Correlation analysis is used to understand the relationships existing between yield and yield components. Path coefficient analysis has been suggested to separate correlation coefficient into direct and indirect effects. In sesame, path analysis has used to identify traits that have significant effects on seed yield. In the present experiment, Thirteen sesame genotypes were grown during Rabi Summer’2019 at Agricultural College and Research Institute, Kudumiyanmalai (Tamil Nadu Agricultural University) taken to assess genotypic, phenotypic correlation and direct and indirect effects of yield traits on yield. The biometrical and morphological traits such as days to fifty percent flowering, plant height, number of branches, number of capsules per plant, seeds per capsule, thousand seed weight, seed yield per plant and plot yield. The result showed significant differences among the accessions in most of the traits studied. This indicates that sufficient variability is present for most of the important characters among different genotypes. Correlation and path analysis revealed that the characters viz., number of seeds/capsule and plant height have positive direct effect along with significant positive correlation with seed yield whereas the character days to fifty flowering showed significant negative association with seed yield. Therefore, these characters can be considered as a criterion for improving seed yield in breeding programs of sesame.

The evaluation of phenotypic variability, heritability, genetic advance and diversity in germplasm collections is important for both plant breeders and germplasm curators to optimize the use of the variability available. In the present study, Thirteen sesame genotypes were grown during Rabi Summer’2019 at Agricultural College and Research Institute, Kudumiyanmalai (TNAU) taken to assess genotypic, phenotypic variability and heritability coupled with genetic advance. The biometrical and morphological traits such as days to fifty percent flowering, plant height, number of branches, number of capsules per plant, seeds per capsule, thousand seed weight, seed yield per plant and plot yield. The GCV and PCV estimates were found to be high for seed yield per plant, number of capsules per plant and number of branches per plant. High heritability coupled with high genetic advance was observed for the characters seed yield per plant, number of seeds per capsule, number of capsules per plant, number of primary branches per plant and plant height. This indicated the additive genes governed these traits and the improvement could be brought about by selection for these traits. Therefore, these characters can be considered as a criterion for improving seed yield in breeding programs of sesame.

This trial conducted on twenty seven elite lines were used for the studies of correlation and path coefficient analysis with twelve yield and attributing traits. The experiment was operated at Agriculture Farm, Nana Ji Deshmukh New Agriculture Campus, Mahatma Gandhi Chitrakoot Gramodaya Vishwavidyalaya, Chitrakoot, Satna (M.P.). The field lay out was done in Randomized Block Design with 3 replications. Correlation coefficient for seed yield (kg/ha) revealed that highly significant and positive association with seed yield per plot and number of seeds per capsule. The direct effect on dependent variable (seed yield (kg/ha)) showed highly positive and significant by No. of seeds / capsule (0.661) followed by No. of capsules / plant (0.524), Oil content (0.181) and 1000 seed weight (0.117). The highest positive and direct effect on seed yield per plot at phenotypic level was recorded by No. of capsules per plant (0.148). therefore, selection of these characters would be effective for further breeding purpose of sesame.

Aims: Evaluation of correlation between yield and yield contributing traits in Sesame, as well as to determine their direct and indirect effects on fruit yield of sesame genotypes. Study Design: Randomized block design (RBD) with two replications. Place and Duration of Study: Oilseeds Research Station, Department of genetics and plant breeding, College of Agriculture, VNMKV, Latur (MS), between July 2016 and January2017. Methodology: For statistical analysis mean values are used. SPSS version 17.0 and GENRES were used to perform the correlation and path analysis using Sixty five accessions and evaluated for the following eleven traits: days to 50% flowering (D50%), days to maturity (DM), capsule length (CL), capsule width (CW), plant height (PH), number of branches per plant (NBP),number of capsules per plant (NCP),number of seeds per capsule (NSC),1000-seed weight (1000SW), oil content (OC), seed yield per plant (SYP). Results: The correlation analysis indicated that CL (0.237), PH...

Pakistan is facing severe scarcity of edible oil and spending a huge amount of foreign exchange on its annual import. Sesame is the best option as an edible oilseed crop due to less water requirement. The present study was conducted to estimate the genetic variability and trait association among 13 sesame genotypes in research area of Oilseeds Research Institute (AARI), Faisalabad, Pakistan during the crop season 2014. The data were subjected to analysis of variance, correlation and path analysis. Analysis of variance showed that genotypes differed highly significantly from each other for all the characters. Plant height, branches per plant and capsules per plant showed high mean values. Yield per plant had highly significant positive correlation of all other traits both at genotypic and phenotypic level. Path analysis revealed that capsules per plant had highest direct effect on seed yield per plant and Seeds per capsules had highest indirect effect via capsules per plant on seed yield per plant. So the trait capsules per plant may be used as selection criteria for the improvement of seed yield of sesame.

Pakistan is facing severe scarcity of edible oil and spending a huge amount of foreign exchange on its annual import. Sesame is the best option as an edible oilseed crop due to less water requirement. Various statistical analyses are used to test the contribution of different yield related traits for developing high yield potential cultivars. Correlation analysis illustrates the association among different yield related traits exist in plant population under study. Genotypic and phenotypic coefficients of variability reveal the extent of differences among the accessions, due to the genetic factors and their response to environmental condition of the experiment. Path coefficient analysis reveals the relationship between variables in multivariable system is considered. Previous studies of various sesame breeders proved that plant height, number of branches per plant, capsules per plant, seeds per capsules, 1000-seed weight are the traits which have significant and positive correlations with yield per plant at both genotypic and phenotypic levels. These characters also have high path analysis values especially capsules per plant had highest direct effect on seed yield followed by 1000-seed weight. So, these traits may be used as selection criteria in future breeding programs for the improvement of seed yield of sesame.

The present study conducted an analysis of genetic variability for components traits of seed yield in 20 sesame (Sesamum indicum L.) genotypes at the Research Farm of S.K.N. College of Agriculture, Jobner. The experiment followed a randomized block design with three replications during kharif, 2018. The main objective of this study was to assess the genetic variability among the genotypes. The results of analysis of variance (ANOVA) showed significant genotypic variation for all traits, indicating their potential for breeding programs. In the present study, RT - 384, RMT - 447 and RMT - 486 were identified as high yielding genotypes with per plant seed yield of 6.75, 6.7 and 6.01 g, respectively. Among the traits studied, plant height exhibited the highest variability with range of 83.13 to 108.40 cm, while test weight had the least variability having range of 3.00 - 3.51 g. Furthermore, phenotypic coefficients of variation (PCV) were higher than genotypic coefficients of variation ...