Wheat is the world's most important crop that excels all other cereal crops both in area and production, thereby providing about 20.0 per cent of total food calories for the people of the world. The experiment was conducted at Research Farm, IGKV, Raipur during Rabi 2013-14. Chhattisgarh is located in the east -central part of the country between 17°14'N and 24°45' N latitudes and 73°30' E and 84°15' E longitudes, whereas Raipur the capital of the Chhattisgarh state, lies at 21°16' N latitude and 81°36' E longitude with an altitude of 289.60 meters above sea level. All Twenty two genotypes were grown in Randomized Block Design with three replications. Correlation studies give a clear picture of characters association which is generally due to linkage, pleiotrophy, physiological association in developmental and biochemical pathway The phenotypic and genotypic correlations were determined among seed yield and its components in possible character combinations. In Correlation coefficient analysis, seed yield per plant exhibited highly significant positive correlations with number of seeds per spike and number of seeds per plant at both genotypic and phenotypic levels, whereas number of seeds per spikelet at the genotypic level.
Molecular characterization of germplasm accessions of rice revealed genetic polymorphism and ensured unambiguous identification. A total of 24 SSR markers were used covering all the chromosomes of rice for their molecular characterization and discrimination. After analysis of the data generated, a total of 69 alleles were detected in 24 accessions of rice. The number of alleles per locus generated by each marker ranged from 1 to 6 alleles with an average number of 2.87 alleles per locus. The highest number of alleles ( 6) was detected in the locus RM 22565 while, lowest number of alleles (1) detected on each of locus OSR 13, RM 431, RM 454 and Xa5s. The PIC value ranged from 0.00 (OSR 13, RM 431, RM 454 and Xa5s) to 0.76 (RM 12146). Microsatellite markers (SSR) are also used to detect the genetic similarity of germplasm accessions of rice. The genetic similarity coefficient ranged from 0.24 to 1.00 as revealed by UPGMA cluster analysis using the 24 SSR markers. A total of five distinct groups resulted at a cut-off similarity coefficient of 0.46 among the 24 rice accessions, below which the similarity values narrowed conspicuously. Coefficient of similarity revealed that the rice accessions of cluster I were genetically distant from cluster IV. Thus, Peeleeluchai (135131) and Mahuwadeta Lal of cluster I; whereas, Kadamphool and Ram Karoni of cluster IV seems to be promising and should be utilized in hybridization programme. Molecular markers like RM 1, RM 12146, RM 215, RM 22710 RM 154 and RM 25 could potentially be used for molecular characterization of rice germplasm accessions from various sources on the basis of polymorphic reactions and high PIC values.
Using line x tester mating design with three CMS lines and seven elite testers, the general combining ability (GCA) of parents and specific combining ability (SCA) of crosses were carried out for grain yield and its attributes. The SCA variance was greater than the GCA variance for grain yield and yield components, suggesting the preponderance of dominance and epistatic gene action in expression of these traits. The line CRMS 31 A and IR 79156 A were recorded as good combiners for head rice recovery percent. The tester NPT 80-1 was good general combiner for grain yield per plant and TOX 981-11-2-3 for both grain yield per plant and head rice recovery percent. The cross combinations APMS 6 A/ET 1-13, CRMS 31 A/ET 1-12, and IR 79156 A/ NP T 80-1 were found to be outstanding with respect to grain yield per plant, head rice recovery percent, and spikelets per panicle. The cross APMS 6 A/NPT 2-2-694- 1 was good combiner for head rice recovery percent. These promising lines, testers, and crosses revealed wide scope for enhancing the grain yield in the CMS line or three line breeding system based rice improvement programme to develop rice hybrids. DOI: http://dx.doi.org/10.3329/bjar.v37i4.14376 Bangladesh J. Agril. Res. 37(4): 583-592, December 2012
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.