The need to understand which factors most strongly affect performance in first-year mathematics programs at Khon Kaen University (KKU), in North Eastern Thailand, provided the main focus of the study which is described. First-year mathematics students in the 1990-1991 academic year, from four KKU faculty groups (Medicine and Nursing, Agriculture, Science and Education, and Engineering) were involved in this study. Research literatures addressing variables which were likely to influence performance in early tertiary mathematical study, and variables associated with difficulties in learning mathematics at the transition from upper secondary school to tertiary studies, were reviewed. The first major aim of the study was to identify the variables which were good predictors of first-year mathematics performance at KKU. Results from stepwise multiple regression analyses indicated that the following predictor variables were statistically significant and entered the regression equations for most Faculty groups: School Mathematics Achievement, Self-Esteem, Study Habits in Mathematics, and Faculty of Study. Other predictor variables that sometimes entered regression equations (depending on the Faculty group) were Socio-Economic-Status, Mathematics Language Competence, Mathematics Confidence, Attitude Towards Mathematics, and Gender. Depending on Faculty group, the statistically significant variables accounted for between 11% and 74% of scores on fist-year KKU mathematics examinations. The predictor variables contributed much more to the variance of scores on first-semester mathematics examinations than to the variance of scores on second-semester mathematics examinations. It was also found that scores on the Direct Entry Examination Mathematics test (administered by KKU) and the School Mathematics Achievement test (developed and administered by the author) had stronger correlations with first-year KKU mathematics performance than did scores on the National Entry Examination Mathematics tests (administered by the Thai Ministry of University Affairs). Scores on the three pre-university mathematics achievement test instruments were better predictors of first-semester mathematics performance than of second-semester mathematics performance. It was found that the mean Mathematics Confidence of male students was statistically significantly higher than that of female students, but there were no statistically significant gender differences in Mathematics Misplaced Confidence. Only about 30% of the main sample ( 30% of the male and 30% of the female sample groups) had appropriate confidence in mathematics, that is, they thought their answers were correct when they were, in fact, correct, and they thought they were wrong when they were, in fact, incorrect. So far as Faculty performance differences were concerned, Engineering students had the highest Mathematics Confidence scores, followed by the Medicine and Nursing group of students and the Science and Education group students. Agriculture students had the lowest mean Mathematics Confidence score. No statistically significant differences occurred in Mathematics Misplaced Confidence between different Faculty groups. The second main aim of the study was to investigate why many first-year students experienced difficulties in coping with their mathematics units. A small group of senior secondary mathematics teachers, university mathematics lecturers, and first-year mathematics students were interviewed during the first semester of the 1990-1991 academic year. Interviews were conducted by the author according to a questionnaire format, and were aimed at identifying factors causing difficulty in the transition from senior secondary to university mathematical study. The analysis of the quantitative data together with the interview data indicated that the major sources of difficulty were associated with: (a) students' mathematical abilities; (b) curriculum content; (c) course organisation; (d) students' study habits; (e) instructional styles; and (f) assessment procedures. The results of the investigation are discussed in the light of the relevant literature and related research. The study concludes with recommendations which are addressed to mathematics teachers and education administrators in senior secondary schools in Thailand, to the Thai Ministry of Education, and to the KKU Department of Mathematics.

Summaries in English, Xitsonga and Afrikaans / Reading literacy for many black South African learners is a problem. In order to understand what happens in the South African foundation phase classrooms that affect learners’ reading performance, this study uses the adapted early grade reading assessment (EGRA) tool to assess Grade 1 learners’ reading abilities in the home language (four schools) and in the first additional language (one school). The EGRA is important for measuring foundational literacy skills. Its outcomes help teachers plan instruction that accommodates diverse learning capabilities. Data were collected through observing literacy practices and activities in the Grade 1 classrooms, evaluate classroom settings and interview Grade 1 teachers and curriculum advisors of the general education and training band to understand their perception of Curriculum and Assessment Policy Statement (CAPS). The main findings revealed that the Grade 1 learners are acquiring foundational reading skills in Xitsonga very slowly during the first year of schooling and on all measures, performance was either low or very low. The teachers’ lack of deep understanding of how early reading develops and how each of the reading activities contributes to different aspects of this development may have contributed to the learners’ reading outcomes. Findings further revealed that the ability to read fluently and with comprehension is determined by hierarchical relationships between various reading skills. Thus, knowledge of letter-sounds facilitates word reading which impacts reading fluency and then reading comprehension – all these skills are important for reading development during early learning only if they are taught well in the classroom. / Ku hlaya ni ku tsala swi tikela vadyondzi vo tala laha Afrika Dzonga. Eka ndzavisiso lowu, ku va hi ta kota ku twisisa leswi swi humelelaka mayelana na matirhelo yo hlaya ya vadyondzi va ntangha R-3, hi kambela vuswikoti lebyi vadyondzi va ntlawa wo sungula (Giredi 1) va nga na byona byo hlaya hi ririmi ra manana (mune wa swikolo) na hi ririmi leri ri nga le eka xiyimo xa masungulo (xikolo xin’we) hi ku tirhisa xikambelwana lexi xi vuriwaka early grade reading assessment (EGRA). Xikambelwana lexi (EGRA) xi ni nkoka lowu kulu mayelana ni ku kambela vuswikoti bya n’wana byo hlaya. Mbuyelo wa xikambelo lexi wu pfuna ngopfu mayelana na leswaku vadyondzisi va kota ku kunguhata madyindziselo lama ya angarhelaka vadyondzi hinkwavo. Ndzavisiso lowu wu humelerisiwile hi ku kambela madyondziselo yo hlaya ni ku tsala eka ntlawa wo sungula (Giredi 1), ku kambela xivumbeko xa kamara ro dyondzela eka rona, ni ku kambela vutivi bya kharikhulamu bya vadyondzisi va ntlawa wo sungula na vaseketeri va vona (curriculum advisors). Mbuyelonkulu wu humesele erivaleni leswaku vadyondzi va kuma ntokoto wo hlaya hi Xitsonga hi ku nonoka va ha ri eka lembe ra vona ro sungula xikolo. Leswi swi thlela swi nyanyisa na hi leswaku mbuyelo wa vona wo hlaya eka swiyenge hinkwaswo swa xikambelo lexi xi nga tirhisiwa ku va kambela a wu ri ehansi ngopfu. Eka ndzavisiso lowu, ku pfumala ka vadyondzisi vutivi hi vuenti bya ku dyondzisa vana eku hlaya swi nga va swi vile na xiave eka mbuyelo wa vadyondzi wo hlaya. Vulavisisi lebyi byi thlela byi humesela erivaleni leswaku vuswikoti byo hlaya hi ku twisisa swi koteka ntsena loko mudyonzi a ri ni ntokoto eka swiyenge hinkwaswo swa ku hlaya hikuva swi na vuxaka. Hikokwalaho, vuswikoti byo hlaya mimpfumawulo ya maletere swi pfuneta ku hlaya marito lawa ya thlelaka ya pfuneta ku hlaya hi nkhuluko ni ku twisisa leswi swi hlayiwaka. Vuswikoti lebyi hinkwabyo byi ni nkoka mayelana ni ku dyondza ku hlaya ntsena loko madyondziselo yo hlaya ya landzelerisa leswi kunguhatiweke eka kharikhulamu. / Leesgeletterdheid vir baie swart Suid-Afrikaanse leerders is ‘n probleem. Om te verstaan wat in die Suid-Afrikaanse grondslagfase-klaskamers gebeur wat die leesprestasie van leerders beïnvloed, word in die studie die aangepaste instrument vir vroeë graad leesassessering (EGRA) gebruik om die leesvermoëns van Graad 1-leerders in die huistaal (vier skole) en in die eerste addisionele taal (een skool). Die EGRA is belangrik vir die meting van fundamentele geletterdheidsvaardighede. Die uitkomste daarvan help onderwysers om onderrig te beplan wat voldoen aan verskillende leervermoëns. Data is versamel deur die waarneming van geletterdheidspraktyke en aktiwiteite in die Graad 1-klaskamers, die klaskamerinstellings te evalueer en onderhoude met Graad 1-onderwysers en kurrikulumadviseurs van die algemene onderwys- en opleidingsband te onderneem om hul persepsie van Curriculum and Assessment Policy Statement (CAPS) te verstaan. Die belangrikste bevindings het getoon dat die graad 1-leerders in die eerste jaar van skool baie stadig basiese leesvaardighede in Xitsonga verwerf, en dat prestasies op alle maatstawwe laag of baie laag was. Die onderwysers se gebrek aan diep begrip van hoe vroeë lees ontwikkel en hoe elkeen van die leesaktiwiteite bydra tot verskillende aspekte van hierdie ontwikkeling, het moontlik tot die leerders se leesuitkomste bygedra. Bevindinge het verder aan die lig gebring dat die vermoë om vlot en met begrip te lees, bepaal word deur hiërargiese verwantskappe tussen verskillende leesvaardighede. Kennis van letterklanke vergemaklik dus die lees van woorde wat die vloeiendheid van lees en dan leesbegrip beïnvloed - al hierdie vaardighede is slegs belangrik vir leesontwikkeling tydens vroeë leer as dit goed in die klaskamer geleer word. / Linguistics and Modern Languages / Ph. D. (Languages, Linguistics and Literature)

English with Englsih, Northern Sotho and Tsonga summaries / Since the inception of the homestead food garden programme in Gauteng Province, more than 3 000 individuals in the City of Tshwane Region 7 have benefited from the programme. It is not known whether the gardens were actually established after beneficiaries had received the tools from government, or whether the gardens still exist and produce food. The aim of the study was to investigate the contribution of the homestead food garden programme to household food security in Region 7 in the City of Tshwane Metropolitan Municipality. The study population consisted of beneficiaries of the homestead food garden programme from 2013 to 2016 in various wards in the region. The objectives of the study were to determine the socio-demographic characteristics of the beneficiaries; to assess the current status of the homestead food gardens and other support programmes in which the beneficiaries were engaged; to assess the contribution of the homestead food garden programme to household food security (availability, accessibility, utilisation and stability); to ascertain the factors influencing food availability in the households of beneficiaries; and to identify the constraints and benefits of homestead food production. The study used a quantitative research approach involving a survey design. A semistructured questionnaire was used for data collection through face-to-face interviews in the homes of participants. The random sampling technique was employed to acquire a proportionate sample of 258 participants. Data were analysed using the Statistical Package for Social Sciences (SPSS) version 24. The analysis of quantitative data included frequencies, percentages, mean and standard deviation, standard error of mean, a binomial test and the Ordered Logistics Regression (OLR) model. Themes and codes were used to analyse data from open-ended questions (qualitative data) and convert them to frequencies and percentages. The results showed that 73% of women participated and96% participants were Black Africans. Youth participation was 19%. The participants who could read and write because they had received primary, secondary and tertiary education were 84%. The average family size of the respondents was five, ranging between 1 and 47 household members. 83% of the participants relied on social grants (child, old-age and disability grants) from government as their main source of income. 83.3% participants had backyard (homestead) gardens for their households and 26% of participants consumed vegetables from their homestead food gardens. The household expenditure of 74% of participants included the cost of vegetables, which they had to buy regularly. The food availability results showed that 51% and 50% of the participants cultivated their backyard gardens during summer and spring respectively. This implied that there were adequate vegetables in the households of most participants during those seasons. It was discovered that 60% of the participants experienced anxiety and uncertainty because they were worried over the previous four weeks that their households would not have enough vegetables. The coping strategy mostly adopted by 69% of participants was to purchase cheap vegetables when there was lack of vegetables from the gardens. 55% participants consumed vegetables frequently because they either had enough harvests from their backyard gardens or had money to buy vegetables. The factors that positively influenced vegetable availability were participants’ age; the number of support programmes available to them; the existence of backyard gardens; and access to water. Some of the major challenges that systematically hindered homestead food gardens were insects; pests and diseases; crop damage by livestock, birds and rats; a lack of water for irrigation; a lack of production inputs (seeds, chemicals, fertilisers and others); and insufficient space to plant or establish a garden. The study found that the major benefits of the homestead food gardens were the consumption of fresh, healthy vegetables from the backyard garden and saving money by not having to buy vegetables. Based on the results of the current study, it is suggested that youth participation should be bolstered to ensure the future of homestead food gardens as the majority of the participants were older than 35 years. It is also suggested that other support measures should be taken to ensure the continuity of the homestead food garden programme, such as training programmes and access to water, fencing and production inputs (seeds and fertilisers) for homestead food gardeners. / Go tloga mola go thongwago lenaneo la dirapana tša dijo la motsana ka Profenseng ya Gauteng, batho ba go feta ba 3 000 ka Seleteng sa 7 sa Tshwane ba holegile ka go fiwa dithulusi tša serapana, seabe sa tšweletšo le tlhahlo go thoma dirapana tša ka mafuri tša malapa a bona. Ga go tsebege ge eba dirapana dihlomilwe ka nnete morago ga gore baholegi ba amogele dithulusi go tšwa mmušong, goba ge eba dirapana di sa le gona le gore di tšweletša dijo. Dinepo tša dinyakišišo e be e le go nyakišiša seabe sa lenaneo la dirapana tša dijo la motsana go tšhireletšo ya dijo tša lapa Seleteng sa 7 ka Mmasepaleng wa Metropothene wa Toropo ya Tshwane. Bakgathema ba dinyakišišo ba bopilwe ke baholegi ba lenaneo la serapana sa dijo sa motsana go tloga ka 2013 go fihla ka 2016 ka diwateng tša go fapana tša selete. Maikemišetšo a dinyakišišo e be e le laetša dipharologantšho tša batho le leago tša baholegi; go sekaseka maemo a bjale a dirapana tša dijo tša motsana le mananeo a mangwe a thekgo ao baholegi ba bego ba le karolo ya ona; go sekaseka seabe sa lenaneo la serapana sa dijo sa motsana go tšhireletšo ya dijo (khwetšagalo, phihlelelo, tšhomišo le tielelo); go laetša mabaka a go huetša khwetšagalo ya dijo ka malapeng a baholegi; le go hlaola mathata le dikholego tša tšweletšo ya dijo tša motsana. Dinyakišišo di šomišitše mokgwa wa dinyakišišo tša khwalithethifi wa go akaretša popo ya lenaneopotšišo. Lenaneopotšišo le beakantšwego seripa le go šomišetšwa kgoboketšo ya datha ka dipoledišano tša go dirwa go lebelelanwe mahlong ka malapeng a bakgathatema. Thekniki ya tiro ya sampole ya go se kgethe e šomišeditšwe go hwetša sampole ya go lekanetšwa ya bakgathema ba 258. Datha di sekasekilwe ka go šomiša tlhalošo ya 4 ya Statistical Package for Social Sciences (SPSS). Tshekatsheko ya datha ya khwalithethifi e akareditše dikelo, diphesente, palogare, phapano ya tekanetšo, phošo ya tekanetšo ya palogare, teko ya phapano le mmotlolo wa ponelopele ya diphetogo. Dikgwekgwe le Dikhoute di šomišitšwe go sekaseka datha go tšwa go dipotšišo tše di bulegilego (datha ya khwalithethifi) le go di fetolela go dikelo le diphesente. Dipoelo di laeditše gore phesente ya godimo (73%) ya basadi e kgathile tema. Bontši (96%) e bile baarabi e bile Maafrika a Bathobaso. Kgathotema ya baswa e be e le ka fase ga 19%. Bontši (84%) bja baholegi bo be bo kgona go bala le go ngwala gobane ba amogetše thuto ya poraemari, sekontari le ya godimo. Bogolo bja lapa bja palogare ya baarabi e be e le hlano, go tloga gare ga tee le 47 ya maloko a lapa. Karolo ye kgolo (83%) ya baarabi ba tshephile dithušo tša leago (dithušo tša bana, botšofadi le bogolofadi) go tšwa mmušong bjalo ka mothopo wa bona wo mogolo wa letseno gomme bontši (83.3%) bo be bo na le dirapana (motsana) tša ka mafuri tša malapa a bona. Go tloga go ponego ya tšhireletšo ya dijo, dipoelo di laeditše gore 26% ya baarabi ba ja merogo ya go tšwa ka dirapaneng tša dijo tša motsana wa bona. Ditshenyegalelo tša lapa tša bontši (74%) bja baarabi di akareditše tshenyegelo ya merogo, yeo ba bego ba swanela ke go e reka kgafetša. Dipoelo tša khwetšagalo ya dijo e laeditše gore 51% le 50% ya baarabi ba lemile dirapana tša ka mafuri a bona nakong ya selemo le seruthwane ka tatelano, seo se rago gore go bile le merogo ye e lekanego la malapeng a baarabi ba bantši dihleng tšeo. Ka go realo go utulotšwe gore, mabapi le phihlelelo ya dijo, bontši (60%) bja baarabi ba itemogetše tlalelo le pelaelo bjalo ka ge ba laeditše gore ba be ba hlobaela mo dibekeng tše nne tša go feta gore malapa a bona a ka se be le merogo ye e lekanego. Leano la go laola le le amogetšwego gagolo ke bontši (69%) bja baarabi go kgonthišiša tielelo ya dijo e be e le go reka merogo ka theko ya fase ge go sena merogo go tšwa ka dirapaneng. Mabapi le tielelo ya dijo, bontši (55%) bja bakgathatema ba be ba e ja merogo kgafetša gobane ba bunne tše di lekanego go tšwa dirapaneng tša ka mafuri a bona goba ba bile le tšhelete ya reka merogo. Mabaka ao a hueditšego khwetšagalo ya merogo gabotse e bile mengwaga ya baarabi; palo ya mananeo a thekgo ao ba ka a fihlelelago; go ba gona ga dirapana tša ka mafuri; le phihlelelo ya meetse. Tše dingwe tša ditlhohlo tše kgolo tšeo di tshwentšego ka botlalo dirapana tša dijo ka motsaneng e bile dikhunkhwane; disenyi le malwetši, tshenyo ya dibjalo ka leruo, dinonyana le magotlo; tlhokego ya meetse a go nošetša; tlhokego ya ditshepetšo tša tšweletšo (dipeu, dikhemikale, manyora le tše dingwe); le sekgoba se lekanego go bjala le go hloma serapana. Dinyakišišo di hweditše gore dikholego tše kgolo tša dirapana tša dijo tša motsana e be e le go ja merogo ye meswa, ye mebotse go tšwa ka serapaneng sa ka mafuri le go boloka tšhelete ka go se reke merogo. Go ya ka dipoelo tša dinyakišišo tša bjale, go šišintšwe gore kgathotema ya baswa e swanetše go thekgwa go kgonthišiša bokamoso bja dirapana tša dijo tša motsana ka ge bontši bja bakgathatema ba be ba le bogolo bja mengwaga ya ka godimo ga 35. Gape go šišintšwe gore dikelo tša thekgo tše dingwe di swanela go tšewa go kgonthišiša tšwelopele ya lenaneo la serapana sa dijo sa motsana, go swana le mananeo a tlhahlo le phihlelelo ya meetse, legora le production inputs (dipeu le manyora) ya boradirapana tša dijo tša motsana. / Ku sukela loko ku sunguriwe nongonoko wa swirhapa swa swakudya eka Xifundzhankulu xa Gauteng, vanhu vo tlula nhlayo ya 3 000 eTshwane eka Region 7 va vuyeriwile hi ku pfunetiwa hi mathulusi ya swirhapa, swipfuneto swo rima na vuleteri ku sungula swirhapa lomu majaratini ya miti ya vona. A swi tiveki loko swirhapa swi sunguriwe endzhaku ka loko vavuyeriwa va amukerile mathulusi eka mfumo, kumbe leswo xana swirhapa leswi swa ha ya emahlweni no rima swakudya. Xikongomelo xa ndzavisiso lowu wa tidyondzo a ku ri ku endla vulavisisi hi ndlela leyi nongonoko wa swirhapa swa swakudya wu pfunetaku hi yona eka ku sirheleleka hi swakudya eka Region 7 eka Masipala wa Dorobankulu ra City of Tshwane Metropolitan Municipality. Vanhu lava a ku dyondziwa hi vona a va katsa vavuyeriwa va nongonoko wa swirhapa swa swakudya lomu makaya ku sukela hi lembe ra 2013 ku fikela hi 2016 eka tiwadi to hlayanyana ta region. Swikongomelo swa ndzavisiso lowu i ku vona muxaka wa vanhu lava nga vuyeriwa; ku kambela xiyimo xa sweswi xa swirhapa swa swakudya na minongonoko yin'wana ya nseketelo laha vavuyeriwa va nga na xiavo eka yona; ku kambela xiavo xa nongonoko wa swirhapa swa swakudya eka ku sirheleleka hi ku kuma swakudya eka mindyangu (ku kumeka, ku fikelela, ku tirhisa, na ku tshamiseka); ku kumisisa mintiyiso kumbe swilo leswi swi nga na nkucetelo eka ku kumeka ka swakudya lomu makaya ya lava vuyeriwaka; na ku vona leswi swi nga swihingakanyi eka mimbuyelo ya ku rima swakudya. Ndzavisiso wu tirhise fambiselo leri vuriwaka quantitative research ku nga ku hlayela leswi a swi katsa dizayini ya survey. Ku tirhisiwe endlelo ra nongonoko wa swivutiso leswi nga tsariwa ku nga semi-structured questionnare ku hlengeleta data hi ku endla ti-interview ta xikandza-na-xikandza emakaya ya lava a va teka xiavo. Ku tirhisiwe thekniki ya random sampling ku kuma mpimanyeto wa proporionate sample eka vanhu va 258 lava a va teka xiavo eka ndzavisiso. Data yi ve yi hlahluviwa hi ku tirhisa Statistical Package for Social Sciences (SPSS) version 24. Nhlahluvo wa quantitative data a wu katsa vungani bya ku humelela ku nga frequences, tiphesente, mean, standard deviation, standard error of mean, binomial test na modlele wa Ordered Logistics Regresion (OLR). Eku hlahluveni ku tirhisiwe tithemes na tikhodi ku kambela data eka swivutiso leswi a swi ri na tinhlamulo to hambana-hambana ku nga open-ended questions (qualitative data) na ku swi hundzuluxa ku va swikombisa leswo swi endleke kangani (frequencies) na tiphesente ta ku endleka. Vuyelo byi kombise tiphesente ta le henhla eka vamanana hi (73%) lava a va ri na xiavo. Vunyingi bya vanhu lava a va hlamula swivutiso a ku ri Vanhu va Vantima va Ma-Afrika. Xiavo xa lavantshwa a xi ri ehansi ka 19%. Vunyingi bya vavuyeriwa (84%) a va kota ku hlaya no tsala hikuva a va kumile dyondzo ya prayimari, sekondari na ya le tikholichi na tiyunivhesiti. Mpimanyeto wa nhlayo ya vanhu va mindyangu a ku ri vanhu va ntlhanu, ku sukela eka wun'we ku fikela eka swirho swa 47 eka ndyangu. Ntsengo wa le henhla wo ringana (83%) wa vahlamula swivutiso i vanhu lava va hanyaka hi mpfuneto wa mali ya mfumo eka vanhu (ku nga xipfuneto xo wundla vana, mudende wa vadyuhari, na mpfuneto eka vo lamala) ku suka eka mfumo tani hi mali leyi nghenaka leyi va tshembeleke eka yona ngopfu kasi vunyingi bya vona (83.3%) va na swirhapa (lomu makaya) emitini ya vona. Mayelana na ku sirheleleka hi swakudya, vuyelo byi kombise leswo 26% wa vahlamuri va swivutiso va dya miroho yo huma eka swirhapa swa swakudya swa vona. Mpimanyeto wa mali lowu tirhisiwaka hi mindyangyu yo tala ku nga (74%) wa vahlamuri va swivutiso va katse ntsengo wa nxavo wa miroho, leyi va yi tirhisaka ku xava hi mikarhi na mikarhi. Vuyelo bya ku kumeka ka swakudya wu kombe leswo 51% wa vahlamuri va swivutiso va rima swakudya swa vona lomu swirhapeni swa le makaya ya vona hi nkarhi wa ximumu na hi nkarhi wa ximun'wana, leswi swu vulaka leswo a ku ri na miroho yo ringanela eka miti eka vahlamuri votala va swivutiso hi mikarhi ya tisizini leti. Ku ve ku kumeka leswaku mayelana na ku kumeka ka swakudya, vunyingi lebyi nga (60%) wa vahlamuri va swivutiso va karhateka na ku va va nga ri na ku tiyiseka hikuva va kombise leswo va xaniseka eka mavhiki ya mune lama nga hundza leswo mindyangu ya vona yi nga ka yi nga vi na miroho yo ringanela. Leswi vunyingi byi swi endleka ku ringeta ku hanya eka xiyimo lexi, vunyingi byi nga (69%) wa vahlamuri va swivutiso va vule leswo va xava miroho ya ntsengo wa nxavo wa le hansi loko ku nga ri na miroho eswirhapeni swa vona. Mayelana na ku tshamiseka hi swakudya, vunyingi bya vahlamuri va swivutiso (55%) va dya miroho hakanyingi hikuva va ri na ntshovelo wo ringanela eka swirhapa swa miroho ya vona kumbe hikuva va ri na mali yo xava miroho. Swilo leswi nga na nkucetelo lowunene hi ku kumeka ka miroho, ku ve malembe ya vukulu bya vahlamuri va swivutiso; nhlayo ya minongonoko ya nseketelo eka vona; vukona bya swirhapa swa miroho lomu makaya; na ku kumeka ka mati. Swin'wana swa mintlhontlho leyikulu leyi nga nkavanyeto eka swirhapha swa swakudya i switsotswana na vuvabyi ya swimila; ku onhiwa ka swibyariwa hi swifuwo; swinyenyane na makondlo; ku pfumaleka ka mati yo cheleta; ku pfumaleka ka swipfuneto swo rima (ku nga timbewu, tikhemikali, swinonisi na swin'wana swo tano); ku ka vanhu va nga ri na ndhawu yo ringanela ku byala kumbe ku endla swirhapa. Ndzavisiso wa dyondo wu kume leswo vunyingi bya vavuyeriwa eka swirhapa swa swakudya ku ve ku kota ku va na miroho ya furexe, miroho leyi nga na rihanyu eka swirhapa swa vona lomu makaya no hlayisa mali hikuva va nga xavi miroho. Hi ku landza vuyelo bya ndzavisiso wa dyondo wa sweswi, ku ringanyetiwa leswaku ku fanele ku khutaziwa ku va na xiavo ka vantshwa ku tiyisa vumundzuku bya swirhapa swa miroho, hikuva vunyingi bya lava va nga na xiavo a ku ri vanhu va malembe ya le henhla ka 35 hi vukulu. Ku pimanyetiwa na leswo ku fanele ku va na tindlela tin'wana to seketela ku tiyisa leswo nongonoko wa swirhapa swa swakudya wu ya emahlweni, ku endliwa ka swilo swo fana na minongonoko ya vuleteri, ku biyela swirhapa hi mifensi na swipfuneto swo byala (swo fana na timbewu na swinonisi eka swirhapa swa swakudya lomu makaya. / Agriculture and  Animal Health / M. Sc. (Agriculture)