Database of African Theses and Dissertations including Research (DATAD-R)

Assessment of tissue culture derived regenerants of linseed (Linum usitatissimus L.) in Ethiopia

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dc.contributor Labuschagne, M. T.
dc.creator Gemelal, Adugna Wakjira 2018-08-30T12:12:08Z 2018-08-30T12:12:08Z 2000 2018-08-30T22:39:58Z 2018-08-30T22:39:58Z
dc.description English: I. The study was undertaken to assess the comparative performance of six linseed regenerants along with two crosses and three check cultivars across 18 linseed-growing environments of Ethiopia from 1996 to 1998. The seed yield and other agronomically desirable characters were analysed with different statistical procedures to determine the adaptation potential, G x E interactions and seed yield stability performance. The main objective of the study was to understand and describe the genotypes and their growing environments by applying different statistical methods of analyses in order to make useful recommendations for the future. Likewise, contemporary studies on the genotypes, environment and their interactions, and various analytical methods ofstability parameters were discussed. 2. Separate and combined analyses of variance across locations and years, seven types of stability parameters, correlation and canonical variate analyses were performed using MSTAT-C, AGROBASE 98 and SAS computer programmes. For the stability analyses, data of 10 varieties evaluated across six locations and three years (excluding the local checks) were analysed by following the procedures of: Francis and Kannenberg (1978) for the coefficient of variation, Finlay and Wilkenson (1963) and Eberhart and RusseIl (1966) for the joint regression, Wricke (1962) for ecovalence, Shukla (1972) for stability of variance, Lin and Binns (1978) for cultivars' superiority measure, Nassar and Huehn (1978) for variance of ranks and Gauch and Zobel (1988) for AMMI stability model. Comparisons were also made among these different stability measurements. Canonical variate analyses were undertaken on SAS CANDISC programme (SAS Institute, 1982) to classify and describe the genotypes and their test localities. 3. The separate trial analyses for the three years have shown highly significant (P<O.Ol) differences among the genotypes for seed yield and most of the measured traits. Totally four regenerants outperformed the crosses in 1996 and most of them repeated their performance during the succeeding years. Across locations and years, Chilalo ranked first (1505 kg ha'), followed by three regenerants (RII-M20G, RIO-N27G and RII-NI266), with a yield ranging from 1414-1455 kg ha". The high yielding performance of the regenerants indicatestheir high potentials and good adaptability to the linseed growing environments of Ethiopia. In fact, R 11-M20G was already recommended for commercial production in Adet area in 1999. Among the locations, the highest yield of 2172 kg ha-I was obtained from Bekoji, followed by that of Kulumsa over the years, indicating the good potentials of these sites. The result also showed tremendous yield variations over locations and years, suggesting high G x E interactions. The average of ANOV A components over the three years showed that about 45% of the total variance was accounted for by blocks, 39% by genotypes and the remaining 16% was attributed to random errors. As higher variability for blocks was recorded at Holetta, Adet and Asasa, further analysis of environmental factors (edaphic and climatic) and close supervisions are needed. 4. The combined analysis of variance across locations showed highly significant (P<O.Ol) difference among the locations (L), genotypes (G) and their interactions for most of the measured traits, indicating high differential responses of the genotypes over the locations, due mainly to edaphic and climatic related factors. About 76-85% of the variance components was also attributed to locations, while the genotypes accounted for only 3-7% (nearly similar to that G x L component) over the three years. These indicate the confounding effects of environmental factors and thus necessity of stability analysis to select appropriate varieties for their required purposes. 5. The combined analysis of variance and the percentage of its components for the seed yield across years per location show highly significant (P<O.O 1) differences for the years, genotypes and their interactions at Bekoji, Holetta and Kulumsa. In contrast, Y x G interactions were not significant at Sinana, Adet and Asasa, indicating more yield stability over the three years at these sites than the others. The variance components of ANOV A indicate higher variabilty for years or growing seasons, ranging from 50% at Adet to 94%at Bekoji. This large seasonal variability may have been due mainly to the amount and distribution of rainfall, among other factors. Repeatability of the trials at Bekoji and Holetta was about 85% against the lowest of Asasa (48%). This also indicates the high level of environmental variations that needs further diagnosis either to adjust or cope along with them. 6. The combined analysis 'across locations, years and their interactions reveals highly significant differences (P<O.Ol) among the genotypes for all the measured traits, suggesting differential responses of the genotypes to their test environments. As significant G x E interactions tend to confound cultivar selection processes and create difficulties in identifying reliable varieties, stability analysis with appropriate statistical methods are required. The variance components of seed yield were estimated to about 55% for years, 26% for locations, 13% for Y x Linteractions, 3% for genotypes and the remaining 3% for the rest of interactions. Most of these interactions were highly significant due mainly to climatic; soil and biotic factors, and more in depth studies are needed for better understanding and further actions. As a general case, however, when G x E interaction is mainly caused by unpredictable environmental factors, such as year to year fluctuations in rainfall (like in this study), the breeder must try to develop stable varieties that can perform relatively good under a range of conditions. But if G x E interaction is due to predictable environmental factors, such as soil types and management practices, the plant breeder can develop either different varieties for different environments or broadly adapted varieties for a range of conditions. 7. The ANOVA of joint regression model for seed yield showed highly significant difference between the genotypes. According to this joint regression, R 12-Nl OD was found the most stable genotype, followed by P136IIxl0314D and Chilalo (the highest yielder across the environments). All these stable varieties also had higher coefficients of determination, which were significantly correlated with the coefficient of regression and deviation from the regression. NorLin was also non-significantly different from the coefficient of regression and thus had general adaptability to diverse environments. The coefficient of variability also showed similar results.8. According to Wricke's (1962) ecovalence, RII-M20G followed by Rl1-N1266, R12- NIOD and P13611xl0314D were the most stable genotypes. The first three genotypes were the regenerants of tissue culture, whereas the fourth was one of the crosses developed at Holetta Research Center. Chilalo, NorLin, R12-D33C and P136lIxl0314B were categorised as intermediate in stability, unlike RI0-N27G and DI2-D24C that were found unstable according to this stability measurement. 9. Shukla' s stability variance (1972) showed that R12-NI0D, PI3611xl0314D and Chilalo were the most stable genotypes, while D12-D24C, RII-NI266 and RII-M20G were classified as the least stable. R 12-N IOD, the regenerant from NorLin was the most stable genotype as measured by both ecovalence and stability variance. Join regression was also in close agreement with these results. 10. Lin and Binns's (1988a) cultivars' superiority measure indicated Chilalo, RI0-N27G and RII-NI266 were the most stable genotypes, while 012-024C and P13611xl0314B were the least stable. In most cases, ranks of cultivar superiority measure were in harmony with the ranks of varietal mean yield rather than with other stabil ity parameters. Il. Nassar and Huehn' s (1978) non-parametric measure of stabi Iity revealed that R 12-N 100 had the smallest changes in ranks and thus was the most stable regenerant unlike D12- 024C, which was significantly unstable. The next more stable varieties were P13611xl03140 and Chilalo. This result was in agreement with most of the above stability measurements. 12. Additive main effects and multiplicative interaction's (AMMI) stability value, and scores of the interaction principal component analysis (IPCA) indicated that RI2-N 1OD, P1361Ixl0314D, RI2-D33C and Chilalo were relatively the most stable genotypes across the tested environments of Ethiopia. On the other hand, R11-N1266, RI0-N27G and Norlin were specifically adapted to low or unfavorable conditions, according to these parameters. AMMI model has been widely and successfully used during the past few years to analyse and understand the G x E interactions and stability in many crops. Since it combines the analysis of variance and principal components analysis in one model, it describes adequately both the G x E interaction and stability analysis through its response patterns. 13. Comparison of the seven stability parameters has shown that the coefficient of variability, Shukla's (1972) stability variance, Nasser and Huehn's (1978) variance of ranks and AMMl's stability value (ASY) were harmonious in detecting the most stable genotype, RI2-NIOD. Ecovalence and deviation from regression also revealed this genotype as one of the stable varieties and only cultivars superiority measure categorised it in the intermediate stability group. The same was true to with the second most stable variety (PI361Ixl0314D). In general, AMMI, Eberhart and Russell's (1966) deviation from regression, Nasser and Huehn's (1978) variance of ranks and Shukla's (1972) stability variance were found very useful in determining the comparative stability of linseed genotypes considered in this study. The coefficient of variability and ecovalence were also relatively better than the cultivar's superiority measure. All in all, the seven parameters detected R12-NIOD, PI361lxl0314D and Chilalo as the most stable varieties, and R12- D24C, RIO-N27G and P13611xl0314B as unstable ones, while the rest were intermediate between these two groups. However, repeatability study is needed to determine the best parameter. 14. The evaluation oil content and oil yield indicated that the highest location mean of 38.26% was obtained from Holetta, followed by that of Bekoji (36.6%). Of the genotypes, R 12- D33C and R12-D24C gave the highest of about 37.4% across the localities. R12-NIOD was also good in its oil percentage, like its seed yield. These varieties should, therefore, be used in the crossing programme to improve the oil contents. The analyses of variance for both oil content and oil yield across locations and years indicated highly significant difference (P<O.OI) between the genotypes. The variance components across locations and years also depicted higher variability for years, locations, and genotypes and for their interactions in this order. J 5. The assessment of agronomic characters revealed that the genotypes took 75 and 139 days to reach the flowering and maturity stages, respectively. The early flowered entries have also matured earlier than others after 134 days, unlike the late maturing ones that took up to 144 days. RII-NI266, RIO-N27G, RI2-N10D and NorLin were among the early maturing group, while R11-M20G, PI361Ixl0314D and the local checks were late maturing. The two crosses were found more susceptible to powdery mildew, while RI2-D33C, RI2-D24C, RII-M20G and Chilalo were relatively resistant to powdery mildew and pasmo diseases. 16. The correlation among the measured characters showed highly significant (P<O.OI) positive correlations between oil yield and seed yield (r = 0.924), oil yield and plant height (r = 0.585), and oil yield and stand count (r = 0.656). Seed yield was, however, negatively affected by days to flowering and maturity, indicating the poor yielding ability of early maturing varieties. The same was true with seed yield and powdery mildew, and seed yield and lodging percent. Oil content was positively influenced by days to maturity, plant height and stand percentage, implying that late maturing and tall plants positively contribute to the oil content of linseed. Highly significant negative correlation was noted between the oil content, and powdery mildews, Fusarium wilt and pasmo, indicating the negative effects of these diseases oil content of linseed. 17. Linear discriminant analysis (canonical variate analysis) was used to classify and compare the 10 genotypes and their attributed variates. The first two canonical variates (CANl and CAN2) altogether accounted for 78.01% of the total variation among the groups of genotypes. The horizontal separation (CAN I) was accounted for about 60.63% of the total variation, while the vertical separation (CAN2) attributed for 17.38%. This vertical separation was mainly due to days to flowering, the score of powdery mildew and lodging percent. Days to flowering and lodging percentage played important roles in the horizontal separation as well. Horizontal separation that showed very highly significant contribution in the total variability was used in grouping the genotypes. R12-D33C and R12-D24C contrasted the most with the other genotypes, like P13611 xl 03140. R l2-D33C and Chilalo varieties were also dissimilar with most of other genotypes. P136llxl03l4D was very similar to Chilalo and the same was true for Rll-N1266 and P13611xl0314B. NorLin cultivar was very similar to R12-NlOD, the most stable variety that deserves a license for commercial production. In general, the 10 linseed genotypes were generally classified into two major categories, the genotypes with above mean values (i.e. positive values) and those with below mean values (i.e. negative ones). RI2-D33C, R12-D24C and Rl1-M20G were among the positive values were though the latter regenerant was largely deviated from the group and much more closer to the average. The second group of genotypes that had negative CANl values included Chilalo, P13611xl0314D, RI2-NI0D, NorLin, P13611xl0314B, RI0-N27G and RII-N1266. Nevertheless, RI2-NI0D and NorLin were slightly deviated from this group as they had relatively lower values. The percent of stand count, days to maturity and oil yield played major roles in identifying this second group. 18. The same 11 variates employed to describe the genotypes were also used here to explore the similarities and differences of the six locations. The first two canonical variates (CANl and CAN2) together accounted for 96.39% of the total variations among the locations. The horizontal separation significantly (P<0.05) accounted for 91.56% of the variability, while vertical separation was responsible for 4.83%. Thus, CANl was mainly considered in classifying these locations. Bekoji contrasted the most with other locations and has verified the long-standing truth of Bekoji site. It has been very suitable site for good performance of linseed by producing highest seed yield, up to 2.5 t ha". Bekoji was dissimilar to most of the other sites based on the seed yield variable. The mean yield obtained from this site was 1752 kg ha', exceeding the remaining localities by over 40%. Hence, the environment of Bekoji needs special strategy in terms of cultivar development and crop management practices to exploit the existing potentials more effectively. The other variates attributed to distinguish this location were oil content, stand percentage, the score of pasmo and percent of lodging and the same was true with Sinana. Asasa, with its highest negative value was also different, as it has been known for its unreliable rainfall and terminal drought. Asasa was dissimilar to most of the other sites based on its oil yield and Fusarium wilt percentage though it was relatively closer to Adet. Kulumsa showed contrasting negative values with Sinana, both being equally closer to the mean value in the opposite directions. Like Asasa, Kulumsa was discriminated by the oil yield and wilt percentage. Kulumsa has a relatively warmer climate and fertile soils that are conducive for good crop growth and development, resulting in high percentage of lodging. It was also conducive for the development of wilt, powdery mildew and pasmo diseases and it can be used as one of disease screening sites. Sinana scored positively above average and differed from the other sites. This result reflects the existing environment of Sinana, as it has a very different agro-ecology, bimodal and erratic rainfall distribution. The area has got two growing seasons per annum, unlike the other research centers. Holetta scored a negative value, which was very closer to the average value and was ungrouped with any of the localities though Kulumsa was relatively closer to it. Holetta, like the other locations with negative values, was discriminated by the oil yield, wilt and other disease scores. These localities are, therefore, considered as proper sites for screening disease resistant and high oil yielding varieties. In short, the canonical discriminant analysis has confirmed the existence of adequate diversity among these six research centers, and opening some more sub-centers and testing sites are justifiable as far as the results of this study are concerned. However, additional studies are required for broader applications and to make use of the canonical discriminant analysis more effectively.
dc.description Afrikaans: 1. Die studie is gedoen om die relatiewe prestasie van ses lynsaad regenerante met twee krusings en drie standaard cultivars oor 18 lynsaad produserende omgewings van Etiopië te vergelyk vir 1996-1998. Die saad opbrengs en ander agronomies belangrike eienskappe is geanaliseer met verskillende statistiese prosedures om aanpassings potensiaal, G x E interaksies en saad stabiliteit te vergelyk. Die hoof doel van die studie was om die genotipes te vergelyk en te beskryf in hulle produksie areas met verskillende statistiese analises sodat sinvolle aanbevelings gemaak kan word vir die toekoms. Net so is kontemporêre studies op genotipes, omgewings, en hulle interaksies uitgevoer, en verskillende analitiese metodes van stabilitieits parameters is bespreek. 2. Afsonderlike en gekombineerde analise van variansie is gedoen oor omgewings en jare, sewe tipes stabiliteits parameters, korrelasie en kanoniese variant analise is gedoen met MSTAT-C, AGROBASE 98 en SAS rekenaar pakette. Vir die stabiliteits analises is data van 10 genotipes oor ses lokaliteite en drie jare (uitsluitend plaaslike standaarde) gedoen met die prosedures van: Francis en Kannenberg (1978) vir koeffisiente van variasie, Finlay en Wilkenson (1963) en Eberhardt en Russel (1966) vir gesamentlike regressie, Wricke (1962) vir ekovalensie, Shukla (1972) vir stabiliteit van variansie, Un en Binns (1978) vir cultivar superioriteit, Nasser en Huehn (1978) vir variansie van rangorde en Gauch en Zobel (1988) vir AMMI stabiliteit. Kanonies variaat analise is gedoen met SAS CANDISC (SAS Instituut, 1982) om genotipes te klassifiseer en te toets in hulle proef omgewings. 3. Die afsonderlike proefanalises vir die drie jare het hoogs betekenisvolle (p<0.01) verskille aangedui tussen genotipes vir saad opbrengs en feitlik alle ander eienskappe. Vier regenerante het beter presteer as kruisings van 1996, en meeste van hulle het dieselfde presteer in opvolgende jare. Oor omgewings en jare het Chilalo die beste presteer (1505 kg ha-l ) gevolg deur drie regenerante (R11-M20G, R10-N27G en R11-N1266) met opbrengste wat wissel van 1414- 1455 kg ha-l . Die goeie prestasie van regenerante toon hulle goeie potensiaal en goeie aanpassing in lynsaad produksie areas van Etiopië. Vir 'n feit is R11-M20G reeds aanbeveel vir kommersiële produksie in Adet vir 1999. Vir die omgewings is die beste opbrengs van 2172 kg ha-l aangeteken by Bekoji gevolg deur Kulumsa oor die jare, wat goeie potensiaal aandui vir hierdie omgewings. Die resultate het geweldige opbrengs variasies aangetoon oor omgewings en jare wat hoë GxE interaksies aangedui het. Die gemiddelde ANOVA komponente oor die drie jaar het aangetoon dat 45% van variasie deur herhalings veroorsaak word, 39% deur genotipes en die orige 16% deur foute. Omdat hoër variasie van herhalings aangedui is by Holetta, Adet en Asasa, is verdere analise van omgewings faktore nodig (edafies en klimatologies) en goeie toesig is nodig. 4. Die gekombineerde analise van variansie oor omgewings het hoogs betekenisvolle (p>0.01) verskille aangetoon tussen lokaliteite (L), genotipes (G) en hulle interaksie vir meeste van die gemete eienskappe, wat groot differensiële reaksie van genotipes oor omgewings aandui, hoofsaaklik a.g.v. edafiese en klimatologiese faktore. Ongeveer 76-85% van variansie komponente is veroorsaak deur omgewings, terwyl genotipes net 3-7% van variasie bygedra het (ongeveer dieselfde as die GxL komponent) oor die drie jaar. Dit het die baie groot invloed van die omgewing beklemtoon, en die nodigheid van stabiliteits analise om die regte genotipe vir die regte einddoel te kies. 5. Die gekombineerde analise van variansie en die persentasie van die komponente vir saad opbrengs oor jare per lokaliteit het hoogs betekenisvolle (p>0.01) verskille aangetoon vir genotipes en hulle interaksies by Bekoji, Holetta en Kulumsa. In kontras hiermee was jaar x genotipe interaksie interaksies nie betekenisvol by Sinana, Adet en Asasa, wat meer opbrengs stabiliteit oor die drie jare by hierdie omgewings aantoon. Die variansie komponente van die ANOVA toon hoër variabiliteit vir jare of groei seisoene wat wissel van 50% by Adet tot 94% by Bekoji. Hierdie groot seisoens variabiliteit kan wees a.g.v. die hoeveelheid en verspreiding van reenval, onder ander faktore. Die herhaalbaarheid van van proewe by Bekoji en Holetta was 85% teen die laagste by Asasa (48%). Dit toon ook die hoë vlak van omgewings variasie aan wat verdere diagnose benodig om of aan te pas of dit goed te bestuur. 6. Die gekombineerde analise oor lokaliteite, jare en hulle interaksies het hoogs betekenisvolle verskille (p>0.01) aangetoon tussen genotipes vir alle gemete eienskappe, wat differensiële respose van genotipes aantoon in hulle toets omgewings. Omdat betekenisvolle GxE interaksies cultivar seleksie bemoeilik, is stabiliteits analises noodsaaklik. Die variansie komponente van van saad opbrengs is bereken op 55% vir jare, 26% vir lokaliteite, 13% vir YxL interaksies en 3% vir genotipes en die orige 3% vir die res van die interaksies. Meeste vanhierdie interaksies was hoogs betekenisvol a.g.v. klimatiese, grond en biotiese faktore, en meer in diepte studies is nodig vir beter begrip hiervan en vir regstellende stappe. 7. Die ANOVA vir die gesamentlike regressie model vir saadopbrengs toon hoogs betekenisvolle verskille tussen genotipes. Volgens die regressie was R12-N10D die mees stabiele genotipe, gevolg deur P13611x10314D en Chilano (die hoogste produseerder oor alle omgewings). AI hierdie stabiele cultivars het ook hoër koeffisiënte van vasstelling gehad, wat weer sterk gekorreleer was met koeffisiënt van regressie en afwyking van die regressie. NorLin was ook nie betekenisvol verskillend van die koeffisiënt van regressie nie, en het dus algemene aanpasbaarheid gehad oor uiteenlopende omgewings. Die koeffisiënt van variabiliteit het dieselfde resultate getoon. 8. Volgens Wricke (1962) se ekovalensie, was R11-M20G gevolg deur R11-N1266, R12N10D en P13611x10314D die mees stabiele genotipes. Die eerste drie genotipes was regenerante van weefsel kultuur, en die vierde is 'n kruising wat by die Holetta Navorsings Sentrum ontwikkel is. Chilano, NorLin, R12-D33C en P13611x10314B is geklas as intermediêr stabiel, terwyl R10-N27G en D12-D24C onstabiel geklas is volgens hierdie metode. 9. Shukla se stabiliteits-analise (1972) het getoon dat R12-N1OD, P13611x10314D en Chilano die mees stabiele genotipes is, terwyl D12-D24C, R11-N1266 en R11- M20G as onstabiel geklassifiseer is. R12-N10D, die regenerant van NorLin was die mees stabiele genotipe soos gemeet deur beide ekovalensie en stabiliteits variansie. Gesamentlike regressie resultate het ook baie hiermee ooreengestem. 10. Lin en Binns (1988a) se cultivar superioriteits analise het aangetoon dat Chilano, R10-N27G en R11-N1266 die mees stabiele genotipes is terwyl D12-D24C en P13611x10314B die minste stabiel was. In meeste gevalle was die rangordes van cultivars vir superioriteit in harmonie met rangordes van variëteits gemiddelde opbrengste eerder as met ander stabiliteits parameters. 11. Nassar en Huehn (1987) se nie-parametriese meting van stabiliteit het aangetoon dat R12-N1ODdie kleinste verskil in rangorde toon, en dus die mees stabiel was. Die ander regenerant D12-D24C was onstabiel. Die ander stabiele cultivars was P13611x10314D en Chilano. Die resultate was in ooreenstemming met meeste van die ander stabiliteits analyses. 12. Additiewe hoof effek en veelvoudige interaksies (AMMI) stabiliteits analise en waardes van die interaksie hoof komponent analise (IPCA) het aangetoon dat R12-N10D, P13611x10314D, R12-D33C en Chilano die mees stabiele cultivars was oor die getoetsde omgewings in Etiopië. Aan die ander kant was R11-N1266, R10-N27G en Norlin aangepas vir swak omgewings. Die AMMI model is in die laaste paar jaar baie suksesvol gebruik om GxE interaksies en stabiliteit te analiseer en te verstaan in baie gewasse. Omdat dit die ANOVA en hoof komponent analise kombineer beskryf dit effektief die GxE interaksie en stabiliteit deur respons patrone. 13. Vergelyking van die sewe stabiliteits parameters het getoon dat koeffisiënt van variabiliteit, Shukla (1972) se stabiliteits variansie, Nasse en Huehn (1978) se variansie van rangordes en AMMI se stabiliteits waardes almal dieselfde stabiele cultivar, R12-N10D aangewys het. Ekovalensie en afwyking van regressie het ook hierdie genotipe as een van die stabiele cultivars aangewys, en net cultivar superioriteit het die cultivar as intermediêr stabiel geklas. Dieselfde was waar vir die tweede stabielste cultivar P13611x10314D. Oor die algemeen is AMMI, Eberhart en Russel (1966) se afwyking van regressie, Nasser en Huehn (1978) se variansie in rangordes en Shukla (1972) se stabiliteits variansie baie nuttig gevind om vergelykende stabiliteit te bepaal vir lynsaad cultivars getoets in hierdie studie. Die koeffisiënt van variabiliteit en ekovalensie was relatief beter as die cultivar superioriteits bepaling. In die geheel gesien, het die sewe gemete eienskappe R12-N10D, P13611x10314D en Chilano as stabiel aangetoon, en R12-D24C, R10-N27G en P13611x10314B as onstabiel. Die res was intermediêr tussen hierdie groepe. Herhaalbaarheids studies is nodig om die beste eienskap te bepaal. 14. Die evaluasie van olie inhoud en olie opbrengs het aangetoon dat die hoogste lokaliteits gemiddeld van 38.26% aangetoon is vir Holetta, gevolg deur Bekoji (36.6%). Van die genotipes het het R12-N1OD en R12-D24C die meeste olie (37.4%) gegee oor die lokaliteite. R12-N10D het ook goeie olie opbrengs gegee, soos saad opbrengs. Hierdie variëteite kan dus in 'n kruisings program gebruik word om olie opbrengs te verhoog. Die variansie analise vir beide olie opbrengs en inhoud oor lokaiteite en jare het hoogs betekenisvolle verskille (p<0.01) tussen genotipes aangetoon. Variansie komponente oor lokaliteite en jare het 15. Die bepaling van agronomiese eienskappe het aangetoon dat genotipes 75 en 139 dae gevat het om te blom, en volwassenheid, onderskeidelik, te bereik. Vroeg blommende variëteite was ook vroeg met volwassenheid, na 134 dae, terwyl die later cultivars tot 144 dae gevat het. R11-N1266, R10-N27G, R12- N10D en NorLin was vinnige cutivars, terwyl R11-M20G, P13611x10314D en die plaaslike standaarde langer groeiers was. Die twee kruisings was meer vatbaar vir poeieragtige meeldou, terwyl R12-D33C, R12-D24C, R11-M20G en Chilano relatief weestandbiedend was teen meeldou en pasmo siektes. 16. Die korrelasie tussen gemete eienskappe het hoogs betekenisvolle (p>0.01) positiewe korrelasies getoon tussen olie opbrengs en saad opbrengs (r=0.924), olie opbrengs en plant hoogte (r=0.585) en olie opbrengs en stand (r=0.656). Saad opbrengs was egter negatief beïnvloed deur dae tot blom en volwassenheid, wat aandui dat vinnig groeiende cultivars swak opbrengsvermoë het. Dieselfde was waar vir vir saad opbrengs en poeieragtige meeldou, en saadopbrengs en omval. Hoogs betekenisvolle negatiewe korrelasie is gekry tussen olie inhoud en meeldou, Fusarium verwelking en pasmo, wat aandui dat die siektes die olie inhoud van die lynsaad negatief beïnvloed. 17. Liniêre diskriminante analise (kanoniese variaat analise) is gebruik om 10 genotipeste vergelyk met hulle bydraende variate. The eerste twee kanoniese variate (CAN1 en CAN2) het 78.01% van alle variasie verklaar tussen groepe genotipes. Die horisontale skeiding (CAN1) het 60.63% van variasie verklaar, terwyl vertikale skeiding (CAN2) 17.28% van variasie verklaar het. Vertikale skeiding was hoofsaaklik a.g.v. dae tot blom, poeieragtige meeldou en omval persentasie. Dae tot blom en omval het ook 'n belangrike rol gespeel in horisontale skeiding. Horisontale skeiding wat betekenisvolle bydrae getoon het tot totale variabiliteit is gebruik om genotipes te groepeer. R12-D33C en R12- D24C het die meeste met ander genotipes gekontrasteer soos P13611x10314D. R12-D33C en Chilano was die mees verskillend van ander genotipes. P13611x10314D was baie dieselfde as Chilano en dieselfde was waar vir R11- N1266 en P13611x10314B. NorLin was baie dieselfde as R12-N10D. In die algemeen is die 10 lynsaad cultivars in twee groepe ingedeel, die genotipes met bo gemiddelde waardes (positiewe waardes) en die met onder gemiddelde waardes (negatiewe waardes). R12-D33C, R12-D24C en R11-M20Ghet positiewe waardes gehad, alhoewellg. regenerant afgewyk het van die groep, en nader was aan die gemiddeld. Die tweede groep wat negatiewe CAN1 waardes gehad het, het ingesluit Chilano, P13611x10314D, R11-N1266, R12-N10D, NorLin, P13611x10314B, R10N27G en R11-N1266. R12-N10D en NorLin het effens afgewyk van die groep en het relatief lae waardes gehad. Persentasie stand, dae tot volwassenheid, en olie opbrengs het 'n groot rol gespeelom die tweede groep te identifiseer. 18. Dieselfde 11 eienokappe wat gebruik is om die genotipes te beskryf, is ook gebruik om te kyk na ooreenkomste en verskille tusen die ses lokaliteite. Die eerste twee kanoniese (CAN1 en CAN2) het saam 96.39% van variasie verklaar. Horisontale skeiding het betekenisvol (p<O.05) bygedra vir 91.56% van variasie, terwyl vertikale skeiding net 4.83% bygedra het. Dus het CAN1 hoofsaaklik die lokaliteite geklassifiseer. Bekoji het die meeste gekontrasteer met ander lokaliteite, wat bestaande kennis bevestig. Dit is 'n baie geskikte lokaliteit vir verbouiing van lynsaad en opbrengs is soveel as 2.5 t ha" . Bekoji was dus verksillend van alle lokaliteite vir saad opbrengs. Die gemiddelde opbrengs vir hierdie lokaliteit was 1752kg ha", wat meer as 40o/~van ander lokaliteite se produksie is. Dus sal Bekoji spesiale strategië benodig i.t.v. cultivar ontwikkeling en bestuurs praktyke om die bestaande potensiaal optimal te gebruik. Die ander variate wat hierdie lokaliteit ondeskei het was olie inhoud, stand, pasmo lesings en omval. Dieselfde was waar vir Sinana. Asasa, met die hoogste negatiewe waarde, was ook verskillend omdat dit bekend is vir onbetroubare reenval en terminale droogtes. Asasa het verskil van meeste lokaliteite op grond van olie opbrengs en Fusarium verwelking alhoewel dit relatief nader was aan Adet. Kulumsa het kontrasterende negatiewe waardes gewys met Sinana, waar beide nader was aan die gemiddeld in beide rigtings. Soos Asasa, was Kulumsa gediskrimineer deur olie opbrengs en verwelking. Kulumsa het 'n relatief warmer klimaat en vrugbare gronde wat goed is vir gewas ontwikkeling en groei, wat hoë persentasies omval veroorsaak. Dit was ook voordelig vir verwelking, poeieragtige meeldou en pasmo siekte en kan gebruik word vir siekte evaluasie. Sinana het bo gemiddelde waardes gehad wat verskil het van ander lokaliteite. Hierdie resultate reflekteer die omgewing, omdat dit agro-ekologies verskillend is, bimodaal en onbetroubare reenval het. Hierdie area het ook twee groeiseisoene per jaar wat verskil van ander lokaliteite. Holetta, soos ander lokaliteite met negatiewe waardes, is onderskei met olie opbrengs, verwelk siekte en andersiekte waardes. In kort het die kanoniese diskriminante analise die bestaan van genoeg variasie aangetoon vir die ses navorsings stasies, meer substasies en toets areas salook van nut wees volgens hierdie resultate.
dc.description Agricultural Research and Training Project office (ARTP)
dc.language en
dc.publisher University of the Free State
dc.rights University of the Free State
dc.subject Plant tissue culture
dc.subject Flax -- Breeding -- Ethiopia
dc.subject Crop improvement -- Ethiopia
dc.subject Dissertation (M.Sc.Agric. (Plant Breeding))--University of the Free State, 2000
dc.title Assessment of tissue culture derived regenerants of linseed (Linum usitatissimus L.) in Ethiopia
dc.type Dissertation

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