Dr. K.B. EswariK. VIJAYA KUMAR2024-09-252024-09-252024-01-12https://krishikosh.egranth.ac.in/handle/1/5810214962Pearl millet (Pennisetum glaucum (L.) R. Br. syn. Cenchrus americanus (L.) Morrone) is a climate-resilient crop grown in the arid and semi-arid areas of the world. It is the most widely grown millet species, accounting for approximately half of the total worldwide production of millets. It can grow on poor soils with little or no inputs and it has resistance or tolerance to many crop diseases and pests and can survive in adverse climatic conditions. Pearl millet also known for nutritional security as it is the rich source of Fe and Zn content. Pearl millet is most useful crop because of its nutritional potential, multipurpose use as feed and fodder and as climate change ready crop with its ability to sustain in harsh environmental conditions like drought and heat, has enormous potential to give higher returns in marginal environments for poor farmers. Plant breeders are constantly challenged to come up with new breeding techniques to maximise selection gain per year. In large segregating material, it is critical to select the best genotypes which act as parental lines in hybrid development programs. Here breeders apply different selection strategies to screen and select best parental lines. These strategies may be by the conventional approaches based on phenotypic data only or/and by molecular approaches, where exploiting the same phenotypic data by adding information from molecular markers. The present investigation was carried out during summer-2020 to kharif-2021 at International Crops Research Institute for the Semi-arid Tropics (ICRISAT), Hyderabad. The objective of the study was to compare selection methods based on phenotypic and genomic information to derive hybrid parental lines having high productivity and better nutritional traits, to investigate the optimum number of testers required to select superior hybrid parental lines and to identify heterosis and combining ability effects of hybrid parental lines. 21 A study was conducted to compare selection efficiency of four selection methods for selection of superior hybrid parental lines for grain yield and nutritional traits. Among them general combining ability (gca), per se performance and visual selection methods were phenotypic information-based selection methods and genomic selection is genotypic information-based section method. The study was conducted on two sets of hybrid parental lines, which consist of 72 seed parental (B) lines (Set-I) and 73 restorer (R) lines (Set-II). These parental lines were crossed with 2 respective testers, generated hybrids and parental lines were evaluated in multilocation trials. Parental lines were genotyped by t-GBS technique with 1217 mid density SNP markers. The breeding values of parental lines were estimated by genomic best linear unbiased prediction (GBLUP) model. Prediction accuracy of the model was ranged between 0.21 to 0.87. In both sets, from each selection method, top 10% lines were selected and crossed with 5 testers and generated hybrids were evaluated in diverse agroclimatic zones. The selection efficiency of methods was determined 1) by comparing the mean performance of the top five (5), ten (10), twenty (20), and all hybrids developed by each selection method 2) by comparing line contribution by each selection method in top performing hybrids and 3) by cost-benefit analysis. Comparison of mean performance revealed that in all four comparison groups (top 5, 10, 20, and all hybrids) of set-I and set-II, hybrids developed by general combining ability (GCA) performed better than other selection methods. In set-I, hybrids developed by visual selection method showed superior performance after GCA and in set-II, genomic selection showed superior performance after GCA. A paired t-test was conducted to check the significant difference between selection methods for mean grain yield performance of top 5, 10, 20 and all hybrids advanced by the four selection methods. In Set-I, in all groups (top 5, 10, 20 and all hybrids advanced by methods) no significant difference between selection methods was observed. Whereas as in Set-II, except in all hybrids group, 1) no significant difference between general combining ability and genomic selection, 2) no significant difference between per se performance and agronomic score, 3) significant difference between GCA and GS methods with per se performance and visual selection methods was observed. These results suggest that selection efficiency of all four selection methods is similar, but among the four methods, selection efficiency of genomic selection and GCA may be similar and superior to per se performance and visual selection methods. Rank correlation analysis between selection methods in both Set-I (B-lines) and Set-II (R-lines) revealed 1) significant positive correlation between genomic selection and general combining ability methods 2) significant positive correlation between per se performance and visual selection methods 3) no correlation between GS and GCA methods with per se performance and visual selection methods. This result also supports the similar selection efficiency of GS and GCA selection methods. Cost benefit analysis indicated that initial implementation of genomic selection costs more compared to other selection methods due to requirement of both genotypic and phenotypic data to train the model. Once the model is available then only genotypic data is sufficient to estimate the breeding value of parental lines so cost involved in genomic selection will be reduced drastically. Then genomic selection would be 74% cheaper than GCA method. The visual selection method is the most affordable method among the four selection strategies. Comparison of three selection methods (gca, per se performance and genomic selection) for combination of grain yield and grain Fe content was done in seventy-two (72) seed parental lines (B-lines). Top 10% lines from each method with the combination of grain yield and Fe content was selected and crossed with 5 testers and generated hybrids were evaluated in four locations. It was observed that in all three 22 comparison groups (top 5, 10 and all hybrids) for grain yield, hybrids generated by general combing ability performed best compared to other selection methods, whereas for grain Fe content in each comparison group not much difference was observed between selection methods. This result suggests that for grain yield, selection efficiency of general combining ability is higher followed by per se performance and genomic selection, but for grain Fe content, selection efficiency of all three methods is similar. Cost-benefit analysis for grain yield and Fe content revealed that initially genomic selection costs more compared to other selection methods, because of the requirement of phenotypic and genotypic data, once the model is trained genomic selection would be 89% cheaper than gca. Then GS will be the most cost-effective selection method for selection of parental lines for both grain yield and nutritional traits. Optimum number of testers study was conducted to find out the number of testers required from a set of 5 testers for selection of parental lines. With different possible combinations of 5 testers, 31 testcross combinations were framed. Based on mean grain yield performance of hybrids, top 10 lines from each of 31 combinations were selected. It was observed that 4 B-lines (line 1, 13, 16 and 17) in Set-I and 3 R lines (line 1, 2, 5) in Set-II were commonly selected in across testcross combinations. Based on mean grain yield hybrid performance, top 5 lines from 5 tester combination were selected. Then these lines were compared for their presence in top 5 lines of testcross combinations of each tester group. In Set-I, the average chance of selecting top 5 lines of 5 tester combination by one, two, three and four tester groups are 56%, 66%, 76% and 92% respectively, whereas in Set-II, average chance observed as 52%, 62%, 74% and 84% respectively. Correlation analysis between mean grain yield of testcross combinations in both sets revealed the less correlation of single tester combinations with two or more tester combinations, but two or more tester group combinations showed more significant positive correlation with other testcross combinations. Line x tester biplot analysis was done to estimate the discriminating ability of 5 R-line testers in Set-I and 5 B-line testers in Set-II for grain yield, grain Fe content and Zn content. Based on vector length in biplot graph, in Set I, following testers have higher discriminating ability: ICMR 1203 and ICMR 14888 for grain yield, ICMR 1202 and ICMR 15222 for grain Fe content, and ICMR 1203 and ICMR 15222 for grain Zn content. In case of Set II, following testers have higher discriminating ability: ICMB 04999 and ICMB 1508 for grain yield, ICMB 04999 and ICMB 98222 for grain Fe content, and ICMB 04999 and ICMB 1508 for grain Zn content. Combining ability and standard heterosis study was conducted in two stages of material using line x tester analysis. Stage-I comprised of 84 B-lines and 75 R-lines, which were crossed with 2 testers and stage-II comprised of 22 B-lines and 25 R-lines, which were crossed with 5 testers. Generated hybrids were evaluated in four locations. The analysis of variance for combining ability in both stages revealed the presence of significant difference among the lines, testers and their hybrids for all the traits under the study. In stage-I, out of 84 B-lines, 15 lines for grain yield, 29 for grain Fe content and 20 lines for Zn content, 29 lines for days to 50% flowering, 25 lines for plant height and 14 lines for 1000-seed weight have shown significant GCA effects in desirable direction. Among them, ICMB 101716 and ICMB 18777 were found to be good combiners for grain yield, grain Fe and Zn content. Out of 75 R-lines, 24 lines for days to 50% flowering, 24 lines for plant height, 12 lines for 1000-seed weight, 23 lines for grain yield, 32 lines for Fe content and 19 lines for Zn content showed significant GCA effects in desirable direction. Among them, ICMR 100152 and ICMR 102502 were identified as promising lines with significant GCA effects for all the traits except for days to 50% flowering. Four lines (ICMR 1701, ICMR 1907, ICMR 100152, and ICMR 23 102502) have shown significant GCA effects for grain yield, grain Fe content and Zn content. In stage-II, out of 22 B-lines, 9 lines for days to 50% flowering, 9 lines for plant height, 6 lines for 1000-seed weight, 7 lines for grain yield, 6 lines for Fe content and 5 lines for Zn content were as significant good combiners in desired direction. ICMB 101810 was found to be as promising line with significant GCA effects for all traits except Fe content. ICMB 101793 has shown significant GCA effects for grain yield and grain Fe content along with other agronomic traits. Out of 25 R-lines, 8 lines for days to 50% flowering, 11 lines for plant height, 7 lines for 1000-seed weight, 5 lines for grain yield, 12 lines for Fe content and 7 lines for Zn content showed significant GCA effects in desired direction. Parental lines ICMR 101206 and ICMR 102502 are promising lines with significant GCA effects for grain yield, Fe content and Zn content. Across two stages, 7 parental lines including 3 B-lines (ICMB 101810, ICMB 101793 and ICMB 17333) and 4 R-lines (ICMR 101206, ICMR 102502, ICMR 102506 and ICMR 102149) were significant good combiners for grain yield, nutritional and agronomic traits. An estimation of SCA effects of crosses in pooled analysis revealed that in stage-I, hybrids ICMA 19222 x ICMR 1202 and ICMA 101790 x ICMR 1203 were observed as best hybrid combinations with significant positive SCA effects for grain yield. For grain Fe and Zn content, 27 and 12 hybrid combinations showed significant positive SCA effects respectively. Hybrid, ICMA 04999 x ICMR 100048 has been identified as best combination with significant SCA effects for grain yield, Fe content, days to 50% flowering and 1000-seed weight. Five hybrids, ICMA 04999 x ICMR 100048, ICMA 04999 x ICMR 1804, ICMA 04999 x ICMR 15555, ICMA 04999 x ICMR 100004 and ICMA 04999 x ICMR 102503 have significant SCA effects for both grain yield and Fe content. In stage-II, out of 103 B-line hybrids, 8 hybrids showed significant positive SCA effects for at least 2 traits along with grain yield. Hybrid ICMA 101780 x ICMR 14888 is the best combination with significant positive SCA effects for grain yield, plant height and 1000-seed weight. Out of 115 R-line hybrids, 5 crosses for days to 50% flowering, 18 crosses for plant height, 6 crosses for 1000-seed weight, 18 crosses for grain yield, 11 crosses for grain Fe content and 9 crosses for Zn content showed significant SCA effects in desirable direction. Among them 8 crosses showed significant positive SCA effects for at least two traits along with grain yield. Standard heterosis analysis revealed that in stage-I out of 168 B-line hybrids, for grain yield, 5 hybrids (ICMA 101795 x ICMR 1203, ICMA 101838 x ICMR 1202, ICMA 17333 x ICMR 1203, ICMA 101828 x ICMR 1203 and ICMA 101832 x ICMR 1203) showed positive standard heterosis over 86M84, 10 hybrids showed positive standard heterosis over Kaveri super boss and 31 crosses showed significant positive standard heterosis over ICMH 1202. For grain Fe content, 8 hybrids showed significant positive standard heterosis over ICMH 1202 which is the major check for Fe and Zn content. In stage II, out of 103 B-line hybrids for grain yield, 6 hybrids showed significant positive standard heterosis for grain yield over ICMH 1203. Hybrids ICMA 101794 x ICMR 1202 and ICMA 101780 x ICMR 1203 showed significant positive standard heterosis over ICMH 1203 for Fe content and Zn content respectively. Out of 115 R-line hybrids for grain yield, 7 hybrids over 86M84, one hybrid over Kaveri Super Boss and 8 hybrids over MP7171 showed positive standard heterosis and 5 hybrids showed significant positive standard heterosis over ICMH 1203. For grain Fe content, 24 23 hybrids showed positive standard heterosis and no hybrid showed significant positive standard heterosis over ICMH 1203. For Zn content 3 hybrids (ICMA 1508 x ICMR 102149, ICMB 98222 x ICMR 102149 and ICMA1 98222 x ICMR 102503) showed significant positive standard heterosis for grain Zn content over ICMH 1203. These promising hybrids and parental lines will be further tested for combination of yield and nutritional superiority and used in line breeding and hybrid development in ICRISAT pearl millet breeding program.EnglishThesis