayo ya mupo, u ṱola na u vusuludza, na u dzhenelela ha tshitshavha kha tsheo dza migodi. Zwiṅwe hafhu, u ṱola khombo nnzhi dza dziṅwe tsimbi dzi lemelaho hu u ṱuṱuwedzwa u itela u angaredza vhuimo ha mulambo wa tsini.
Text in English with summaries in Zulu and Venda
</summary>
<dc:date>2025-11-01T00:00:00Z</dc:date>
</entry>
<entry>
<title>Selected soil trace metals in KZN, Cedara : their concentration, adsorption, extraction methods and threats to food security</title>
<link href="https://ir.unisa.ac.za/handle/10500/32317" rel="alternate"/>
<author>
<name>Zuma, Vincent Thulani</name>
</author>
<id>https://ir.unisa.ac.za/handle/10500/32317</id>
<updated>2026-03-20T11:26:51Z</updated>
<published>2025-11-01T00:00:00Z</published>
<summary type="text">Selected soil trace metals in KZN, Cedara : their concentration, adsorption, extraction methods and threats to food security
Zuma, Vincent Thulani
This study investigated the concentrations of cadmium (Cd), copper (Cu), chromium (Cr), cobalt (Co), zinc (Zn), manganese (Mn), nickel (Ni) and lead (Pb) in soils from Cedara Research Farm in KwaZulu-Natal, South Africa. Soil samples were collected using a beta soil auger from areas representing different land uses and analysed for total and bioavailable metal concentrations. Total metals were determined through complete acid digestion, while bioavailable fractions were assessed using the Ambic-2 extraction method. Metal concentrations were quantified using inductively coupled plasma–atomic emission spectroscopy (ICP-AES) and atomic absorption spectroscopy (AAS).&#13;
The mean concentrations of metals followed the order Mn &gt; Pb &gt; Zn &gt; Cr &gt; Ni &gt; Cu &gt; Co &gt; Cd, with values of 245.57, 206.94, 127.19, 98.76, 23.80, 21.83, 2.16 and 0.97 mg·kg−1, respectively. The concentrations of Cr, Cu, Pb and Zn exceeded the allowed limits for agricultural soils, while Co was undetectable at all sites. Cadmium was detected in only three fields and Ni remained within acceptable limits across all sites. Manganese levels were consistently higher than those at the control site. The pollution indices (Igeo, EF and CF) indicated significant contamination by Cu, Zn and Mn, particularly in non-agricultural fields. However, the cropping areas exhibited comparatively lower concentrations, suggesting the mobilisation and partial removal of metals through agricultural activity. Comparison with background values from the 1970s confirmed ongoing soil contamination.&#13;
Between the two extraction methods tested, Ambic-2 extracted higher and more consistent metal concentrations than ammonium-EDTA. Elevated levels of heavy metals in these agricultural soils pose potential risks to food safety and human health. Routine monitoring and inclusion of heavy metal analyses in standard soil fertility assessments are recommended to improve soil management and mitigate heavy metal pollution.
</summary>
<dc:date>2025-11-01T00:00:00Z</dc:date>
</entry>
</feed>
