417 research outputs found
Pre-breeding sesame (Sesamum indicum L.) for improved yield, and oil quality and quantity in Ethiopia = Ukuzalanisa kwangaphambili i-Sesame (Sesamum indicum L.) ukuze kuvunwe u-oyela okuthuthukisiwe, oyikhwalithi nomningi e-Ethiopia.
No full textDoctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.ABSTRACT
Pre-breeding Sesame (Sesamum indicum L.) for Improved Yield, and Oil Quality and Quantity in Ethiopia
Sesame (Sesamum indicum L.; 2n = 2x = 26) is a multi-purpose industrial oilseed crop serving the food, feed, and cosmetic industries globally. Sesame is Ethiopia’s most valuable export crop after coffee (Coffea arabica L.), contributing to socio-economic development. However, the productivity of the crop is low (<0.6 ton ha-1) and stagnant in Ethiopia and other major sesame growing regions in sub- Saharan Africa due to a multitude of production constraints. The low yield of sesame is attributable to lack of high-yielding and well-adapted varieties, with less capsule shattering; resistant/tolerant to biotic and abiotic stresses; a lack of modern crop production technologies and well developed infrastructure. Sesame remains a largely under-researched and underutilized crop in Ethiopia despite its economic value in the local, regional and international trades. There is a need for a dedicated sesame genetic improvement programme to develop and deploy new improved varieties with farmer- and market-preferred traits. Therefore, the specific objectives of this study were: i) to document sesame production opportunities and constraints and farmer-and market-preferred varieties and traits in eastern and southwestern Ethiopia as a guide for breeding; ii) to determine the variance components, broad-sense heritability (h2b) and association of seed and oil yield-related traits in Ethiopian sesame germplasm for effective breeding; iii) to determine the extent of genetic variation among 100 diverse sesame germplasm collections of Ethiopia using phenotypic traits and simple sequence repeat (SSR) markers and select distinct and contrasting genotypes for breeding and iv) to determine the genetic diversity and relationships among Ethiopia’s sesame germplasm collections using seed oil content and fatty acid compositions and diagnostic SSR markers and select genetically unique and promising parental lines for breeding. Different but complementary research activities were conducted to attain the objectives.
The first study was conducted using a participatory rural appraisal (PRA) involving 160 farmers in two selected sesame growing regions and four districts in Ethiopia. A considerable proportion of the respondent farmers (56.0%) reported cultivating sesame using seeds of unknown varieties often sourced from the informal seed sector. The most important constraints to sesame production in the study areas were lack of access to improved seeds (reported by 83.0% of respondents), low yield potential of the existing varieties (73.8%), diseases (69.4%), and low market price (68.8%). These constraints were attributed to the lack of a dedicated breeding programme, formal seed sector, strong extension services, and well-developed pre-and post-harvest infrastructures.
The most important market-preferred traits of sesame included true-to-type seed, white seed colour, and high seed oil content. Reasonable market price, resistance to crop diseases, drought tolerance, resistance to crop insect pests, higher seed yield, higher thousand-seed weight, higher oil content, white seed colour, early maturity, and good oil qualities such as aroma and taste were the vital farmer-preferred attributes in order of significance. Hence, these traits should be integrated in current and future sesame breeding programs.
The second study evaluated 100 sesame germplasm under field conditions at two locations using a 10 x 10 lattice design with two replications. The findings revealed a higher genotypic coefficient of variation and h2b values for the number of primary branches (NPB), number of secondary branches (NSB), thousand seed weight (TSW), seed yield per hectare (SYH) and oil yield per hectare (OYH), suggesting that high genetic gains can be achieved through selection. Higher direct effects of OYH and number of seeds per capsule (NSPC) were recorded affecting SYH, while SYH, number of capsules per plant (NCPP) and TSW had a higher direct effect on OYH. Genotypes Hirhir Kebabo Hairless-9, Setit-3, Orofalc ACC-2, Hirhir Humera Sel-6, Setit-1 and ACC-NS-007(2) were selected for further breeding based on their high seed yield, oil content and oil yield.
In the third part of the study, 100 sesame entries were field evaluated at two locations in Ethiopia for agro-morphological traits and seed oil content using a 10 × 10 lattice design with two replications. Also, test genotypes were profiled using 27 polymorphic SSR markers at the Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences. Analysis of variance revealed significant (p≤ 0.05) entry by environment interaction for plant height, internode length, number of secondary branches, and grain yield. Genotypes such as Hirhir Kebabo Hairless-9, Setit-3, Orofalc ACC-2, Hirhir Humera Sel-6, ABX = 2-01-2, and Setit-1 recorded grain yield of >0.73 ton ha−1. Grain yield had positive and significant (p < 0.01) associations with oil yield (r = 0.99), which is useful for simultaneous selection. Moderate gene diversity and polymorphic information content values of 0.30 and 0.25 were recorded based on SSR analysis, respectively. The genotypes were separated into two and four major distinct groups based on cluster and population structure analyses, respectively, thus enabling selection and subsequent crossing to develop breeding populations for cultivar development. Based on phenotypic and genomic divergence, the following superior and complementary genotypes were selected: Hirhir Humera Sel-6, Setit-3, Hirhir Kebabo Hairless Sel-4, Hirhir Nigara 1st Sel-1, Humera-1 and Hirhir Kebabo Early Sel-1 (from cluster II-a), Hirhir kebabo hairless-9, NN-0029(2), NN0068-2 and Bawnji Fiyel Kolet, (from cluster II-b). The selected genotypes will serve as parents for sesame breeding program in Ethiopia.
Iqoqa
I-Sesame (Sesamum indicum L.; 2n = 2x = 26) iyisitshalo sembewu kawoyela enezinhloso eziningi ephakela izimboni ukudla, izimboni eziphakelyo, nezimboni zezimonyo emhlabeni jikelele. I-Sesame iyisitshalo esiyigugu kakhulu sase-Ethiopia esithunyelwa ngaphandle ngemuva kwekhofi (i-Coffea arabica L.), esinegalelo ekuthuthukisweni kwenhlalakahle yezomnotho. Nokho, ukukhiqiza kwezitshalo kuphansi ngomklamo ka (<0.6 ton ha-1) futhi kumile e-Ethiopia nakwezinye izindawo ezinkulu ezitshala i-sesame e-sub-Saharan Africa ngenxa yobuningi bezingqinamba zokukhiqiza. Isivuno esiphansi se-sesame sibangelwa wukuntuleka kwezinhlobo ezikhiqiza kakhulu futhi eziguquguqukayo, ezinokuqhekeka okuncane kwekhepsuli; ukucindezeleka kwe-biotic kanye ne-abiotic; ukuntuleka kobuchwepheshe besimanje bokukhiqiza izitshalo nengqalasizinda ethuthuke kahle. I-Sesame isalokhu iyisitshalo esingacwaningiwe futhi esisetshenziswa kancane e-Ethiopia naphezu kokubaluleka kwayo kwezomnotho ekuhwebeni kwasekhaya, kwesifunda kanye nakwamanye amazwe. Kunesidingo sohlelo oluzinikele lokuthuthukisa izakhi zofuzo ze-sesame ukuze kuthuthukiswe futhi kusetshenziswe izinhlobo ezintsha ezithuthukisiwe ezinezimpawu ezikhethwa abalimi nezimakethe. Ngakho-ke, izinhloso eziqondile zalolu cwaningo kwakuyilezi: i) ukubhala amathuba nezingqinamba zokukhiqiza i-sesame kanye nezinhlobo nezici ezikhethwa abalimi nezimakethe empumalanga naseningizimu-ntshonalanga ye-Ethiopia njengomhlahlandlela wokuzalanisa; ii) ukunquma izingxenye ezihlukene, ukutholakala komqondo obanzi (h2b) kanye nokuhlotshaniswa kwezici ezihlobene nembewu nesivuno sikawoyela ku-germplasm ye-sesame yase-Ethiopia ukuze zizale ngempumelelo; iii) ukunquma izinga lokuhlukahluka kofuzo phakathi kwamaqoqo e-sesame germplasm ayikhulu (100) ahlukahlukene ase-Ethiopia kusetshenziswa izimpawu ze-phenotypic kanye nezimpawu eziphindaphindayo ezilandelanayo, phecelezi, i-Simple Sequence Repeat (SSR) nokukhetha izinhlobo zofuzo ezihlukile nezihlukile zokuzalanisa kanye iv) ukunquma ukuhlukahluka kofuzo kanye nobudlelwano phakathi kwamaqoqo e-sesame germplasm yase-Ethiopia kusetshenziswa okuqukethwe kukawoyela wembewu kanye nokuqanjwa kwe-esidi enamafutha kanye nezimpawu zokuxilonga ze-SSR bese ukhetha imigqa yabazali eyingqayizivele nethembisayo yokuzalanisa. Kwenziwa imisebenzi yocwaningo eyahlukene kodwa ehambisanayo ukuze kuzuzwe izinjongo.
Ucwaningo lokuqala lwenziwa kusetshenziswa i-participatory rural appraisal (PRA) ebandakanya abalimi abayikhulu namashumi aysithupha (160) ezifundeni ezimbili ezikhethiwe ezitshala i-sesame kanye nezifunda ezine e-Ethiopia. Ingxenye enkulu yabalimi abaphendulile (56.0%) babike ukuthi balima i-sesame besebenzisa izimbewu zezinhlobo ezingaziwa ezivame ukutholakala emkhakheni wembewu ongekho emthethweni. Izithiyo ezibaluleke kakhulu ekukhiqizweni kwe-sesame ezindaweni zocwaningo kwaba ukuntula ukufinyelela kwembewu ethuthukisiwe (okubikwe ngabangu- 83.0% abaphendulile), isivuno esiphansi sezinhlobo ezikhona (73.8%), izifo (69.4%), kanye nentengo ephansi yemakethe (68.8%). Lezi zingqinamba zidalwe ukushoda kohlelo oluzinikele lokuzalanisa, umkhakha wembewu osemthethweni, izinsiza eziqinile zokwandisa, kanye nengqalasizinda ethuthuke kahle ngaphambi nangemuva kokuvuna. Okubaluleke kakhulu izici ezikhethwa yizimakethe ze-sesame zihlanganisa imbewu yohlobo lwangempela, umbala wembewu emhlophe, nokuqukethwe kwamafutha embewu ephezulu. Intengo enengqondo yemakethe, ukumelana nezifo zezitshalo, ukubekezelela isomiso, ukumelana nezinambuzane zezitshalo, isivuno esiphezulu sembewu, isisindo sembewu eyinkulungwane, uwoyela ophakeme, umbala wembewu emhlophe, ukuvuthwa ngaphambi kwesikhathi, kanye nezimfanelo ezinhle zikawoyela njengephunga nokunambitha kwaba izici ezibalulekile ezikhethwa ngumlimi ngokulandelana kokubaluleka. Ngakho-ke, lezi zici kufanele zihlanganiswe ezinhlelweni zamanje nezesikhathi esizayo zokuzalanisa ama-sesame.
Ucwaningo lwesibili luhlole i-germplasm ye-sesame eyikhulu (100) ngaphansi kwezimo zensimu ezindaweni ezimbili kusetshenziswa idizayini ye-lattice engu-(10 x 10) enezimpinda ezimbili. Okutholakele kuveze inani eliphakeme le-genotypic coefficient ye-variation kanye namanani e-h2b yenani lamagatsha ayisisekelo, (i-NPB), inombolo yamagatsha esibili, phecelezi, number of secondary branches (NSB), isisindo sembewu eyinkulungwane, (i-TSW), isivuno sembewu ngehektha ngalinye, (i-SYH) kanye nesivuno samafutha ngehektha ngalinye, (i-OYH), ephakamisa ukuthi izinzuzo eziphezulu zofuzo zingatholakala ngokukhethwa.
Imiphumela eqondile ephakeme ye-OYH kanye nenani lembewu nge-capsule ngayinye (NSPC) zarekhodwa ezithinta i-SYH, kuyilapho i-SYH, inani lamaphilisi ngesitshalo ngasinye (NCPP) kanye ne-TSW ibe nomthelela oqondile ophezulu ku-OYH. I-Genotypes u-Hirhir Kebabo Hairless-9, i-Setit-3, i-Orofalc ACC-2, i-Hirhir Humera Sel-6, i-Setit-1 kanye ne-ACC-NS-007(2) bakhethelwe ukuqhubeka nokuzalaniswa ngokusekelwe emvuzweni yabo ephezulu yembewu, okuqukethwe kukawoyela namafutha.
Engxenyeni yesithathu yocwaningo, okufakiwe okuyinkulungwane (1000) kwe-sesame kwahlolwa ezindaweni ezimbili e-Ethiopia ukuze kutholwe izici ze-agro-morphological kanye nokuqukethwe kwamafutha embewu kusetshenziswa idizayini ye-lattice engumashumi aphindwe kashumi (10 × 10) enezimpinda ezimbili. Futhi, ukuhlolwa kohlobo lwe-genotype kwenziwa iphrofayili kusetshenziswa omaka be-SSR be-polymorphic abangamashumi amabili nesikhombisa (27) e-Oil Crops Research Institute ye-Chinese Academy of Agricultural Sciences. Ukuhlaziywa kokuhluka kuveze okubalulekile (p ≤ 0.05) ukungena ngokusebenzelana kwemvelo ngobude besitshalo, ubude be-internode, inombolo yamagatsha esibili, nesivuno sokusanhlamvu. Ama-Genotypes afana no-Hirhir Kebabo Hairless-9, i-Setit-3, i-Orofalc ACC-2, i-Hirhir Humera Sel-6, i-ABX = 2-01-2, kanye ne-Setit-1 erekhodiwe isivuno sokusanhlamvu esingu->0.73 ton ha−1. Isivuno sokusanhlamvu sasinezivumelwano ezinhle nezibalulekile (p <0.01) nesivuno samafutha (r = 0.99), okuwusizo ekukhetheni ngesikhathi esisodwa. Ukuhlukahluka kwezakhi zofuzo okumaphakathi kanye namanani okuqukethwe kolwazi lwe-polymorphic we-0.30 no-0.25 arekhodwa ngokusekelwe ekuhlaziyweni kwe-SSR, ngokulandelanayo. Izinhlobo ze-genotype zahlukaniswa zaba amaqembu amabili namaqembu amane, amakhulu, ahlukene ngokusekelwe ekuhlaziyweni kweqoqo kanye nesakhiwo sabantu, ngokulandelana, ngaleyo ndlela kuvumela ukukhetha nokuwela okulandelayo ukuze kuthuthukiswe imiphakathi yokuzalanisa futhi kuthuthukiswe izimila. Ngokusekelwe ekwehlukeni kwe-phenotypic kanye ne-genomic, lawa ma-genotype alandelayo aphezulu futhi ahambisanayo akhethiwe: u-Hirhir Humera Sel-6, u-Setit-3, u-Hirhir Kebabo Hairless Sel-4, u-Hirhir Nigara 1st Sel-1, u-Humera-1 no-Hirhir Kebabo Early Sel-1 (kusuka ku-cluster II-a), i-Hirhir kebabo hairless-9, i-NN-0029(2), i-NN0068-2 kanye ne-Bawnji Fiyel Kolet, (kusuka ku-cluster II-b). Ama-genotype akhethiwe azosebenza njengabazali bohlelo lokuzalanisa u-sesame e-Ethiopia
Genetic enhancement of pearl millet (pennisetum glucum (L.) R. Br.) for resistance to striga bermonthica (Del.) benth and compatibility to fusarium oxysporum F. sp. strigae in Burkina Faso.
No full textDoctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.Pearl millet (Pennisetum glaucum [L.] R. Br. 2n = 2x = 14) is one of the most important cereal crops cultivated in the semi-arid tropics of sub-Saharan Africa and India, serving millions of households, and local and regional markets. It is a staple food crop in Burkina Faso, widely grown in the Sahelian and Sudano-Sahelian zones, characterised by poor soil conditions and erratic rainfall, and high temperatures. However, the potential production and productivity of pearl millet in Africa, including Burkina Faso, is constrained by the parasitic weed [Striga hermonthica (Del.) Bentham], bird damage, downy mildew, head miner, and low-yielding landraces. Developing S. hermonthica-resistant pearl millet varieties adapted to semi-arid regions with the desirable farmer and market-preferred traits would enhance yield gains and sustainable production. Therefore, the overall objective of this study was to improve pearl millet production and productivity in Burkina Faso by developing pearl millet varieties with Striga-resistance, compatibility with a biocontrol agent, Fusarium oxysporum f.sp. Strigae (FOS) and adapted to local agroecologies. The specific objectives of this study were to: (i) investigate the constraints affecting pearl millet production and farmers’ approaches to S. hermonthica management in Burkina Faso to guide breeding and production, (ii) screen pearl millet genotypes for resistance to S. hermonthica and compatibility with a biocontrol agent, FOS, in the Sahel to select contrasting and promising parents for resistance breeding and production, (iii) determine the genome-wide association analyses of agronomic traits and S. hermonthica resistance in pearl millet to identify genetic markers for marker-assisted breeding and trait introgression, (iv) determine the generation mean analysis of S. hermonthica resistance in pearl millet to guide selection, genetic advancement and variety development, and (v) determine the combining ability effects and the response of pearl millet genotypes for agronomic traits and S. hermonthica resistance for selecting superior parents and hybrids.
The first study employed a participatory rural appraisal (PRA) and was conducted in the Sahel and Sudano-Sahelian zones of Burkina Faso, involving 492 farmers to document farmers’ perceptions of the prevailing constraints affecting pearl millet production and related approaches to manage S. hermonthica. Recurrent drought, S. hermonthica infestation, shortage of labour, lack of fertilisers, lack of cash, and the use of low-yielding varieties were the main challenges hindering pearl millet production and productivity in the study areas. The study revealed a high population growth rate in rural areas, with 40% of respondents reporting families of up to 20 individuals per household. The majority of the respondents (40%) ranked S. hermonthica infestation as the primary constraint affecting pearl millet production, with yield losses of up to 80%. About 61.4% of the respondents in the study areas had achieved mean pearl millet yields of < 1.00 ton ha-1. Poor access, the high cost of improved seed, and a lack of farmers’ preferred traits in the existing improved pearl millet varieties were the main reasons for their low adoption, as 32% of respondents reported. S. hermonthica management options in pearl millet production fields included moisture conservation using terraces, manual hoeing, hand weeding, use of micro-plots locally referred to as ‘zaï’, crop rotation and mulching. These management techniques were ineffective because they do not suppress the below-ground S. hermonthica seed and are difficult to implement. Integrated management practices employing breeding for S. hermonthica-resistant varieties with the aforementioned control measures could offer a sustainable solution for Striga management and improved pearl millet productivity in Burkina Faso.
The second study evaluated 150 pearl millet genotypes in S. hermonthica hotspot fields in rain-fed and greenhouse conditions using a 10 × 15 alpha lattice design in two replications in Burkina Faso. Significant differences were recorded among the tested pearl millet genotypes for the assessed agro-morphological and Striga resistance traits. Days to flowering were significantly delayed due to S. hermonthica infestation. Applying FOS on pearl millet seed significantly reduced the mean emerged Striga number in S. hermonthica-infested conditions. IP-3098, IP-6112, IP-9242, IP-10579, and IP-11358 were identified exhibiting S. hermonthica resistance and were compatible to FOS. The pearl millet genotypes supported few to none S. hermonthica emerged plants and had relatively low values under the Area under Striga Number Progress Curve (ASNPC). The selected genotypes are useful parents for breeding and integrated Striga management in Burkina Faso and related agro-ecologies.
In the third chapter, 150 pearl millet genotypes were assayed in genome-wide association analyses study for agronomic and S. hermonthica resistance traits to identify genetic markers for marker-assisted breeding and trait introgression. 256 K single nucleotide polymorphisms (SNPs) were used in the study. Significant differences (P < 0.001) were detected among the assessed pearl millet genotypes for S. hermonthica parameters and agronomic traits. Further, there were significant genotype by S. hermonthica interaction for the number of S. hermonthica and ASNPC. Twenty-eight SNPs were significantly associated with a low number of emerged S. hermonthica located on chromosomes 1, 2, 3, 4, 6, and 7. Four SNPs were associated with days-to-50%-flowering on chromosomes 3, 5, 6, and 7, while five were associated with panicle length on chromosomes 2, 3, and 4. Seven SNPs were linked to thousand-grain weight on chromosomes 2, 3, and 6. The putative SNP markers associated with a low number of emerged S. hermonthica and agronomic traits in the assessed genotypes are valuable genomic resources for accelerated breeding and variety deployment of pearl millet with Striga resistance and farmer-and market-preferred agronomic traits.
The fourth study determined the gene action and inheritance of S. hermonthica resistance in newly developed pearl millet populations to guide selection and genetic advancement. Bi-parental crosses were derived from contrasting pairs of Striga-resistant/Striga-susceptible of pearl millet lines. Two sets of parental lines and their subsequent F1s, F2s, and backcross generations were evaluated under greenhouse and S. hermonthica infested field conditions using a randomised complete block design with three replications. The analysis of variance showed significant (P < 0.001) differences among the generations across sets for Striga parameters. Striga resistance is quantitatively inherited and governed by multiple genes. Duplicate gene action controlled the inheritance of the number of emerged S. hermonthica. Unique F2 individuals with S. hermonthica resistance were selected from the two sets for genetic advancement through recurrent selection method for pearl millet variety development by integrating desirable agronomic and farmer-preferred traits.
The last study assessed the combining ability effects of pearl millet genotypes for S. hermonthica resistance and agronomic traits. The analysis of variance for combining ability effects showed significant (P < 0.01) differences among parents for days to flowering, panicle diameter, and grain yield. The difference between lines and testers were significant (P < 0.001) for panicle length and the number of emerged Striga. The genotype IP-11358 had high and positive general combining ability (GCA) effects (158.99) for grain yield. Negative GCA effects of -6.99, -6.40, and -134.08 were recorded for Striga count 60 days after planting, Striga count 80 days after planting, and ASNPC in that order for genotype IP-11358 in the greenhouse under S. hermonthica conditions. The hybrid IP-11358 × ICMB177111 displayed a higher specific combining ability (SCA) effect and standard heterosis for grain yield. The selected pearl millet genotypes are suitable for breeding high-yielding and Striga-resistant open-pollinated and hybrid varieties for Striga-prone areas in Burkina Faso and related agro-ecologies of sub-Saharan Africa.
Overall, the study identified S. hermonthica as the most critical pearl millet production constraint in Burkina Faso. Also, the study highlighted significant genetic diversity among 150 genotypes for S. hermonthica resistance when assessed using economic traits and SNP markers under Striga hotspot areas. Best-performing genotypes such as IP-3098, IP-6112, IP-9242, IP-10579 and IP-11358 were selected as suitable parents for S. hermonthica resistance breeding. The family IP-11358 × ICMB177111 was identified as having high-yielding and Striga-resistance. The selected genotypes are recommended for production and as donor parents for new population improvement in pearl millet Striga resistance breeding.
Iqoqa
Amabele, iPearl millet (Pennisetum glaucum [L.] R. Br. 2n = 2x = 14) angolunye lohlobo lwamabele osanhlamvana atshalwa ezindaweni ezisalugwadule ezisemazansi ne-Afrika kanye nase-India, asetshenziswa izinkulungwane ngezinkulungwane zemindeni kanye nosomabhizinisi abaningi basezifundeni nezifundazwe ezahlukene. Amabele lawa yikhona kudla okujwayelekile okudliwayo eBurkina Faso, atshalwa kakhulu ezindaweni zaseSahelian naseSudano-Sahelian, ezaziwa ngokuba nomhlabathi ongemuhle kahle nezimvula ezingani njalo kanye nokushisa okukhulu. Nokho, ukutshalwa kwamabele, ipearl millet e-Afrika, kufaka neBurkina Faso, kuthikanyezwa ukhula oluyimpilangokunye iStriga hermonthica (Del.) [iBentham], nezinyoni ezilimaza amabele, amaqhuqhuva amila emacembeni, imiswenya, nokungajwayeli kahle indawo. Ukutshalwa kwamabele epearl millett akwazi ukubekezela, iS. Hermonthica, nasezindaweni ezisagwadule, kuye ngezimfuno zomlimi nabamabhizinisi, kungathuthukisa isivuno esihle nokugcineka okuhle kwemikhiqizo. Ngakho-ke, inhlosongqangi yalolu cwaningo bekuwukuthuthukisa ukukhiqizwa kwamabele, ipearl millet eBurkina Faso ngokukhiqiza izinhlobo ezahlukene zepearl millet ezikwazi ukubekezela ngokweStriga, zivumelane nokusetshenziswa kwezivikeli iFusarium oxysporum f.sp. Strigae (FOS) futhi ziphile ngaphansi kwesimo sezulu sendawo. Inhloso yocwaningo bekuyilena: (i) ukucubungula izinkinga ngokukhiqizwa kwamabele, ipearl millet kanye nezindlela ezisetshenziswa ngabalimi ukulawula iS. Hermonthica eBurkina Faso ukunikeza umhlahlandlela ngokutshalwa nokukhuliswa, (ii) ukucubungula izinhlobo zepearl millet nokubekezela kweS. hermonthica kanye nokuvumelana namakhemikhali, i-FOS, ekukhethweni kwemikhiqizo ekwazi ukubekezelela izimo ezahlukene, (iii) ukubheka ufuzo olujwayelekile kanye nokubekezelela izimo kwepearl millet yeS. hermonthica ukubheka izinto ezijwayelekile ekukhiqizweni nokukhula kwamabele, (iv) ukuhlonza izindlela zokukhiqiza nokukwazi ukubhekana nezimo kwepearl millet, iS. Hermonthica ukuze kube nomhlahlandlela wokukhetha, ukuthuthuka okujwayelekile kanye nokuthuthuka, futhi (v) ukubheka ukuhlangana kwamandla nokwamukela ukwakheka kofuzo lwepearl millet nokubekezela kweS. hermonthica ukukhetha indawo enamandla nohlobo oluqhamuka kokungafani.
Ucwaningo lokuqala lwalusebenzisa indlela egxile kumbambiqhaza wasemakhaya, iparticipatory rural appraisal (PRA) ezindaweni zaseSahel naseSudano-Sahelian eBurkina Faso, kuhlanganisa abalimi abangama-492 ukuthola izimvo zabo mayelana nezinkinga eziqhubekayo ezimayelana nokukhiqizwa kwepearl millet nezindlela zokulawulwa neS. hermonthica. Ukuphindaphinda kwezikhawu zesomiso, ukuhlasela kweS. hermonthica, ukuntuleka kwezisebenzi, kukamanyolo, kwemali, nokusetshenziswa kwezinhlobo ezingekho ezingeni, yikhona okuba nomthelela ongemuhle ekukhiqizweni kwepearl millet kulolu cwaningo. Lolu cwaningo luveze ukwenyuka kwesibalo sabantu ezindaweni zasemakhaya, amaphesenti angama-40 ababambiqhaza bocwaningo baveza ukuthi umuzi ngamunye cishe unamalungu angama-20 ekhaya elilodwa. Iningi lababambiqhaza (40%) liveze ukuthi ukuhlasela kweS. hermonthica kuyimbangela enkulu ebhekene nokukhiqizwa kwepearl millet, okwenza kube nokulahleka kwenzuzo ngamaphesenti angama-80. Cishe amaphesenti angama-61.4 ababambiqhaza bocwaningo avune isivuno esincane sepearl millet esiyi < 1.00 ton ha-1. Ukutholakali kalula, ukubiza kakhulu kwembewu ethuthukisiwe, kanye nokungabi nolwazi olwanele lwabalimi ngokufunakalayo mayelana nezinhlobo ezithuthukisiwe zepearl millet ngezinye zezizathu ezinqala ezenza kungabi lula ukujwayela, njengoba kubike ababambiqhaza abangamaphesenti angama-32. Ezinye zezindlela zokulawula iS. hermonthica emasimini epearl millet kufaka ukugcinwa komswakama kusetshenziswa indlela yokwenza amasimu angahlali, ukulima ngezandla, ukuhlakula ngezandla, ukusebenzisa amaploti amancane, abizwa ngokuthi i‘zaï’, ukushintshashintsha izitshalo nokwemboza izitshalo zingashiswa yilanga. Lezi zindlela azikwazanga ukuza nemiphumela emihle ngoba zazingakwazi ukulwa nembewu yeS. hermonthica ngaphansi komhlabathi kanti futhi kwakuwumsebenzi ukuzenza. Indlela eyinhlanganisela yokulawula ukuzaleka kwezinhlobo ezahlukene zokubhekana neS. Hermonthica kanye nezindlela ezibalulwe ngenhla kungaletha isisombululo esingasebenza isikhathi eside ekulawulweni kweStriga nasekukhiqizweni kwepearl millet eBurkina Faso.
Ucwaningo lwesibili luhlaziye izinhlobo eziyi-150 zepearl millet emasimini ehlaselwe kakhulu yiS. hermonthica esimweni sezimvula kanye nobuluhlaza kusetshenziswa indlela yokukala, i-alpha lattice design, wesikalo esiyi-10 × 15 kabili ngokufanayo eBurkina Faso. Kwatholakala umahluko omkhulu kakhulu ezinhlotsheni zepearl millet kulezo ezahlolwa ukubumbeka kokubekezela kweStriga. Izinsuku zokuqhakaza kwezimbali kwabambezeleka kakhulu ngenxa yokuhlasela kweS. hermonthica. Ukusebenzisa i-FOS embewini yepearl millet kwehlisa ngamandla amakhulu ukuvela kweStriga ezimbewini ezine-S. hermonthica. I-IP-3098, i-IP-6112, i-IP-9242, i-IP-10579, ne-IP-11358 kwabonakala kulwa neS. hermonthica futhi kuhambisana ne-FOS. Izinhlobo zepearl millet zakwazi ukubhekelela izitshalo ezimbalwa ezingenayo iS. hermonthica kanti akubanga nasizo olutheni ezindaweni ezineStriga Number Progress Curve (ASNPC). Izinhlobo ezikhethiwe zinikeza indawo enhle yokukhiqiza futhi indlela ehlangene yokulawula iStriga ingaba usizo eBurkina Faso kwezolimo.
Esahlukweni sisithathu, izinhlobo eziyi-150 zepearl millet zahlolwa izinga lazo ocwaningweni oluhlola ufuzo olwakha izifo ezitshalweni kanye nokubekezela kweS. hermonthica ukubheka izinto eziveza ufuzo kulokho okwakhiwe ukuveza ufuzo kanye nokuqhubeka kwalo. Ama-256 K esingle nucleotide polymorphisms (SNPs) asetshenziswa kulolu cwaningo. Umehluko omkhulu (P < 0.001) wabonakala ezinhlobeni ezahlolwa zepearl millet maqondana nezikalo nofuzo kweS. hermonthica. Okunye, kwaba khona ukuhlangana phakathi kwezinhlobo ezahlukene zofuzo lweS. Hermonthica ne-ASNPC. Ama-SNP angamashumi amabili nesishiyagalolunye ayamaniswa nenombolo ephansi yokwakheka kweS. hermonthica kumakhromozomu 1, 2, 3, 4, 6, no-7. Ama-SNP amane ayamaniswa nezinsuku kuya kumaphesenti angama-50 okuthela izimbali namakhromozomu 3, 5, 6, no-7, kanti ayisihlanu wona ayamaniswa namakhromozomu 2, 3, no-4. Ayisikhombisa wona ayamaniswa namagatsha amakhromozomu ayi-2, 3, no-6. Okujwayelekile okukhombisa iSNP okuyamaniswa nobuncane beS. hermonthica kwavela kanye nokuphathelene nokulima ezinhlobeni ezahlukene zofuzo ekutshalweni nokukhiqizwa kwepearl millet ngokubekezela kweStriga nabalimi kanjalo nokufunwa ngabathengi kwezokutshala.
Ucwaningo lwesine lwaveza ukusebenza kofuzo nobukhona bokuzabalaza kweS. hermonthica okolweni omusha wepearl millet ukulawula ukukhethwa kanye nokukhula kofuzo. Izinhlobo ezimbili ezakhiwe ezingafani zavela ekuzabalazeni kweStriga yepearl millet. Izinhlobo ezimbili ezakhiwe kanye nemixhantela ye-F1s, i-F2s, neminye eyakhiwe kuhlanganiswe nofuzo kwahlolwa ngaphansi kokukhula kohlaza namasimu afakwe iS. hermonthica kusetshenziswa indlela yokwenza engahleliwe kuzona zontathu izinhlobo. Ukuhlaziywa kwezinhlobo ezahlukene kwaveza umehluko omkhulu we-P < 0.001 kuzona zonke izinhlobo ezakhiwe zeStriga. Ukuzabalaza kweStriga kubonakala kuzenzakalela ngokwemvelo futhi kulawulwa izinhlobo eziningi ezahlukene zofuzo. Ukuphindaphinda ufuzo kabili kwalawula ukuvela ngokwemvelo kweS. hermonthica. Izinhlobo eziyikhethelo ze-F2 ezinokuzabalaza kweS. hermonthica zakhethwa ofuzweni olubili kusetshenziswa indlela yokubheka ukuphindeka kwento ukuhlola izinhlobo zepearl millet ngokuhlanganisa izindlela zokulima nezokufuna uhlobo oluthize lwesitshalo.
Ucwaningo lokugcina beluhlola amandla ahlangisiwe ofuzo lwepearl millet lokulwa kweS. hermonthica kanye nobunjalo bezokutshala. Ukuhlaziya izinhlobo zamandla okukwazi okuhlangane kwaveza umehluko omkhulu ka-P < 0.01 kulezo zinhlobo ezikwazi ukuthwala ezinye ngezinsuku ezimbalwa ngaphambi kokuqhakaza kwezimbali, ukukala ukukhula ngobude, kanye nokuphuma kwezinhlamvu.
Umehluko phakathi kwemigqa nezinto zokuhlola wawumkhulu (P < 0.001) ukubheka ukukhula ngobude kanye nesibalo seStriga. Ufuzo lwe-IP-11358 lwakhombisa ukuba namandla aphezulu okuhlangana (GCA) okunemiphumela (158.99) kokuphuma kwezinhlamvu. Imiphumela engemihle ye-GCA eyi-6.99, i-6.40, no-134.08 yatholakala yeStriga emuva kwezinsuku ezingama-60 kutshaliwe, neyeStriga emuva kwezinsuku ezingama-80 kutshaliwe, ne-ASNPC ngokulandelana kwezinhlobo zofuzo lwe-IP-11358 lohlaza ngaphansi kwezimo zeS. hermonthica. Ingxubevange ye-IP-11358 × ICMB177111 yaveza amandla amakhulu okudibanisa (SCA) kanye nokuhluma kwezinhlamvu okuxubile. Izinhlobo zofuzo ezikhethiwe zepearl millet zikulungele ukukhiqiza ngendlela esezingeni eliphezulu kanye nokuzabalaza kweStriga esilekelelwa izinyosi ukuze kuqhakaze kanye nengxubevange yeStriga ngokwezindawo ezahlukene eBurkina Faso nezindawo ezitshala amabele emazweni asemazansi ne-Afrika.
Sekukonke, lolu cwaningo lukwazile ukuveza ukuthi iS. hermonthica iyona enamandla amakhulu okudicilela phansi ukutshalwa kwepearl millet eBurkina Faso. Kanti futhi lolu cwaningo lukwazile ukuveza izinhlobo ezahlukene zofuzo oluyi-150 lokuzabalaza kweS. hermonthica uma kuhlolwa kusetshenziswa ukunyakaza komnotho ne-SNP ngaphansi kwezindawo ezigcwele iStriga. Izinhlobo ezenza kangcono zofuzo ezifana ne-IP-3098, i-IP-6112, i-IP-9242, i-IP-10579 ne-IP-11358 kwakhethwa njengesizinda esihle sokuzabalaza kweS. hermonthica uma yakhiwa. Uhlobo lwe-IP-11358 × ICMB177111 lwahlonzwa njengolunamandla amakhulu okukhula kanye nokulwa kweStriga. Izinhlobo ezikhethiwe zofuzo zinconywa njengezifanelekile emkhiqizweni futhi njengesizinda esihle sokufukamela umkhiqizo omusha wokuzabalaza kwepearl millet Striga
Breeding groundnut (arachis hypogaea L.) for rust resistance in Tanzania.
No full textDoctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.Abstract available in pdf
Genetic analysis and hybrid prediction in tropical maize (Zea mays L.) using phenotypic and single nucleotide polymorphic markers.
No full textDoctoral Degree. University of KwaZulu-Natal, PietermaritzburgMaize (Zea mays L., 2n = 2x = 20) is a commodity crop serving the food, feed, and processing industries globally. The productivity of maize in Africa remains low (< 2 t/ha) due to various yieldlimiting factors, including abiotic stresses (such as drought, heat stress, flooding, waterlogging, erosion and poor soil health), and biotic stresses (e.g. foliar diseases and insect pests). Limited adoption of new high yielding varieties, slow rate of varietal turnover , socio-economic constraints, and policy issues further hinder productivity. Seed Co Limited is a Pan-African seed company involved in the research, development, and commercialization of seeds of major food security grain crops, including maize. The Seed Co breeding program aims to enhance the yields of new generation maize cultivars via hybrid breeding by utilizing complementary and contrasting inbred lines. New lines and experimental hybrids are developed and phenotyped using economic agronomic traits and genotyped using high-resolution Single Nucleotide Polymorphism (SNP) markers to facilitate effective selection. Integrating phenotypic and genomic selection accelerates the development of inbred lines with desirable traits to create high-performing single crosses and three-way hybrids. The new hybrids should undergo rigorous field testing for yield gains and stability across various locations to guide cultivar release and commercialization. Therefore, to complement this breeding initiative, the objectives of the study were: to assess a maize germplasm panel's genetic diversity and population structure comprising 182 founder lines and 866 derived inbred lines using Single Nucleotide Polymorphism (SNP) markers to identify genetically unique lines for hybrid breeding, to conduct genome-wide prediction of yield and component traits using qualitative and quantitative phenotypic traits and SNP markers based on the additive-dominant genomic best linear unbiased predictions model to compute genomic estimated breeding values and genomic estimated genetic values to guide inbred line development and hybrid breeding, to assess the gains in yield and yield components among single cross maize hybrids selected through genomic prediction across representative locations to guide breeding and production and to determine the combining ability effects of newly selected inbred lines and quantify the magnitude of heterosis and genotype by environmental interaction (GEI) effects of single cross hybrids to select and recommend contrasting elite lines and experimental hybrids.
In the first study, 182 founder and 866 derived maize inbred lines were characterized for genetic diversity and population structure analyses using SNP markers to identify genetically unique lines for hybrid breeding through beneficial allelic combinations. Genotyping was performed using the Affymetrix platform for the 182 founder lines (1201 SNP markers) and the Midseq platform for the 866 derived lines (1484 markers). Moderate genetic variation with genetic distance ranging from 0.004 to 0.44 (mean: 0.25) for founder lines and 0.004 to 0.34 (mean: 0.13) for derived lines was observed. Heterozygosity values ranged from 0.00 to 0.24 for both lines. About 82% of the 1201 markers and 84% of the 1484 markers exhibited polymorphism information content ranging from 0.25 to 0.50, detecting a high level of genetic diversity and that the SNPs were highly informative in distinguishing the tested lines. Analysis of molecular variance revealed significant genetic differences (P ≤ 0.001) among and within populations in the founder and derived lines. Notably, within-population variations accounted for 97% (founder lines) and 88.38% (derived lines) of the detected variations. Population structure analysis identified three subpopulations among founder lines and two among derived lines, which was supported by cluster analysis. Based on pairwise comparisons, genetically distant lines were selected, including G15NL337 and G15NL312 (Cluster 1), 15ARG152 and RGS-PL44 (Cluster 2), RGS-PL44 and 15ARG149 (Cluster 2), and RGS-PL33 and RGS-PL44 (Cluster 2). The selected lines are genetically distinct and recommended for marker-assisted hybrid maize breeding to leverage beneficial alleles.
The second study genotyped 1,102 genetically diverse inbred lines from two heterotic groups (N3 and SC) using high-density SNP markers. The 1,102 lines and 4 testers were crossed in a line-by-tester design to generate 2,830 single cross hybrids (SCHs). Phenotypic data were collected from field trials with the following SCHs: 684 evaluated at five locations in 2018/19, 760 at four locations (2019/20), 646 at four locations (2020/21), and 740 at four locations (2021/22) summer seasons in Zimbabwe. The trials were laid out in a 6 x 7 alpha lattice design with two replications at each site. 20 highperforming and contrasting inbred lines with the highest genomic estimated breeding values (GEBVs) and genomic estimated genetic values (GEGVs), each from the two heterotic groups, were identified for genetic advancement, combining ability tests and commercial hybrid development. 20 highperforming candidate SCHs with high GEGVs were identified for three-way hybrid development, variety registration and commercialization.
In the third study, 30 SCHs were developed from 11 inbred lines (6 from the N3 group and 5 from the SC group) with the highest predicted GEGVs for grain yield and associated traits using the genotypic best linear unbiased prediction (GBLUP) model. The lines were crossed using a factorial mating design with the six N3 lines used as female and five SC lines as male. The derived 30 SCHs and six commercial single cross check hybrids were field evaluated in seven locations, four in Zimbabwe and three in Zambia using a 6 x 6 alpha lattice design with two replications at each location. A combined analysis of variance revealed significant (P≤0.05) variation among the hybrids for the assessed 11 quantitative traits. Significant yield gains were realized over the mean of checks (at 13.09%), mean of the population (10.83%) and mean of best check (1.47%). Moderate to high broad-sense heritability (50 to 94%) and genetic advance were recorded for most of the assessed traits, indicating the success of selection assisted by genomic predictions. The study identified three best single cross hybrids (i.e., CTL03 x G16NL721, CTL03 x G17NL544 and GS-PL07 x G17NL544) with high and stable yields and recommended for commercialization.
In the fourth study, 11 elite inbred lines (6 female parents from N3 and 5 male parents from SC group) were crossed using a factorial mating design, resulting in 30 SCHs. The lines were selected based on the highest GEGVs for yield and component traits through GS using the GBLUP model. The 30 SCHs and six commercial check hybrids were field evaluated at seven locations (four in Zimbabwe and three in Zambia) during the 2022/2023 summer season. The trials were arranged in a 6 x 6 alpha lattice design with two replications at each location. Data were recorded on yield and yield components, and general combining ability (GCA) and specific combining ability (SCA) effects were computed. Significant GCA effects for grain yield (GY) were noted for lines CTL03, G17NL544, G16NL721, and GS-PL07, while significant SCA effects were recorded for crosses 15AG163 x G16NL679, G15NL304 x G17NL642, and 15AG162 x G16NL679. The additive main effects and multiplicative interaction (AMMI) model explained 38.95%, 50.58% and 7.24% of the total variation in GY due to genotype (G), environment (E), and genotype x environment interaction (GEI) effects in that order. The test locations were clustered into two mega environments: Rattray Arnold Research Station (RARS), Agricultural Research Trust (ART), Mpongwe Research Station (MPRS), and Lusaka West Research Station (LWRS) (Environment 1), and Mkushi Research Station (MKRS), Stapleford Research Centre (STAP), and Kadoma Research Centre (KRC) (Environment 2). The genotype and genotype-by-environment interaction (GGE) biplot analysis identified hybrids G15NL304 x G17NL544 and 15AG162 x G17NL544 as high-yielding and stable, suitable for commercialization. The two mega-environments and the selected stable, high-yielding general and specific combiners are recommended for genotype evaluation and production in Zimbabwe, Zambia, and comparable agroecologies.
Overall, the present study identified contrasting and genetically delineated inbred lines and enhanced the existing heterotic groups using high-throughput SNP markers. Best-performing lines (e.g. CTL03 and GS-PL07) were selected from the N3 heterotic group and G17NL544 and G16NL721 from the SC heterotic group. New single cross hybrids, such as CTL03 x G16NL721, CTL03 x G17NL544, and GS-PL07 x G17NL544, were selected with grain yields of 8.38 t/ha, 8.24 t/ha, and 8.23 t/ha, respectively. The new experimental hybrids are recommended for three-way hybrid development or release following multi-environment evaluation
Genetic analysis of stem rust resistance among Ethiopian grown wheat lines.
No full textPh. D. University of KwaZulu-Natal, Pietermaritzburg 2014.Wheat (Triticum aestivum L.) is one of the major food crops in the world. Ethiopia is
the second largest wheat producer in sub-Saharan Africa. However, wheat
production in Ethiopia is constrained by many biotic and abiotic factors, and socioeconomic
constraints. Among the biotic stresses are the rust diseases: stem rust
caused by Puccinia graminis f.sp. tritici, leaf rust (P. triticina Eriks) and stripe rust (P.
striiformis Westend. f.sp. tritici)). Stem rust is considered to be the most destructive
disease of wheat in the main wheat growing regions of Ethiopia. Losses may reach
100% on susceptible wheat cultivars when conditions are favorable for disease
development. Use of resistant cultivars is the most effective, economical and
environmentally safe control measure, especially for the resource poor farmers. Due
to the frequent emergence of new stem rust races through mutation, migration and
recombination of exsisting virulence genes, efforts to identify potentially new
sources of effective resistance genes are of the highest importance followed by their
incorporation into a desirable genetic background.
The objectives of the study were 1) to identify the primary threats to wheat
production, farmers’ selection criteria for wheat varieties, and disease management
practices with emphasis on wheat rusts in the Arsi, Bale and West Shewa
administrative zones of Ethiopia; 2) to identify possible sources of stem rust
resistance among Ethiopian wheat lines; 3) to determine the levels of heterosis and
combining ability, and to identify the best parents and crosses for breeding to stem
rust resistance, high grain yield and desirable agronomic traits; 4) to
introgress durable resistance genes from known resistance sources into farmers’-
preferred and locally adapted but stem rust susceptible, improved wheat varieties.
A participatory rural appraisal (PRA) research was conducted involving 270 farmers
in six districts of three administrative zones in Ethiopia. The participating farmers
listed and prioritized their wheat production constraints. Wheat rust diseases, the
high costs of fertilizers, lack of access to seeds of improved varieties and high seed
prices were the major constraints reported by the respondents. The most important
traits that farmers sought in wheat varieties were disease resistance and high grain
yield. Estimated yield losses due to stem rust disease were more than 60% in all the
surveyed areas. Fungicide application was the main disease management practice
used by the majority of respondent farmers.
Field and greenhouse experiments were conducted to identify possible sources of
stem rust resistance among Ethiopian wheat lines. Two hundred fifty two wheat
genotypes were evaluated for their resistance to stem rust at the seedling stage.
Ninety one lines that exhibited intermediate and susceptible seedling reactions were
field tested for their slow rusting characteristics. Among the 91, 38 lines that had
high to moderate level of slow rusting were advanced to further field evaluation. Ten
lines (H04-2, 204408-3, 214551-1, 231545-1, 7041-1, 7514-1, 226385-1, 226815-1,
7579-1, and 222495-1) were identified as good slow rusting lines while seven
(237886-1, 227059-1, 203763-1, 226275-1, 227068-2, 226278-1 and 7994-1) were
identified as moderately slow rusting lines.
Fifteen wheat hybrids were developed through a half diallel mating design involving
six parents. The F1’s and their parents were field evaluated for their stem rust
reaction and agronomic performances at the Debere-Zeit Agricultural Research
Center in Ethiopia, which is a well known hot spot area for stem rust. The analysis
of variance revealed that tested genotypes had considerable genetic variability for
all characters studied. The maximum positive mid-parent (31.45%) and betterparent
heterosis (25.38%) were observed for grain yield. Plant height and days to
maturity had maximum negative mid-parent heterosis levels of -11.01% and -8.02%,
respectively. The majority of the crosses expressed negative heterosis over their
mid-parent for AUDPC, indicating these crosses manifested resistance against stem
rust. Significant general combining ability (GCA) effects were observed for all the
characters studied. Furthermore, significant specific combining ability (SCA) effects
were detected for most of the traits. Non-additive gene action was predominant for
grain yield, thousand kernel weight and plant height. Additive gene action played a
greater role in the inheritance of AUDPC, kernels per spike, number of tillers per
plant and days to maturity. The study identified parental lines with good GCA effects
for most of the characters, especially H04-2, Digelu and Danda’a. Crosses 231545-
1 x H04-2, 7041-1 x H04-2, Digelu x Kubsa and Danda’a x Kubsa had significantly
negative SCA effects for AUDPC. Progenies of these crosses will be selected in an
ongoing stem rust resistance breeding program. In general, H04-2 and Danda’a
were good general combiners for most of the important studied characters. Crosses
that involved these lines performed well for most of the traits. Hence, Lines H04-2
and Danda’a could be exploited in wheat breeding programs to develop stem rust
resistant and high yielding wheat cultivars.
Stem rust resistance genes were introgressed into locally adapted, high yielding
susceptible wheat varieties, Kubsa (HAR1685) and Galama (HAR604), from two
sources of adult plant resistance, Pavon 76 and Kenya Plume, using the single
backcross-selected bulk breeding approach. The resistance sources were crossed
with the adapted high yielding varieties and a single backcross was made with the
recurrent parent. The resulting BC1 populations were selfed until the F3. Bulk
selection was practiced from BC1- F3. The F3 populations, along with the recurrent
parents, were evaluated in a replicated trial at Debre-Zeit Agricultural Research
Center under high stem rust pressure to determine the genetic improvement
attained in the populations for stem rust resistance and agronomic traits. All F3
populations, except the cross of Galama x Kenya Plume, were better performing for
stem rust resistance and most agronomic traits studied when compared to the
recurrent parents. The F3 progenies of Kubsa x Pavon 76 had superior mean
values and high genetic gains for most agronomic attributes and stem rust
resistance. These progenies will be advanced and selected in subsequent
generations to develop locally adapted pure line wheat varieties with improved stem
rust resistance and farmers’-preferred agronomic traits.
Overall, the present study attempted to understand farmers’ wheat varietal
preferences, farmers’ wheat production constraints, identified slow rusting wheat
lines among the Ethiopian bread wheat germplasm, identified promising lines and
F1 hybrids with good combining ability for breeding towards stem rust resistance
and high yields. Durable stem rust resistance genes were incorporated into locally
adapted susceptible wheat varieties for further selection and future release to
enhance wheat productivity in Ethiopia
Genetic enhancement of sorghum for yield-related traits and drought tolerance through induced mutagenes.
No full textDoctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.Sorghum (Sorghum bicolor [L.] Moench) is the foundation crop in the world's dry regions, for
food, feed, and bioenergy feedstock. There has not been a systematic breeding program and
farmers-preferred varieties of the crop in Namibia due to several constraints. There is a need
to develop high-yielding and farmer-preferred sorghum varieties with drought-adaptive traits
to boost sorghum productivity in the country. The overall goal of this study was to contribute
to the national sorghum breeding program aimed at improving sorghum production and
productivity through the development and deployment of climate-smart cultivars preferred by
farmers and markets in Namibia via induced mutagenesis. The specific objectives of the study
were: (1) to assess the present state of sorghum production in northern Namibia and
document farmers’ perceived production constraints and trait preferences in new varieties to
guide drought-tolerance breeding; (2) to determine the optimum doses of a single and
combined use of gamma radiation and ethyl methanesulfonate (EMS) for effective mutation
breeding in sorghum; (3) to determine the genetic profile of elite sorghum lines developed via
gamma radiation using diagnostic simple sequence repeat (SSR) markers and phenotypic
traits for selection; and (4) to determine the Genotype by environment interaction (GEI) of
newly-developed mutant and traditional sorghum lines for grain yield and yield related traits
for drought-prone areas of Namibia.
In the first study, a survey was conducted using a participatory rural appraisal in the following
six selected sorghum-growing constituencies: Kapako and Mpungu (Kavango West Region),
Eenhana and Endola (Ohangwena Region), and Katima Mulilo Rural and Kongola (Zambezi
Region). Data were collected using a structured questionnaire involving 198 farmers in 14
sampled villages across the regions. An equal proportion of male and female respondent
farmers cultivate sorghum, suggesting the value of the crop to both genders in Namibia. Most
respondent farmers (63.6%) were in productive age groups of <40 years old. In the study
areas, low-yielding landrace varieties, namely Ekoko, Okambete, Makonga, Kamburo, Nkutji,
Katoma, Fuba, Dommy, Kawumbe, and Okatombo, were widely cultivated, and most of the
farmers did not use chemical fertilizers to cultivate sorghum. Farmers’ perceived sorghum
production constraints in the study areas included recurrent drought, declining soil fertility,
insect pest damage, high cost of production inputs, unavailability of improved seed, lack of
alternative improved varieties with farmers’ preferred traits, lack of organic manure, limited
access to market and limited extension service. The key farmers’ preferred traits in a new
sorghum variety included high grain yield, early maturity, and tolerance to drought and storage
pests. The study recommends genetic improvement and new variety deployment of sorghum
with the described farmers-preferred traits to increase the sustainable production of the crop
in Namibia.
In the second study, two concurrent experiments were conducted as follows: in experiment I,
the seeds of four sorghum genotypes (Parbhani Moti, Parbhani Shakti, ICSV 15013, and
Macia) were treated using five gamma radiation doses (0, 300, 400, 500 and 600 Gray [Gy]),
and three EMS doses (0, 0.5 and 1.0%), and gamma radiation followed by EMS (0 and 300
Gy and 0.1% EMS; 400 Gy and 0.05% EMS). In experiment II, the seeds of two sorghum
genotypes (Macia and Red sorghum) were treated with only seven doses of gamma radiation
(0, 100, 200, 300, 400, 500 and 600 Gy). The combined applied doses of gamma radiation
and EMS are not recommended due to poor seedling emergence and seedling survival rate
below LD50. The best dosage of gamma radiation for genotypes Red sorghum, Parbhani Moti,
Macia, ICSV 15013 and Parbhani Shakti ranged between 392 and 419 Gy, 311 and 354 Gy,
256 and 355 Gy, 273 and 304 Gy, and 266 and 297 Gy, respectively. The optimum dosage
ranges of EMS for genotypes Parbhani Shakti, ICSV 15013, Parbhani Moti and Macia were
between 0.41% and 0.60%, 0.48% and 0.58%, 0.46% and 0.51%, and 0.36% and 0.45%,
respectively. The above dose rates are useful for induced mutagenesis and creating genetic
variation in the tested sorghum genotypes for breeding programs.
In the third study, 20 mutant lines (which were at mutation generation 7 [M7]) were developed
using gamma-irradiation at 350 Gy from the seed of the variety Macia (SDS 3220). Also, five
check varieties were used for the comparative study. DNA extraction was carried out on young
and fresh leaves samples per test line 20 days after sowing. Seventeen SSR markers
amplified a total of 50 alleles, which varied from 2 to 5 (mean = 2.94). The number of effective
alleles per locus varied from 1.08 to 2.53, with a mean of 1.96. The observed heterozygosity
ranged from 0.00 to 0.21 (mean = 0.09). The mean expected heterozygosity value was 0.45
indicating moderate genetic differentiation of the tested lines for selection and hybridization.
Cluster analysis classified the genotypes into three main groups. Moderate to high genetic
distance (≥ 0.50) was displayed between drought-tolerant and high-yielding genotypes that
aided in selecting mutant lines such as ‘ML2, ML3, ML4, ML7 and ML14’ compared with the
check varieties ‘Macia, Kotovara, ICSR 137, and ICSV 17004’. The selected lines are a useful
source of genetic variation for breeding high-yielding and drought-tolerant varieties suited for
the drought-prone environments of Namibia.
In the fourth study, 50 sorghum genotypes, including 10 newly-developed mutant lines (M9),
33 landraces, two sorghum varieties widely grown in Namibia, and five standard check
varieties were evaluated under field conditions using a 10 x 5 alpha lattice design with three
replications. The experiments were carried out in four environments with two growing seasons
in Namibia. Data were collected on grain yield and related traits and subjected to the Additive
Main Effects and Multiplicative Interaction (AMMI) model. The AMMI model showed that
93.9% of the total genetic variation was attributed to days to 50% flowering (DF), while 94.04%
of the variation was due to plant height (PH), 86.52% to panicle weight (PW), 70.67% to
thousand-grain weight (TGW), and 90.68% to grain yield (GY). The larger variations attributed
to genotypic effects for PL (36.3%), TGW (33.2%) and PH (20.7%) are useful for genotype
selection for yield-related traits. Based on a multi-trait biplot and Best Linear Unbiased
Prediction (BLUPs) analyses of the GEI data across all drought-prone testing environments,
the medium maturity mutant line designated as L7P9-13 was selected as the best yielding (2
tons/ha) and recommended for the drought-prone areas of Namibia.
In summary, the study identified sorghum production systems, key farmers’ perceived
production constraints and trait preferences in new varieties in Namibia. Also, the best dosage
of gamma radiation and EMS were determined for increasing the genetic diversity in sorghum
for genetic enhancement. Newly developed mutant lines ML2, ML3, ML4, ML7 and ML14
displayed moderate to high genetic distance useful for breeding high-yielding and droughttolerant
varieties suited for the drought-prone environments of Namibia. The medium maturity
and drought-tolerant mutant line designated as L7P9-13 was the best yielding (2 tons/ha) and
recommended for large-scale production in the country
Genetic analysis of striga resistance and yield-influencing traits in tropical and subtropical maize.
No full textDoctoral Degree. University of KwaZulu-Natal, PietermaritzburgMaize (Zea mays L., 2n = 2x = 20) is a vital food security and economic crop in sub-Saharan Africa (SSA) and globally. In SSA maize production is challenged by an array of biotic and abiotic stresses. Two parasitic weeds belonging to the genus Striga, S. hermonthica (Del.) Benth (Sh) and S. asiatica (L.) Kuntze (Sa) causes marked yield losses varying from 10% to 100% in susceptible maize cultivars. Striga-resistant maize varieties released so far had partial or moderate resistance and were bred for Sh resistance only. There are therefore no commercially grown maize varieties with Sa resistance requiring to develop new-generation maize varieties with durable Sa and Sh resistance and wide adaptability using genetically diverse tropical and subtropical genetic resources and genomic resources. The overall objective of this study was therefore, to improve maize resistance to Sa and Sh by harnessing genetic diversity and identifying markers and genes for resistance breeding. The overall hypothesis of the study was that novel genetic resources, genetic markers and genes associated with Sa and Sh resistance could be identified for dual Striga resistance for maize breeding programs.
The study had further five specific objectives: 1) To undertake a meta-analysis and provide a detailed comparison of the Striga control methods in the production of maize, sorghum, and the major millets as a guide to effective Striga management. 2) To assess the response of 130 tropical and sub-tropical African maize germplasm to Sh and Sa resistance and desirable agronomic traits and select promising genotypes. 3) To determine the genetic diversity of 130 tropical and sub-tropical maize inbred lines, hybrids, and open-pollinated varieties using phenotypic traits and single nucleotide polymorphism (SNP) markers to select Striga-resistant and complementary genotypes for breeding. 4) To determine the combining ability and gene action controlling grain yield and Striga resistance among single crosses of maize to select desirable hybrids with Sh and Sa resistance and promising agronomic traits. 5) To undertake a genome-wide association analysis of grain yield and Sh and Sa resistance among tropical and sub-tropical maize populations to identify putative genetic markers and genes for marker-assisted resistance breeding and gene pyramiding.
In the first part of the study, a meta-analysis was conducted on already reported Striga control methods on the major cereal crops (i.e., maize, sorghum, and millets) using 66 research articles. The data collected included grain yield (GY), Striga emergence count (SEC), and Striga damage rating (SDR). The search showed mean yield for maize varieties with Striga-resistant genes at 2053.00 kg ha−1, ranging from 281.00 to 6260.00 kg ha−1, and a mean SDR of 4.70, varying from 2.00 to 7.00. Likewise, sorghum varieties with Striga resistance genes achieved greater GY with a mean yield response of 1738.00 kg ha−1, ranging from 850.00 to 2162.00 kg ha−1. A relatively low GY was achieved in maize and sorghum production when deploying integrated Striga management (ISM) (e.g., cultural control + host resistance, and host resistance + chemical herbicides) and chemical Striga control. The outcome of this part of the study was that SDR is the best selection criterion for improving GY performance in maize, while SEC and SDR were the parameters of choice in sorghum selection programs for better GY under Striga infestation. The meta-analysis revealed that host resistance is the most effective method for controlling Striga infestation and boosting GY in maize and sorghum.
The second part of the study focused on screening 130 tropical and sub-tropical maize germplasms, including checks, in a controlled environment for their reaction to Sh and Sa infestations using a 13×10 alpha lattice design with two replications over two seasons. The following data were collected on maize: days to 50% silking (DS), days to anthesis (DA), anthesis-silking interval (ASI), plant height (PLHT), ear height (EHT), Root lodging (RL), the number of ears per plant (EPP), husk cover (HUSK), ear aspect (EASP), and grain yield per plant (GY/plant). Striga parameters included the number of emerged Sa and Sh plants 8 and 10 weeks after planting, denoted as SEC8 and SEC10, and host plant damage by Striga 8 and 10 weeks after planting, designated as SDR8 and SDR10. The mean yield of maize and Striga par were 3.35 and 3.07, respectively. Under Sh-infested conditions, SEC8 and SEC10 mean values were 3.66 and 3.77, respectively, while the SDR8 and SDR10 values were 5.25 and 2.75 respectively. The results suggested that dual resistance to the two Striga species exists in some tropical and sub-tropical maize lines. The study selected genotypes CML440, CML566, CML540, CML539, CLHP0343, CLHP0326, TZISTR1248, TZSTRI115, TZISTR25, TZISTR1205, TZSTRI113, TZISTR1119, TZISTR1174 and the OPVs B.King/1421, Shesha/1421, ZM1421, DTSTR-WSYN13, DTSTR-YSYN14, and 2*TZECOMP3DT/WhiteDTSTRSYN) C2 with dual resistance to Sa and Sh. These genotypes are suitable for use as parents in developing high-performing maize varieties with Striga resistance and improved grain yield.
The third part of the study assessed the genetic diversity of 130 tropical and sub-tropical maize inbred lines, hybrids, and open-pollinated varieties using Striga resistance and agronomic traits, and SNP markers. The SNP markers demonstrated that the test genotypes had an average gene diversity of 0.34 and a polymorphic information content of 0.44, indicating significant phenotypic variation. Significant variation was recorded within populations (85%) compared to between populations using the analysis of molecular variance. The structure analysis allocated the test genotypes into eight major clusters (K = 8) in concordance with the principal coordinate analysis (PCoA). The following genetically distant inbred lines were selected, displaying good agronomic performance and Sa and Sh resistance: CML540, TZISTR25, TZISTR1248, CLHP0303, TZISTR1174, TZSTRI113, TZDEEI50, TZSTRI115, CML539, TZISTR1015, CZL99017, CML451, CML566, CLHP0343 and CML440. The new selections will now facilitate the breeding of maize varieties with Striga resistance and market-preferred traits.
In the fourth part of the study, a combining ability analysis was undertaken to determine the mode of gene action regulating Sa and Sh resistance and to select good combiner parental maize lines for hybrid breeding. Four preliminarily selected tropical high-yielding and Sh-resistant testers and eight sub-tropical lines with Sa resistance were crossed using a line-by-tester mating design, and 32 single cross hybrids were generated. The crosses and their parents were evaluated under field and controlled environments during the 2023/2024 growing season using a 7 x 6 alpha lattice design with two replications. Combined analysis of variance revealed a significant (p<0.05) effect of the crosses on grain yield (GY), related agronomic traits, Striga emergence counts, and Striga damage rating 8 and 10 weeks after sowing. The ratio of the general combining ability effect (SCA) and the specific combining ability effect (SCA) was less than one for all the traits, indicating the predominance of non-additive genetic effects in trait inheritance and signifying the value of hybrid breeding. The best general combiner tester was TZISTR1248 in the Sa-infested environment, while tester TZISTR1174 was noteworthy under Sh environment. Lines CML540 and CLHP0343 were the best combiners in Sa environment, while CZL99017, CML566, CML540, and CLHP0343 were promising in Sh environment and CML540 was the best general combiner in all test environments. The crosses CML540 x TZISTR1174, CML540 x TZDEEI50, and CML539 x TZISTR1174 exhibited high yields, significant SCA effects, and high heterosis for GY in Sa environment. Whereas, in Sh environment, cross CML440 x TZDEEI50 had the best GCA effect and heterosis for GY. Crosses CML451 x TZISTR1174, CML539 x TZISTR1174, CML440 x TZDEEI50, CML566 x TZDEEI50, CZL99017 x TZISTR1248, and CML539 x TZISTR1248 were relatively the best specific combiners for GY in both Sa and Sh environments. The selected lines and testers and the new experimental hybrids are recommended for multi-environment evaluation in Sa and Sh-prone agroecologies to enhance grain yield and Striga resistance.
In the fifth final part of the study, a genome-wide association analysis of grain yield and Sh and Sa resistance among tropical and sub-tropical maize populations was undertaken to identify putative genetic markers and genes for resistance breeding. The test genotypes were profiled for GY, SEC8, SEC10, SDR8, and SDR10. Population structure analysis and genome-wide association mapping were undertaken based on 16,000 single nucleotide polymorphism (SNP) markers using the Diversity Array Technology Sequencing platform. The genome-wide association study identified 50 significant loci associated with Sh resistance and 22 significant loci linked to Sa resistance, corresponding to 39 and 19 candidate genes, respectively. No significant loci were found associated with dual resistance, suggesting that breeding maize must be specific for resistance to each Striga species using germplasm adapted to the endemic region of each parasite.
Overall, the study finally revealed a novel result that host resistance is the most effective method for controlling Striga infestation and boosting GY despite that research institutions advocate integrated Striga management. Promising genotypes with Sa and Sh resistance were selected, and some tropical and sub-tropical genotypes showed dual resistance. Suitable parental lines and testers and new experimental hybrids were selected for Sa and Sh resistance breeding in SSA. The new selections could be explored for future Striga resistance breeding and the development of new varieties. Significant loci associated with Sh and Sa resistance with their corresponding genes were detected and could be used to facilitate selection for Sh and Sa resistance and GY in tropical and sub-tropical maize genetic resources
Genetic characterization of citron watermelon (citrullus lanatus var. citroides [L.H. Bailey] mansf. ex greb.) and development of experimental hybrids = Isimo sofuzo sekhabe i-citron (Citrullus lanatus var. citroides [L.H. Bailey] Mansf. ex Greb.) kanye nokuthuthukiswa kwenhlanganisela yokuhlola.
No full textDoctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.Citron watermelon (Citrullus lanatus var. citroides [L.H. Bailey] Mansf. ex Greb.) is indigenous to sub-Saharan Africa (SSA) with multiple uses, including human food and animal feed. Its succulent leaves are used as leafy vegetables, while the ripened yellow and orange-fleshed fruits are used to prepare various traditional dishes, and the seeds are roasted and consumed as snack. It is an emerging potential rootstock for producing grafted sweet watermelon (Citrulus lanatus var. lanatus) to improve fruit yield and biotic and abiotic stress tolerance. It is also a source of novel genes for breeding in sweet watermelon to improve fruit yield, quality and disease resistance. Citron watermelon in SSA is mainly cultivated using unimproved landrace varieties. Landraces exhibit marked phenotypic variation for fruit shape, size, skin colour patterns, and seed coat colours. Phenotypic and genetic variation among South African citron watermelon landraces is yet to be systematically assessed for diverse use and cultivar design. The overall goal of this study was to initiate a pre-breeding program for citron watermelon through identification and selection of unique and complementary genotypes for production, value-adding and breeding. The specific objectives of this study were: i. To determine the extent of genetic diversity among South African citron watermelon landrace accessions using selected simple sequence repeat (SSR) markers to identify genetically divergent accessions for trait integration and variety development; ii. To assess the phenotypic diversity of citron watermelon landrace accessions of South Africa and to select desirable genotypes with suitable agronomic and horticultural traits for direct production, breeding and conservation; iii. To estimate variance components, heritability and genetic advance of phenotypic traits in citron watermelon to guide the selection of superior genotypes for direct production and breeding; iv. To determine the combining ability and hybrid performance of citron watermelon genotypes for agronomic traits for breeding. In the first study, 48 citron watermelon landrace collections widely grown in the Limpopo Province of South Africa were genotyped using 11 selected SSR markers.
The SSR markers amplified a total of 24 alleles, with a mean expected heterozygosity value of 0.38, indicating moderate genetic diversity among the studied accessions. Analysis of molecular variance attributed 8%, 75%, and 17% of the molecular variation between populations, among accessions and within accessions, respectively. Three distinctive genetic groups were identified based on cluster analysis. The following distantly related genotypes are recommended as breeding parents namely: WWM03, WWM04, WWM15, WWM16, WWM18, WWM22, WWM23, WWM24, WWM25, WWM26, WWM28, WWM33, WWM34, WWM35, WWM38, WWM39, WWM41, WWM66, WWM76, WWM78, WWM81, WWM84, WWM86 and WWM89 (selections from Cluster I), WWM14, WWM37, WWM42, WWM44, WWM46, WWM50, WWM65, WWM79, WWM85 and WWM87 (Cluster II), and WWM38, WWM47 and WWM48 (Cluster III). These are useful parental lines for pre-breeding to develop and release new varieties with multiple uses. In the second study, 36 selected citron watermelon landrace accessions were evaluated under field conditions across two environments using a 6 × 6 lattice design with three replicates. Data on key qualitative and quantitative traits were collected and subjected to non-parametric and parametric statistical analyses. The accessions showed wide phenotypic variation and unique traits for genetic improvement. Positive and significant correlations (p < 0.001) were recorded between total fruit yield per plant with plant height (r = 0.64), number of harvestable fruits (r = 0.70), number of marketable fruits (r = 0.73) and marketable fruit yield (r = 0.96). Seed yield per plant positively and significantly (p < 0.001) correlated with number of male flowers (r =0.68), plant height (r = 0.61) and total fruit yield (r = 0.79). Principal component analysis identified nine components which accounted for 86.38% of total variation amongst accessions for assessed phenotypic traits. The study recommended citron watermelon accessions such as WWM14, WWM16, WWM39, WWM41, WWM67 and WWM79 for use as leafy vegetables owing to their profuse branching ability and longer vine production. Whereas accessions including WWM03, WWM17, WWM35, WWM40, WWM50, WWM67, WWM79 and WWM85 are selected with larger fruit size. Accessions WWM05 and WWM09 are sour-flesh types which are suitable genetic stocks for breeding sweet-and-sour and sweet dessert watermelons. Orange-fleshed accessions such as WWM03, WWM04, WWM46, WWM64, WWM66 and WWM67 are recommended for fresh consumption, cooking, processing or variety design.
Accessions WWM02, WWM03, WWM08, WWM14, WWM16, WWM23, WWM38, WWM40, WWM41 and WWM67 have red and white seed coat colour which are superior selections to prepare roasted citron watermelon seed snack. In the third study, variance components, heritability and genetic gains of phenotypic traits were estimated involving 36 accessions of citron watermelon grown under field conditions across two test environments using a 6 × 6 lattice design with three replicates. High broad-sense heritability and genetic advance as percent of the mean were recorded for fruit length at 83.86 and 4730.45%, seed length (77.73 and 1731.27%), hundred seed weight (73.73 and 4027.36%), fruit diameter (70.44 and 2949.64%) and fruit weight (70.39 and 8490.05%), respectively. Step-wise regression analysis revealed marketable fruit yield and total number of fruits per plant explaining 89% (R2 = 0.89) of total variation for total fruit yield per plant, whereas number of seed per fruit and hundred seed weight explained 92 (R2 = 0.92) of total variation for seed yield per fruit. Citron watermelon landrace accessions WWM03, WWM14, WWM16, WWM39, WWM65, WWM67 and WWM79 with high total fruit yield and seed yield per fruit were selected for production or breeding programme. In the fourth study, five selected parental genotypes were crossed in a 5 × 5 half-diallel mating design to develop 10 hybrids. The 15 families (five parents and 10 F1 hybrids) were evaluated across two environments using a randomized complete block design (RCBD) with three replications. General combining ability (GCA) and specific combining ability (SCA) effects were significant (p < 0.001) for most traits. Environment × GCA was non-significant, whereas Environment × SCA effects were significant (p < 0.001) for most traits. The ratios of GCA/SCA variances were less than unity for most traits, indicating non-additive gene action of the traits. Broad-sense heritability varied from low to moderate, implying variable selection response of the assessed traits among the F1 hybrids. The parental genotypes WWM16 with positive GCA effects for fruit and seed yield and WWM66, with positive GCA effects for the number of seeds per fruit and seed yield, were identified for hybrid breeding. The following F1 hybrids, namely: WWM04 × WWM16, WWM03 × WWM66 and WWM16 × WWM50 with positive SCA effects on total fruit yield per plant and marketable fruit yield per plant, and WWM04 × WWM50, WWM03 × WWM16 and WWM03 × WWM66 with positive SCA effects for number of seeds per fruit and total seed yield were identified. The study identified novel and best-performing F1 hybrids of citron watermelon for economic traits and are recommended for multi-environmental evaluations, variety registration and commercialization. Overall, the study revealed genetic and phenotypic variation in citron watermelon to select and recommend suitable genotypes for production and for breeding new generation varieties based on market needs and consumer preferences. The study recommends accessions such as WWM14, WWM16, WWM39, WWM64, WWM67, WWM76 and WWM79 with high fruit yield, and WWM03, WWM04, WWM14, WWM15, WWM16, WWM24, WWM28, WWM37, WWM46, WWM66 and WWM68 exhibiting high fruit and seed yield for breeding or direct production. The parents WWM04, WWM03 and WWM16 were identified as good combiners for fruit or seed yield and related-component traits for future breeding. The F1 hybrids derived from these parents, including WWM04 × WWM16, WWM03 × WWM16, WWM03 × WWM66, WWM16 × WWM50, and WWM04 × WWM50 were best performing for economic traits and new breeding population development.
Iqoqa.
Ikhabe le-citron (i-Citrullus lanatus var. citroides [L.H. Bailey] Mansf. ex Greb.) lingelendabuko e-Afrikha eseMazansi, (i-sub-Saharan Africa (SSA)) elinemisebenzi eminingi, okubalwa kuyo ukudla kwabantu kanye nokudla kwezilwane. Amahlamvu alo amnandi asetshenziswa njengemifino emaqabunga, bese kuthi izithelo esezivuthiwe eziphuzi kanye neziwukudla ezisawolintshi zisetshenziswa ukwenza ukudla kwendabuko okwahlukene, bese imbewu iyosiwa bese idliwa njengokudla okulula. Yisiqu sempande esafufusa ukukhiqiza ikhabe elingxube (i-Citrulus lanatus var. lanatus) ukuthuthukisa umkhiqizo wesithelo kanye nokubekezelela ingcindezi yokuphilayo nokungaphili. Kuyimbangela yofuzo olusha ukukhiqiza ikhabe elinoshukela ukukhulisa ekhabeni elinoshukela ukuthuthukisa umkhiqizo wesithelo, izingabunjalo kanye nokulwa nezifo. Ikhabe le-citron e-SSA litshalwa kakhulu kusetshenziswa izinhlobo ezahlukene zohlobo olusangulube engathuthukile. Uhlobo olusangulube olwehlukile ukumisa isithelo, ubungako, umbala wesikhumba kanye nemibala eyemboze imbewu. Uhlobo lokufanisa nofuzo phakathi kwekhabe lwe-citron lwaseNingizimu Afrikha nezingulube kusamele luhlolwe ngendlela ukuveza umsebenzi owehlukile nohlaka lokutshala. Inhloso enkulu yalolu cwaningo kwakungukuqala uhlelo lokuqalela ukwandisa ikhabe le-citron ngokuveza kanye nokukhetha uhlobo lokulekelela olwehlukie ukukhiqiza, ukwengeza ukubaluleka kanye nokwandisa. Izinhloso ezikhethekile zalolu cwaningo kwakuyilezi:
i. Ukuthola ukuthi luhamba luze lufike kuphi uhlobo lomehluko phakathi kwekhabe laseNingizimu Afrikha olusangulube olungenisiwe kusetshenziswa ukulandelana okulula okukhethekile kokuphinda izinkomba, (ama-simple sequence repeat (SSR)) ukuveza ukungena okwehlukile kofuzo ukuveza ukuhlanganisa kanye nokuthuthuka okwehlukile;
ii. Ukuhlola umehluko wohlobo lwekhabe le-citron olusangulube olungenisiwe lwaseNiningizimu Afrikha kanye nokukhetha ufuzo oludingekayo kanye nezinkomba zomhlabathi olimekayo kanye notshalekayo ukuqondisa umkhiqizo, ukwandisa kanye nokugcineka;
iii. Ukuhlawumbisela umehluko wezinhlaka, ifa kanye nokuqhubeka kofuzo lwezinkomba zohlobo ekhabeni lwe-citron ukuhlola ukukhetha kohlobo lofuzo olukhulu ukuqondisa umkhiqizo kanye nokwandisa;
iv. Ukuthola ukukwazi okuhlanganisayo kanye nokusebenza okuyinhlanganisela yohlobo lwekhabe lwe-citron ukulimekela ukwandisa.
Ocwaningweni lokuqala, amaqoqa amakhabe ekhabe le-citron olusangulube olutshalwa esiFundazweni saseLimpopo saseNingizimu Afrikha afaniswa kusetshenziswa izinkomba eziyi-11 ezikhethiwe ze-SSR. Izinkomba se-SSR zakhulisa isamba sokuzo olungama-24, ngemini elindelekile ebalwe ngenani lika-0.38, okukhomba umehluko wobuhlobo ophakathi nendawo phakathi kwezingenelelo ezacwaningwa. Ukuhlaziya komehluko wezinhlayiya kwaveza u-8%, u-75%, kanye no-17% womehluko wezinhlayiya phakathi kwamaqoqo, phakathi kwezingenelelo kanye nangaphakathi kwezingenelelo, ngokulandelana kwakho. Amaqoqo ohlobo olwehlukile amathathu avezwa ngokuhlaziya ngendlela yokubeka ngamaqoqo. Izinhlobo ezihlobene ngokuqgagqana ziyaphakanyiswa njengabazali bokwandisa ababizwa: i-WWM03, i-WWM04, i-WWM15, i-WWM16, i-WWM18, i-WWM22, i-WWM23, i-WWM24, i-WWM25, i-WWM26, i-WWM28, i-WWM33, i-WWM34, i-WWM35, i-WWM38, i-WWM39, i-WWM41, i-WWM66, i-WWM76, i-WWM78, i-WWM81,i-WWM84, i-WWM86 kanye ne-WWM89 (ukukhetha eQoqweni I), i-WWM14, i-WWM37, i-WWM42, i-WWM44, i-WWM46, i-WWM50, i-WWM65, i-WWM79, i-WWM85 kanye ne- WWM87 (IQoqo II), kanye ne-WWM38, i-WWM47 kanye ne-WWM48 (IQoqo III). Laba olayini bokuzala abanomsebenzi wokulungiselela ukwandisa ukuthuthukisa kanye nokukhulula izinhlobo ezintsha kanye nemisebenzi eminingi.
Ocwaningweni lwesibili, ikhabe le-citron elikhethiwe elingama-36 olusangulube lokungenisiwe lwahlolwa ngaphansi kwezimo zensimi ezimweni ezimbili ezingefani kusetshenziswa uhlobo lohlaka u-6 × 6 nezifaniso ezintathu. Imininingo yezinkomba ezisemqoka zekhwalithethivu kanye nezinombolo yaqoqwa bese yahlotshaniswa nokuhlaziya okunemikhawulo kanye nokungenamkhawulo. Okwangeniswa kwaveza umehluko wohlobo omkhulu kanye nezinkomba ezahlukile zokuthuthukisa ufuzo. Ukuhlobana okuhle futhi okubalulekile (p < 0.001) kwaqoshwa phakathi kwesithelo esikhiqiziwe ngokwesitshalo esinobude baso obu-(r = 0.64), inombolo yezithelo ezinokuvuneka (r = 0.70), inombolo yezithelo ezidayisekayo (r = 0.73) kanye nomkhiqizo wesitho esidayisekayo (r = 0.96). Umkhiqizo wembewu ngokwesitshalo kwahlobana kahle futhi kakhulu (p < 0.001) nenombolo yezimbali zesilisa (r = 0.68), ubude bezitshalo (r = 0.61) kanye nenani lomkhiqizo wesithelo (r = 0.79). Ukuhlaziya kwengxenye enkulu kuveze izinhlaka eziyisishiyagalombili kwachaza u-86.38% yomehluko ohlangene phakathi kokungenisiwe kwahlola izinkomba zezinhlobo ezinofuzo.
Ucwaningo luphakamisa ukuthi ikhabe le-citron olufana ne-WWM14, i-WWM16, i-WWM39, i-WWM41, i-WWM67 kanye ne-WWM79 elisetshenziswa njengemifino engamaqabunga liyimbangela yokukwazi ukusabalala okwedlulele kanye nomkhiqizo wesivuno omude. Kanti okungenisiwe okufana ne-WWM03, i-WWM17, i-WWM35, i-WWM40, i-WWM50, i-WWM67, i-WWM79 kanye ne-WWM85 kukhethwa njengesithelo esikhulu ngobungako. Okungenisiwe kwe-WWM05 kanye ne-WWM09 kuyizinhlobo zokudliwayo okumuncu okuwufuzo olulungele ukugcinelwa ukwandiswa kwamakhabe anoshukela nesimuncwana kanye nesidlo sokuphetha. Okungenisiwe okudliwayo okusawolintshi okufana ne-WWM03, WWM04, i-WWM46, i-WWM64, i-WWM66 kanye ne-WWM67 kuphakanyiswa ukudliwa kusekusha, ukuphaka, ukukhiqizwa, noma uhlaka lohlobo. Okungenisiwe kwe-WWM02, i-WWM03, i-WWM08, i-WWM14, i-WWM16, i-WWM23, i-WWM38, i-WWM40, i-WWM41 kanye ne-WWM67 kunembewu ebomvu kanye nemhlophe yemibala yokwembozile okukhetheke kakhulu ukulungisela imbewu eyosiwe yekhabe le-citron lokudla okulula.
Ocwaningweni lwesithathu, izinhlaka zoshintsho, ukufuza, imivuzo yofuzo yezinkomba zezinhlobo kwahlawumbiselwa kubalwa okungenisiwe okungama-36 kwekhabe le-citron elitshalwa ngaphansi kwezimo zensimu ngapha nangapha kwezizinda zokulinga ezimbili kusetshenziswa uhlaka lohlelo luka-6 × 6 nezimpinda ezintathu. Ukufuza okusabalele ngokubanzi kanye nokusabalala kohlobo njengephesenti lemini kwaqoshelwa ubude besithelo ku-83.86 kanye no-4730.45%, ubude bembewu (77.73 no-1731.27%), isisindo sembewu esiyikhulu (73.73 no- 4027.36%), ubude bephakathi lesithelo (70.44 no-2949.64%) kanye nesisindo sesithelo (70.39 no-8490.05%), ngokulandelana. Ukuhlaziya ukuphendukela emumva ngokwesigaba ngesigaba kwaveza imiphumela yesithelo edayisekayo kanye nenani lenombolo yezithelo ngesitshalo kuchaza ama-89% (R2 = 0.89) womehluko ophelele wesiphumo sesithelo ngesitshalo, kanti inombolo yembewu ngesitshalo kanye nesisindo sembewu eyikhulu kwachazwa ngo-92% (R2 = 0.92) wenani lomehluko wesiphumo sembewu ngesitshalo. Okungenisiwe kwekhabe le-citron elisangulube i-WWM03, i-WWM14, i-WWM16, i-WWM39, i-WWM65, i-WWM67 ne- WWM79 nenani eliphezulu leziphumo zesithelo kanye nesiphumo sembewu ngesitshalo kwakhethelwa umkhiqizo noma uhlelo lokwandisa.
Ocwaningweni lwesine, izinhlobo ezifuzene zokuzalana ezinhlanu zakhethwa ngapha nangapha kuhhafu ka-5 × 5 wohlaka lokuhlanganisa uqondanisa ukuthuthukisa inhlanganisela eyi-10. Imindeni eyi-15 (abazali abahlanu kanye nenhlanganisela ka-10 F1) kwahlolwa ngapha nangapha ezimweni ezimbili kusetshenziswa uhlaka lweqoqo oluphelele olukhethwe ngokungenhloso, (i-randomized complete block design (RCBD)) nokuphindaphinda okuthathu. Ukukwazi kokuhlanganisa okwejwayelekile, (i-General combining ability (GCA)) kanye nemiphumela yokukwazi kokuhlanganisa okuthile, (i-specific combining ability (SCA)) kwakubalulekile (p < 0.001) ezinkombeni eziningi. I-Environment × GCA yayingabalulekile, kanti imiphumela ye-Environment × SCA yayibalulekile (p < 0.001) ezinkombeni eziningi. Ubudlelwane bomehluko we-GCA/SCA babubuncane ngaphansi ngokukodwa ezinkombeni eziningi, okukhomba ukusebenza kofuzo olungengezeleli lwezinkomba. Ufuzo olubanzi ngokusabalele lwehluka kusukela phansi kuya phakathi nendawo, okusho impendulo yokukhetha ivarebuli ezinkombeni ezihloliwe phakathi kwenhlanganisela ye-F1. Uhlobo lofuzo lokuzala i-WWM16 nemiphumela emihle ye-GCA yesithelo kanye nesiphumo sembewu kanye ne-WWM66, nemiphumela emihle ye-GCA enombolweni yembewu ngesithelo kanye nesiphumo sembewu, kwatholakala ukwandisa okuyinhlanganisela. Inhlanganisela elandelayo ye-F1, nokuyi-: WWM04 × WWM16, i-WWM03 × WWM66 kanye ne-WWM16 × WWM50 nemiphumela emihle ye-SCA enanini lesiphumo sesithelo ngesitshalo kanye nesiphumo sesithelo esithengisekayo, kanye ne-WWM04 × WWM50, i-WWM03 × WWM16 kanye ne-WWM03 × WWM66 nemiphumela emihle ye-SCA enombolweni yembewu ngesitshalo kanye nenani lesiphumo lembewu kwatholakala. Ucwaningo lwaveza izinhlanganisela ezintsha futhi ezisebenza kangcono kakhulu ze-F1 zekhabe le-citron ezinkombeni zomnotho kanti ziyanconywa ukuhlolelwa imvelo okuningana, ukubhalisa umehluko kanye nokuthengisa.
Sekukonke, ucwaningo luveze ukuthi umehluko wofuzo kanye nowohlobo lofuzo ekhabeni le-citron ukukhetha kanye nokuphakamisa uhlobo lofuzo olulungele imkhiqizo kanye nokwandisa izinhlobo zenzalo entsha kuncike ezidinweni zemakethe kanye nasekukhetheni kwabathengi. Ucwaningo luphakamisa okungeniswayo okufana ne-WWM14, i-WWM16, i-WWM39, i-WWM64, i-WWM67, i-WWM76 kanye ne-WWM79 nesiphumo esiphezulu sesithelo, kanye ne-WWM03, i-WWM04, i-WWM14, i-WWM15, i-WWM16, i-WWM24, i-WWM28, i-WWM37, i-WWM46, i-WWM66 kanye ne-WWM68 kuveza isithelo esiphezulu kanye nesiphumo sembewu ukwandisa umkhiqizo oqondile. Abazali i-WWM04, i-WWM03 kanye ne-WWM16 batholakala njengezihlanganiso zesithelo noma zesiphumo sembewu kanye nezinkomba zezinhlaka ezihlobene ukwandisa kwesikhathi esizayo. Izinhlanganisela ze-F1 ezatholakala kulaba bazali, okubalwa kubo i-WWM04 × WWM16, i-WWM03 × WWM16, i-WWM03 × WWM66, i-WWM16 × WWM50, kanye ne- WWM04 × WWM50 kwakusebenzela kakhulu izinkomba zomnotho kanye nokuthuthukisa inani lokwandisa
Pre-breeding of sorghum [sorghum bicolor (L.) moench] for drought tolerance in the semi-arid zones of Nigeria=Ukulungisela ukuzalanisa kweSorghum [Sorghum bicolor (L.) Moench] Yokubekezelela Isomiso Ezindaweni Ezomile ZaseNigeria.
No full textDoctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.Sorghum [Sorghum bicolor (L.) Moench] is a staple food crop serving millions of people in Africa and Asia's arid and semi-arid agro-ecologies. Sorghum is widely cultivated in Northern Nigeria, serving diverse value chains, including the food and feed sectors and the brewery industry. However, the potential production and productivity of sorghum in Africa, including Northern Nigeria, is constrained by severe drought stress associated with climate change. Furthermore, smallholder farmers in Nigeria still cultivate low-yielding and drought-susceptible unimproved sorghum landraces. Developing drought-tolerant sorghum cultivars adapted to semi-arid regions would enhance yield gains and stability with desirable product profiles according to the needs of the farmers and the marketplace. Therefore, the overall objective of this study was to improve sorghum productivity in Nigeria by developing new generation, locally adapted and drought-tolerant varieties. The specific objectives of this study were to: (1) present the current opportunities and constraints to sorghum production in Nigeria and make recommendations as a guide to new variety design and sustainable production, (2) determine drought tolerance and genotype-byenvironment interaction (GEI) effect on grain yield of a population of African sorghum genotypes to identify high-yielding and drought-adapted genotypes for production and breeding, (3) assess the genetic diversity and deduce the population structure among 200 sorghum accessions to guide the selection of contrasting parents for pre-breeding and breeding of drought-tolerant sorghum cultivars and (4) determine the combining ability, heterosis and gene action conditioning agronomic traits and grain yield among sorghum genotypes to select genetically superior and contrasting parental genotypes and new families for drought tolerance breeding, cultivar release and commercialization.
In the first chapter, a participatory rural appraisal (PRA) study was conducted in three selected sorghum growing zones in Northern Nigeria involving 250 farmers. Socio-economic data were collected through surveys and focus group discussions.
Results showed that sorghum was cultivated mainly by males (80%) who had grade 6-12 level of education (31.3%), with a productive age of 21-45 years (75.7%) and a household family size of below five members (52.3%). Low-yielding landrace varieties such as Kaura (37.4%) and Fara-fara (29.3%) were the most widely cultivated types across the study zones due to their good grain quality. The major farmers' preferred traits from a sorghum variety were high yield, drought tolerance and Striga resistance. The study recommends integrated sorghum technology development incorporating the described preferences of the farmers for sustainable production and economic gains of the crop. The second chapter examined 225 sorghum genotypes assembled from diverse origins to determine drought tolerance and GEI effects on grain yield. The collections were evaluated under non-stressed (NS), pre-anthesis drought stress (PreADS), and post-anthesis drought stress (PoADS) conditions under field and greenhouse environments. The additive main effect and multiplicative interaction (AMMI) analysis revealed that genotype (G), environment (E), and GEI were significant (p<0.05) and accounted for 38.7, 44.6, and 16.6% of the total explained variation in grain yield, in that order. AMMI 4 was the best-fitting model for genotype selection with better grain yield. Based on AMMI 4 and the Best Linear Unbiased Predictors (BLUPs) analyses, genotypes Yar Lazau and Dangama Wulchichi, with a grain yield of 5.6 t/ha and 6.3 t/ha, were selected as being suitable for non-stressed conditions, respectively. Genotypes ICNSL2014-022-4 and Takumbo with BLUPs of 2.5 t/ha and 2.6 t/ha were best-suited for pre-anthesis drought stress conditions, whereas genotypes Danyar Bana and Gagarau - 4 with BLUPs of 4.2 t/ha and 4.3 t/ha are recommended for post-anthesis drought-prone environments, respectively. The identified sorghum genotypes are valuable genetic resources to develop novel drought tolerance cultivars or for production in dry agro-ecologies of sub-Saharan Africa characterized by pre-and-post anthesis drought stress. In the third chapter, diversity arrays technology (DArT) –derived single nucleotide polymorphism (SNP) markers were used to assess the genetic diversity and discern the population structure of 200 sorghum accessions to select complementary lines for breeding. The markers have moderate discriminatory power, with the polymorphism information content ranging between 0.09 to 0.38. The average gene diversity value (0.32) was high, while the average observed heterozygosity (0.15) was relatively low, a typical value for autogamous crop species like sorghum. The population structure and cluster analyses revealed four main clusters with a high level of genetic diversity among the accessions studied. The variation within populations (41.5%) was significantly higher than that among populations (30.8%) and between samples within a structure (27.7%). The high genetic variation within the population could be attributed to the preservation of sorghum landraces by farmers and differences in the genetic constitution,
adaptation and parentage. The study identified distantly related sorghum accessions such as Samsorg 48, Kaura Red Glume (from Cluster 1); Gadam, AS 152 (Cluster 2); CSRO1, ICNSL2014−062 (Cluster 3); and Yalai, Kafi Mori (Cluster 4) useful in developing new gene pools and novel genotypes for the West and Central Africa (WCA) sorghum breeding programs. Based on the phenotypic and genotypic data, 12 contrasting parents were selected for breeding population development with high yield and drought tolerance.
In the last chapter, 12 contrasting sorghum parents were selected from a diverse set of 225 genotypes exhibiting variable agronomic traits, including high grain and drought tolerance and farmer-preferred attributes. The 12 parents were crossed using a half-diallel mating design to create 66 F1 progenies. The F1 progenies, the parents, and two check varieties were evaluated under three environments in Nigeria. The results revealed the presence of significant variations amongst test genotypes allowing the selection of suitable parents and hybrids for traits of interest. The contribution of the specific combining ability (SCA) variance to total variance was higher than that of the general combining ability (GCA) for most of the studied traits, indicating that nonadditive gene action was more dominant in conditioning trait inheritance. GCA x environment and SCA x environment interaction effects were significant (p<0.05) for days to anthesis, aboveground biomass and grain yield. Parental genotypes Samsorg 7, Masakwa, and SSV2008091, recorded significant and positive GCA effects for grain yield and are useful germplasm resources for breeding high-yielding cultivars. Crosses AS 152 x SSV2008091, Samsorg 7 x Kurumbasau, AS 152 x ICNSL2014-022-8, and Masakwa x Hindatu exhibited high and positive SCA effects and were the top performers recording above-ground biomass yield of 29.3, 23.4, 27.2 and 16.5 t/ha and grain yield of 6.4, 6.6, 6.6 and 6.5 t/ha, in that order. The crosses exhibited high parent heterosis for grain yield and other agronomic traits, revealing that hybrid breeding is an effective
strategy for boosting sorghum production. The newly selected F1 progenies had higher yields than the local checks and are recommended for hybrid or pure line breeding and variety release in Nigeria's drought-prone areas and similar sub-Saharan Africa (SSA) agro-ecologies after continuous selection and multi-environment testing. Overall, the study identified drought stress as the most critical sorghum production constraint in Northern Nigeria. Also, the study highlighted significant genetic diversity among the test genotypes. Best performing genotypes Yar Lazau, ICNSL2014-022-4 and Danyar Bana were
selected as suitable for non-stressed, pre-anthesis and post-anthesis drought stress conditions, respectively. The selected genotypes are recommended for production or breeding in droughtprone areas. In addition, the study identified drought-tolerant and early-maturing genotypes (e.g., Samsorg 7, Masakwa, and SSV2008091) with good general combining ability effects for breeding
population development and heterosis breeding in the semi-arid region of Northern Nigeria.
IQOQA
Amabele [Sorghum bicolor (L.) Moench] iyisivuno sokudla okuyinhloko esiphakela izigidi zabantu e-Afrika kanye ne-agro-ecologies eyomile necishe koma yase-Asia. Amabele atshalwa kakhulu eNyakatho yeNigeria, asetshenziselwa uchungechunge lwezinto ezahlukahlukene, kufaka phakathi imikhakha yokudla kanye nomkhakha wokuphiswa kotshwala. Kodwa-ke, ukukhiqizwa okungenzeka kanye nomkhiqizo wamabele e-Afrika, kufaka phakathi iNyakatho yeNigeria, kucindezelwa ukucindezeleka okukhulu kwesomiso okuhambisana nokuguquka kwesimo sezulu. Ngaphezu kwalokho, abalimi abancane eNigeria basalima amabele akhiqiza kancane nesezindaweni ezizwelayo esomisweni. Ukuthuthukisa kokutshalwa kohlobo lwamabele abekezelela isomiso ezifundeni ezomile kungathuthukisa ukuzuza kwesivuno nokuzinza ngamaphrofayili omkhiqizo ofiselekayo ngokwezidingo zabalimi kanye nendawo yemakethe. Izinhloso ngqo zalolu cwaningo zazithi: (1) ukwethula amathuba amanje kanye nezingqinamba zokukhiqiza amabele eNigeria futhi wenze izincomo njengesiqondiso sokuklama izinhlobonhlobo ezintsha kanye nokukhiqizwa okuqhubekayo, (2) ukunquma ukubekezelela isomiso kanye nomphumela wokusebenzisana kwegenotype-by-environment (GEI) ekuvuneni okusanhlamvu kwabantu be-African sorghum genotypes ukuhlonza amagenotypes aphezulu futhi avumelaniswe nesomiso sokukhiqiza nokuzala, (3) ukuhlola ukuhlukahluka kwezakhi zofuzo nokuthola isakhiwo sokusabalala phakathi kokufinyelela kwamabele angama-200 ukuqondisa ukukhethwa kwabazali abahlukile bokuzalanisa kwangaphambili nokuzalanisa amacultivars amabele abekezelela isomiso futhi (4) ukunquma ikhono lokuhlanganisa, iheterosis kanye nesenzo segene esilungisa izici ze-agronomic kanye nesivuno sokusanhlamvu phakathi kwamagenotypes amabele ukukhetha amagenotypes aphakeme ngofuzo futhi ahlukile wabazali kanye nemindeni emisha yokuzalanisa ukubekezelelana kwesomiso, ukukhululwa kwecultivar nokuthengisa.
Esahlukweni sokuqala, ucwaningo lwe- participatory rural appraisal (PRA) lwenziwe ezindaweni ezintathu ezikhethiwe zokukhulisa amabele eNyakatho yeNigeria ezibandakanya abalimi abanga-250. Imininingwane yezenhlalo nezomnotho yaqoqwa ngokusebenzisa inhlolovo kanye nezingxoxo zeqembu lokugxila. Imiphumela ikhombise ukuthi amabele alinywa ikakhulukazi ngabesilisa (80%) ababenezinga lemfundo lebanga le-6-12 (31.3%), abaneminyaka ekhiqizayo yeminyaka engama-21-45 (75.7%) kanye nobukhulu bomndeni wasekhaya obungaphansi kwamalungu amahlanu (52.3%). Izinhlobo zomhlaba ezithela kancane ezifana neKaura (37.4%) neFara-fara (29.3%) zaziyizinhlobo ezitshalwa kakhulu kuzo zonke izindawo zokufunda ngenxa yekhwalithi yazo enhle yokusanhlamvu. Izici ezikhethiwe zabalimi abakhulu ezivela ezinhlobonhlobweni zamabele zaziyisivuno esiphezulu, ukubekezelela isomiso nokumelana neStriga. Ucwaningo luncoma ukuthuthukiswa kobuchwepheshe obuhlanganisiwe bamabele okufaka izintandokazi ezichaziwe zabalimi zokukhiqiza okuqhubekayo kanye nokuzuza kwezomnotho kwesivuno.
Isahluko sesibili sihlole amagenotypes anga-225 amabele ahlanganiswe kusuka ezimvelaphini ezahlukahlukene ukunquma ukubekezelela isomiso nemiphumela ye-GEI ekuvuneni okusanhlamvu. Amaqoqo ahlolwe ngaphansi kwezimo ezingacindezelekile, ezinon-stressed (NS), ukucindezeleka kwesomiso sangaphambi kwe-anthesis, ipre-anthesis drought stress (PreADS), kanye nepost-anthesis drought stress (PoADS) ngaphansi kwezindawo zensimu kanye negreenhouse. Umphumela oyinhloko wesengezo kanye nokuhlaziywa kokusebenzisana kwemultiplicative (AMMI) kuveze ukuthi igenotype (G), imvelo okuyi-environment (E), ne-GEI yayibalulekile (p<0.05) futhi yaba ngama-38.7, 44.6, ne-16.6% wokuhlukahluka okuphelele okuchaziwe kwesivuno sokusanhlamvu, ngaleyo ndlela. I-AMMI 4 yayiyimodeli efaneleka kakhulu yokukhethwa kwegenotype ngesivuno esingcono sokusanhlamvu. Ngokusekelwe ekuhlaziyweni kwe-AMMI 4 kanye neBest Linear Unbiased Predictors (BLUPs), amagenotypes uYari Lazau noDangama Wulchichi, ngesivuno sokusanhlamvu se-5.6 t / ha ne-6.3 t / ha, bakhethwa njengabafanele izimo ezingacindezelekile, ngokulandelana. IGenotypes ICNSL2014-022-4 neTakumbo enama-BLUP we-2.5 t / ha ne-2.6 t / ha yayilungele kakhulu izimo zokucindezeleka kwesomiso sangaphambi kwe-anthesis, kanti amagenotypes Danyar Bana noGagarau - 4 nge-BLUPs ye-4.2 t / ha ne-4.3 t / ha kunconywa ezindaweni ezithambekele esomisweni ngemuva kwe-anthesis, ngokulandelana. Igenotypes yamabele ehlonziwe iyimithombo yofuzo eyigugu ukuthuthukisa amacultivars okubekezelela isomiso senoveli noma ukukhiqizwa kuma-agro-ecologies omile e-Afrika engezansi kweSahara ebonakala ngokucindezeleka kwesomiso sangaphambi kokuthunyelwe kwe-anthesis.
Esahlukweni sesithathu, idiversity arrays technology (DArT) – nezimpawu amaderived single nucleotide polymorphism (SNP) kwasetshenziselwa ukuhlola ukuhlukahluka kwezakhi zofuzo nokuqonda isakhiwo senani sokufinyelela kwamabele okungama-200 ukukhetha imigqa ehambisanayo yokuhiqiza. Izimpawu zinamandla okubandlulula ngokulinganisela, ngokuqukethwe kolwazi lwepolymorphism okuphakathi kuka-0.09 kuya ku-0.38. Inani elijwayelekile lokuhlukahluka kwezakhi zofuzo (0.32) laliphezulu, kanti isilinganiso sabona iheterozygosity (0.15) yayiphansi kakhulu, inani elijwayelekile lezinhlobo zezitshalo ze-autogamous njengamabele. Isakhiwo senani kanye nokuhlaziywa kweqoqo kwaveza amaqoqo amane aphambili anezinga eliphezulu lokuhlukahluka kwezakhi zofuzo phakathi kokufinyelela kokufundiwe. Ukuhlukahluka ngaphakathi kwenani (41.5%) kwakuphakeme kakhulu kunalokho phakathi kwenani (30.8%) naphakathi kwamasampula ngaphakathi kwesakhiwo (27.7%). Ukuhlukahluka okuphezulu kwezakhi zofuzo ngaphakathi kwenani kungabangelwa ukulondolozwa komhlaba wamabele ngabalimi kanye nokwehluka komthethosisekelo wofuzo, ukuzivumelanisa nezimo kanye nokuba ngumzali. Ucwaningo luveze ukufinyelela kwamabele okuhlobene kude njengeSamsorg 48, i-Kaura Red Glume (kusuka ku-Cluster 1); Gadam, AS 152 (Cluster 2); CSRO1, ICNSL2014−062 (Cluster 3); noYalai, uKafi Mori (Cluster 4) owusizo ekuthuthukiseni amachibi amasha ezakhi zofuzo kanye namagenotypes amasha ezinhlelo zokuzalanisa amabele zaseNtshonalanga naphakathi ne-Afrika (WCA). Ngokusekelwe emininingweni yephenotypic negenotypic, abazali abayi-12 abaphikisanayo bakhethwa ukuthuthukisa inani lesivuno esiphezulu nesinokubekezelela isomiso.
Esahlukweni sokugcina, imithombo eyi-12 eyahlukene yamabele yakhethwa esethini ehlukahlukene yamagenotypes anga-225 abonisa izici eziguquguqukayo ze-agronomic, kufaka phakathi okusanhlamvu okuphezulu nokubekezelela isomiso kanye nezici ezikhethiwe zomlimi. Imithombo eyi-12 yaxutshwa kusetshenziswa umklamo wokukhwelana wesigamu sediallel ukudala inzalo ye-66 F1. Inzalo ye-F1, imthombo, kanye nezinhlobo ezimbili zokuhlola zahlolwa ngaphansi kwezindawo ezintathu eNigeria. Imiphumela yaveza ukuba khona kokuhlukahluka okuphawulekayo phakathi kwamagenotypes okuhlola okuvumela ukukhethwa kwemithombo efanelekayo kanye namahybrid ezici ezithakazelisayo. Umnikelo ispecific combining ability (SCA) ukuhlukahluka kokuhlukahluka okuphelele kwakuphakeme kunalokho kwekhono igeneral combining ability (GCA) iningi lezici ezifundiwe, okubonisa ukuthi isenzo segene esingangeziwe sasibusa kakhulu esimweni sefa lesici. I-GCA x imvelo kanye ne-SCA x imvelo kwakubalulekile (p<0.05) ezinsukwini kuya ku-anthesis, ngaphezu kwebiomass yomhlaba kanye nesivuno sokusanhlamvu. Amagenotypes awumthombo i-Samsorg 7, i-Masakwa, ne-SSV2008091, aqophe imiphumela ebalulekile futhi emihle ye-GCA yesivuno sokusanhlamvu futhi ayimithombo ewusizo yegermplasm yokuzalanisa amacultivars aphezulu. Ukuxutshwa kwe-AS 152 x SSV2008091, i-Samsorg 7 x Kurumbasau, i-AS 152 x ICNSL2014-022-8, ne-Masakwa x Hindatu kubonise imiphumela ephezulu futhi emihle ye-SCA futhi yayingabadlali abaphezulu abaqopha isivuno se-biomass esingaphezulu komhlaba we-29.3, 23.4, 27.2 ne-16.5 t / ha kanye nesivuno sokusanhlamvu se-6.4, 6.6, 6.6 no-6.5 t / ha, ngaleyo ndlela. Ukuxuba kwabonisa iheterosis ephezulu yomthombo wesivuno sokusanhlamvu nezinye izici ze-agronomic, eveza ukuthi ukuzalanisa ihybrid kuyindlela ephumelelayo yokukhulisa ukukhiqizwa kwamabele. Inzalo esanda kukhethwa ye-F1 yayinesivuno esiphezulu kunokuhlolwa kwendawo futhi inconywa ukuzalanisa umugqa wehybrid noma ohlanzekile kanye nokukhishwa kwezinhlobonhlobo ezindaweni zaseNigeria ezithandwa isomiso kanye ne-agro-ecologies efanayo yesub-Saharan Africa (SSA) ngemuva kokukhethwa okuqhubekayo nokuhlolwa kwemvelo eningi.
Sekukonke, ucwaningo lwaveza ukucindezeleka kwesomiso njengengcindezi ebucayi kakhulu yokukhiqiza amabele eNyakatho Nigeria. Futhi, ucwaningo lwaqhakambisa ukuhlukahluka okuphawulekayo kwezakhi zofuzo phakathi kwamagenotypes okuhlola. Amagenotypes enza kahle kakhulu uYar Lazau, ICNSL2014-022-4 noDanyar Bana akhethwa njengafanelekile ezimweni zokucindezeleka ezingacindezelekile, zangaphambi kwe-anthesis kanye nezimo zokucindezeleka kwesomiso ngemuva kwe-anthesis, ngokulandelana. Amagenotypes akhethiwe anconywa ukukhiqizwa noma ukuzala ezindaweni ezithambekele esomisweni. Ngaphezu kwalokho, ucwaningo lwaveza amagenotypes abekezelela isomiso futhi avuthwa ekuqaleni (isib., iSamsorg 7, iMasakwa, ne-SSV2008091) ngemiphumela emihle ejwayelekile yokuhlanganisa ikhono lokuthuthukiswa kwenani elizalayo kanye nokuzalanisa iheterosis esifundeni esomile saseNyakatho Nigeria
Breeding wheat (triticum aestivum L.) for drought tolerance, improved yield and biomass allocation through chemical mutagenesis.
No full textDoctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.Abstract available in PDF
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