Assessing Diversity of Sesame Genotypes Using Cluster Analysis and Principal Component Analysis

Gupta, Deepak Kumar; Muralia, Suresh; Khandelwal, Vikas; Nehra, Anju

doi:10.20546/ijcmas.2021.1001.038

Cited by 3 publications

(5 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Section: Resultssupporting

confidence: 91%

“…The number of primary and secondary branches and increase in basal leaf area contributed to the increase in seeds per capsule in a positive direction. Similar results were reported bySingh et al (2018),Baraki et al (2020) and DeepakGupta et al (2021). The important yield traits both through correlation and PCA analyses showed a negative association with days to maturity which was also observed byBaraki et al (2020).…”

supporting

confidence: 88%

See 1 more Smart Citation

Assessment of genetic variability for seed yield and its components in sesame (Sesamum indicum L.) based on multivariate analysis

2022

EJPB

View full text Add to dashboard Cite

Sesame is an important oilseed crop in India. The productivity of sesame is considerably low owing to several production challenges. Developing high yielding varieties with resistance to biotic and abiotic stresses remains a major goal in sesame breeding. In this study, a total of 55 sesame genotypes were evaluated for 16 quantitative traits related to seed yield. Genetic relationship and variability in the genotypes were assessed based on correlation, principal component analysis (PCA) and cluster analysis. The results showed that seed yield had a high positive correlation with the number of capsules per plant and a high negative correlation with days to maturity. The PCA revealed six components contributing to the total variance, which were components 1 (plant height, the number of primary branches, leaf length and leaf width), 2 (seed yield per plant and thousand seed weight in the positive direction and days to maturity in the negative direction), 3 (days to flower initiation and days to 50 per cent flowering), 4 (capsule width and seeds per capsule), 5 (the number of capsules per plant) and 6 (the number of seeds per capsule) in the order of importance. Cluster analysis showed five clusters of genotypes in accordance with the phenotypic traits. Overall results indicated that the number of capsules per plant, the number of seeds per capsule and thousand seed weights were the most critical traits for selecting high yielding genotypes in sesame.

show abstract

Section: Resultssupporting

confidence: 91%

supporting

confidence: 88%

Assessment of genetic variability for seed yield and its components in sesame (Sesamum indicum L.) based on multivariate analysis

2022

EJPB

View full text Add to dashboard Cite

show abstract

“…Inter-correlation among the traits showed that days to 50% flowering showed significant and positive association with days to 80% physiological maturity, stem height from base to first branch, capsule length, oil content and protein content and negative association with internodal length, 1000-seeds weight and stover yield per plant at genotypic level while at phenotypic level it showed significant association with days to 80% physiological maturity, oil content and protein content. These results were in agreement with Gupta et al (2021) for days to 80% physiological maturity; Takele et al (2021) for days to maturity and oil content. Significant and positive association of days to 80% physiological maturity was observed with only two traits viz.…”

Section: Resultssupporting

confidence: 91%

“…Hence, direct selection for these traits may lead to development of high yielding genotypes of sesame. These results are in confrontation with Singh and Bisen (2018), Lalpantluangi and Shah (2018) for number of capsules per plant at genotypic level and for plant height, number of branches per plant at phenotypic level; Singh et al (2020) and Takele et al (2021) for number of capsules per plant, the number of branches per plant, plant height and harvest index; Patil and Lokesha (2018), Navaneetha et al (2019), Saravanan et al (2020) for number of capsules per plant, plant height and number of branches per plant; Abate et al (2018) for plant height, number of capsules per plant, stover yield/plant and harvest index; Haibru et al (2018), Singh et al (2018) and Disowja et al(2020) for number ofcapsules per plant, plant height; Gupta et al (2021) for harvest index; Singh et al (2018) for number of capsules per plant; Abhijatha et al (2017), Patil and Lokesha (2018), Jamir et al (2020) and Kumar et al (2022) for number of capsules per plant, number of branches per plant; Ravitej et al (2019) and Sasipriya et al (2022) for number of capsules per plant, number of branches per plant both at phenotypic and genotypic level; Abdou et al (2015) for harvest index, number of branches per plant, this relation indicates that the best yield was obtained with highly branched plants because capsules number increases with the degree of branching and thus ultimately increase seed production.…”

Section: S245mentioning

confidence: 99%

Trait Association and path coefficient analysis for yield and yield attributing traits in Sesame (Sesamum indicum L.)

Kumari¹,

Shah²

2023

EEC

View full text Add to dashboard Cite

Correlation and path analysis were carried out in 36 diverse genotypes of sesame collected from different parts of the country along with North-East region of India for local landraces. Analysis of variance indicated the presence of good amount of genetic variability among the genotypes under study. Correlation studies indicated that seed yield per plant was significantly and positively associated with traits, i.e. plant height, internodal length, number of capsules per plant, number of branches per plant, stover yield per plant and harvest index both at genotypic and phenotypic levels which indicate the importance of these traits in selection for enhancing the seed yield. Path analysis revealed that maximum positive direct effect on seed yield per plant was imposed by days to 80% physiological maturity, internodal length, capsule length, stem height from base to first branch, stover yield per plant, harvest index, relative water content, oil content and protein content both at genotypic and phenotypic levels. This indicate that these are the real independent characters and they have maximum contribution towards increase in the seed yield per plant.

show abstract

“…To know which trait or combination of traits would mitigate stress better, it is necessary to find a group of principal traits which can be obtained by principal component analysis (PCA) [ 91 ]. PCA showed that PC1 and PC2 are the important principal components as they contributed to the maximum variance in both optimal (63.62%) and stress conditions (75.62%), with an eigen value of more than one, which implies that the traits have a narrow angle in PC1 and PC2, and which may be used for indirect selection of the genotypes to mitigate the stress by creating better genetic recombinants [ 3 , 92 , 93 ]. However, most of the traits which are necessary for the survival of seedlings were showing positive correlation with H 2 O 2 and MDA in optimal condition, and had shown negative correlation in stress conditions.…”

Section: Discussionmentioning

confidence: 99%

Deciphering Physio-Biochemical Basis of Tolerance Mechanism for Sesame (Sesamum indicum L.) Genotypes under Waterlogging Stress at Early Vegetative Stage

Chugh,

Mishra,

Sharma

et al. 2024

Plants

View full text Add to dashboard Cite

Waterlogging represents a substantial agricultural concern, inducing harmful impacts on crop development and productivity. In the present study, 142 diverse sesame genotypes were examined during the early vegetative phase to assess their response under waterlogging conditions. Based on the severity of symptoms observed, 2 genotypes were classified as highly tolerant, 66 as moderately tolerant, 69 as susceptible, and 5 as highly susceptible. Subsequent investigation focused on four genotypes, i.e., two highly tolerant (JLT-8 and GP-70) and two highly susceptible (R-III-F6 and EC-335003). These genotypes were subjected to incremental stress periods (0 h, 24 h, 48 h, 72 h, and 96 h) to elucidate the biochemical basis of tolerance mechanisms. Each experiment was conducted as a randomized split-plot design with three replications, and the statistical significance of the treatment differences was determined using the one-way analysis of variance (ANOVA) followed by the Fisher least significant difference (LSD) test at p ≤ 0.05. The influence of waterlogging stress on morphological growth was detrimental for both tolerant and susceptible genotypes, with more severe consequences observed in the latter. Although adventitious roots were observed in both sets of genotypes above flooding levels, the tolerant genotypes exhibited a more rapid and vigorous development of these roots after 48 h of stress exposure. Tolerant genotypes displayed higher tolerance coefficients compared to susceptible genotypes. Furthermore, tolerant genotypes maintained elevated antioxidant potential, thereby minimizing oxidative stress. Conversely, susceptible genotypes exhibited higher accumulation of hydrogen peroxide (H2O2) and malondialdehyde content. Photosynthetic efficiency was reduced in all genotypes after 24 h of stress treatment, with a particularly drastic reduction in susceptible genotypes compared to their tolerant counterparts. Tolerant genotypes exhibited significantly higher activities of anaerobic metabolism enzymes, enabling prolonged survival under waterlogging conditions. Increase in proline content was observed in all the genotypes indicating the cellular osmotic balance adjustments in response to stress exposure. Consequently, the robust antioxidant potential and efficient anaerobic metabolism observed in the tolerant genotypes served as key mechanisms enabling their resilience to short-term waterlogging exposure. These findings underscore the promising potential of specific sesame genotypes in enhancing crop resilience against waterlogging stress, offering valuable insights for agricultural practices and breeding programs.

show abstract

Assessing Diversity of Sesame Genotypes Using Cluster Analysis and Principal Component Analysis

Cited by 3 publications

References 8 publications

Assessment of genetic variability for seed yield and its components in sesame (Sesamum indicum L.) based on multivariate analysis

Assessment of genetic variability for seed yield and its components in sesame (Sesamum indicum L.) based on multivariate analysis

Trait Association and path coefficient analysis for yield and yield attributing traits in Sesame (Sesamum indicum L.)

Deciphering Physio-Biochemical Basis of Tolerance Mechanism for Sesame (Sesamum indicum L.) Genotypes under Waterlogging Stress at Early Vegetative Stage

Contact Info

Product

Resources

About