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Title of Thesis

Abdul Ghafoor
Institute/University/Department Details
Department of Biological Sciences/ Quaid-i-Azam University, Islamabad
Biological Sciences
Number of Pages
Keywords (Extracted from title, table of contents and abstract of thesis)
vigna mungo, blackgram, mm5-60, mm3340, korea, mash1, mm 33-40/9105, mash 1/mm 5-60, 9106/mm 33-40, 9104/mm 33-40, mm 33-40/9104, korea/mm 33-40, mash 1/mm 33-40, sds-page, random amplified polymorphic dna, rapd

Blackgram (Vigna mungo L.) germplasm consisting 484 accessions was evaluated for qualitative and quantitative characters alongwith investigations regarding harvest index. Out of this material, a representative sample consisting of 111 accessions was used for cluster and principal component analyses based on morphological and biochemical techniques (SDSPAGE for seed proteins). Biochemical markers were also used for detection of QTLs in blackgram germplasm. Forty two accessions, selected on the basis of geographic origin were analyzed for cluster and PCA to investigate association between morphologica1 biochemical and geographic parameters. Forty pure-lines of Vigna spp. were analyzed for morphological and biochemical (seed protein & RAPD) characters to study cluster analysis and association between morphological and biochemical genetic diversity. Finally inheritance of quantitative and qualitative traits were investigated in F 1 and F2 populations involving diverse parents. In germplasm evaluation, high variation was observed for days to flowering, maturity, branches, pods, biological yield, grain yield and harvest index. For pod length, seeds per pod and seed weight, low variance was observed and hence improvement for these traits seemed to be difficult in the local germplasm used in present study. MYMV was associated with all the characters under study except with seeds/pod, seed weight and harvest index where it was insignificant. The decrease in branches was 12.20%, in pods 15.40%, in biomass 14.07% and grain yield 13.93%. From the germplasm analyzed, accessions with best performance for individual characters were identified which are suggested to be exploited for their genetic potential in future breeding programme. Highest selection scores were observed for harvest index ranging from 30.1 to 35.0% followed by 25.1 to 30.0%, and hence 25.1-35.0% harvest index would be one of the criteria for future selection. Keeping in view the results regarding ID and other statistics, 50 high yielding accessions/genotypes have been identified for further use. In a representative sample consisting of 111 genotypes, genetic variance was observed for quantitative characters and seed protein. Out of 29 protein subunits, 20 were polymorphic and 9 were monomorphic. On the basis of banding pattern, gel was divided into four regions and first three regions were used for recording data. SDS-PAGE provided a powerful tool for germplasm discrimination based on genetic differences in seed storage protein comparison in blackgram. SDS-PAGE was also observed important for preliminary detection of QTLs. Out of 240 combinations for detection of QTLs, 24 were observed significant in detection of QTLs and hence could be used for screening purposes. PCA and cluster analyses based on quantitative traits proved to be best method for grouping accessions for specific traits to select desirable parents for breeding programme. Data analysed for geographic distribution based on provinces, altitude and crop-ecological zones revealed that among all three geographic parameters, 16 accessions out of 42, which were about 40% of the total, grouped together on the basis of provincial distribution only. The separation on the basis of PC1 and PC2 for provincial distribution revealed 5 groups. Forty selected pure-lines of Vigna spp. were analysed for RAPD, SDS-PAGE and quantitative traits which revealed that SDS-PAGE proved to be a powerful tool for differentiating Vigna radiata and Vigna mungo, whereas within Vigna mungo a low level of genetic diversity was observed and no clear differentiation was exhibited either for agronomic characteristics or origin as various clusters consisted of mixed genotypes from different origins. Out of 53 primers, 46 revealed amplification and out of these, 36 exhibited polymorphism and hence could be used for Vigna DNA fingerprinting. SDS-PAGE and RAPD exhibited high relationship which indicated that both these biochemical markers could be used for studying inter-specific genetic diversity among Vigna spp. Grouping of 40 genotypes on the basis of three parameters revealed that Vigna radiata was quite different in biochemical analyses (RAPD & SDS-PAGE), whereas one V radiata (45727) was related to V. mungo based on quantitative traits. All 40 genotype shared grouping for all three parameters (morphological, SDS-PAGE & RAPD) and it was observed that 8 genotypes out of 40 (20%) shared all three groups. Cluster analysis showed that many genotypes from same origins were grouped separately or vice versa. Eleven parents (9010, 9024, 9025, 9102, 9104, 9105, 9106, MM 5-60, MM 3340, Korea & Mash 1) were used to study inheritance of qualitative characters like, pubescence, seed coat colour, presence of spot on the seed and pod colour. All four qualitative characters revealed monogenic nature of inheritance segregating in Mendelian 3: 1 ratio. The hairiness pattern was observed dominant over non-hairiness; brown seed coat colour dominant over green seed coat colour. Presence of spots on seed coat was dominant to absence of spots and black pods were dominant over brown pods in blackgram. Seven hybrids (MM 33-40/9105, Mash 1/MM 5-60, 9106/MM 33-40, 9104/MM 33-40, MM 33-40/9104, Korea/MM 33-40 and Mash 1/MM 33-40) revealed strong linkage between spots on seed coat and pod colour in the present research material and suggested to be used for preliminary mapping in blackgram. Results regarding inheritance of quantitative traits indicated the presence of both additive and non-additive genetic variation, but the magnitude varied. The major portion of GCA variance was observed for seed weight only, whereas for all other characters, SCA or Reciprocal variance contributed more towards genetic variance. Genotype "9020" produced the highest GCA effects for pods, pod length, seeds/pod, seed weight, biomass and grain yield; Mash 1 was best general combiner for plant height; Mash 3 best for branches and 9026 proved to be the best general combiner for pods/branch and H1. The genotype "9026" gave negative GCA effects for most of the characters (plant height, branches, pods, seed weight, biological yield and grain yield) but it exhibited best general combiner for pods/branch and m. In the present investigation it can be concluded that hybrids involving genotypes 9020, Mash 1 and 9026 could be examined carefully for selection in the proceeding generations to select superior transgressive segregants.

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S. No. Chapter Title of the Chapters Page Size (KB)
1 0 Contents 0
260.24 KB
2 1 Introduction 1
76.51 KB
3 2 Review Of Literature 6
275.48 KB
  2.1 Morphological Characters 6
  2.2 Biochemical Analysis 11
  2.3 Inheritance 21
4 3 Material And Methods 26
246.82 KB
  3.1 Genetic Diversity Based on Morphological Characters 26
  3.2 Biochemical (SDS-PAGE) Basis of Genetic Diversity 29
  3.3 Geographic Distribution Pattern in Relation With Morphological and Biochemical Traits 32
  3.4 Detection of Genetic Variation by Random Amplified Polymorphic DNA. 35
  3.5 Inheritance 38
5 4 Results 41
2100.18 KB
  4.1 Genetic Diversity Based on Morphological Characters 41
  4.2 Biochemical (SDS-PAGE) Basis of Genetic Diversity 64
  4.3 Geographic Distribution 91
  4.4 Random Amplified Polymorphic DNA (RAPD ) 118
  4.5 Inheritance 142
6 5 Discussion 166
395.26 KB
  5.1 Genetic Diversity Based on Morphological Characters 166
  5.2 SDS-PAGE and its Significance in Determining QTLs 172
  5.3 Geographic Distribution 178
  5.4 Randomly Amplified Polymorphic DNA (RAPD) Analysis 180
  5.5 Inheritance 186
7 6 Conclusion 194
71.32 KB
8 7 Recommendations 198
301.54 KB
  7.1 Literature Cited 202
9 8 .Appendix I 225
298.35 KB
  8.1 APPENDIX II 226
  8.2 APPENDIX III 230
  8.3 APPENDIX IV 234