Background: Asian soybean rust caused by PhakopsorapachyrhiziSyd. is a major threat for production and expansion of soybean in India. Understanding the nature of inheritance of rust resistance in DSb 21 will help in estimating the number of genes involved in governing the resistance mechanism and thus will be helpful in designing a suitable breeding method. Methods: Utilizing JS 335 and EC 241778, in a long term breeding programme, a highly rust resistant variety, DSb 21 has been released from University of Agricultural Sciences Dharwad, Karnataka. To study the genetics of rust resistance in DSb 21, F2 and F3 generation of two crosses involving susceptible x resistant (JS 335 x EC 241778) and resistant x susceptible (DSb 21 x JS 335) were used. Result: The F2 segregation analysis in both the crosses revealed the same segregation ratio of three resistant to one susceptible phenotype based on chi square test indicating rust resistance is controlled by a single dominant gene. In both the crosses the F2 results were confirmed by studying the F3 progenies for reaction to rust.
The experimental material for the present study comprised of 28 inbred lines (including two checks) which were developed by mutation and hybridization among the lines from AICRP trials MARS, UAS, Dharwad and on the basis of SPAD readings and stay green nature, they were considered as drought tolerant lines. These lines were used for the present experiment and were evaluated under both normal and moisture stress condition in rain out shelter to study their root characteristics. Among 28 inbreds evaluated, eight inbred lines i.e. DSR-13, DSR-19, DSR-23, DSR-24, DSR-37, DSR-66, DSR-107 and DSR-132 were identified as drought tolerant nature which exhibited least reduction in their yield under moisture stress condition. Simultaneously hybridization programme was also initiated during summer 2018 using these 28 inbred lines as testers (males) and 5 CMS lines as female lines in Line × Tester fashion. Among 140 hybrids developed, only 40 F1 hybrid combinations were further analyzed for heterosis and combining ability studies along with four checks RHA 6D-1, RHA 95C-1, KBSH-53 and Cauvery Champ. Most of the hybrid combinations showed significant negative heterosis for flowering indicating earliness, and also all the combinations showed a positive heterosis for plant height indicating tallness dominant over dwarf checks. The combinations CMS 7-1-1 A × DSR-37 (624 kg/ha), CMS-853A × DSR-19 (624 kg/ha), and CMS-853A × DSR-23 (619 kg/ha) exhibited significant maximum heterosis for seed yield (kg ha−1) over the checks KBSH-53 (496.50 kg/ha) and Cauvery Champ (486.50 kg/ha) showing maximum seed yield per hectare.
Background: Sunflower crop being a highly cross pollinated with high yield potential, can be grown in all seasons with its suitability in variety of inter and series cropping systems due to its photo insensitive nature and can be adapted to a variety of environmental conditions also. So keeping in mind of its potential and future use, research was conducted with available lines to study PCA and its diversity that might be used in hybridization programmes.
Methods: The 45 lines of sunflower were grown in a randomised block design with three replications at the Research Farm, Department of Genetics and Plant Breeding, College of Agriculture, Vijayapur during summer 2018-19 for study on principal component analysis and diversity analysis.
Result: At the genotypic stage, the analysis of variance showed highly significant variations among the genotypes for all of the characters. Whereas Divergence analysis using principal component analysis and hierarchical cluster analysis has been shown to be effective in determining which genetically distant parents should be used for hybridization. Divergence in genotypes were divided into nine major groups or clusters and out of nine components, four components had more than one eigen value (Table-2). The first principal component explained 33.40 per cent of total variation, while the second, third, fourth, fifth, sixth, seventh, eighth and ninth principal components explained 23.30, 14.10, 11.19, 6.30, 4.90, 3.60, 1.90 and 0.60 per cent, respectively.
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