Study of Genetic Divergence in Lowland Rice Genotypes of Bihar

Kushwaha, Nitesh; Kant, Ravi; Kumar, Rajesh; jaya, Nilan; Chhaya, Ruchika; Sinha, Naincy; Singh, Digvijay; Mohanty, Tushar Arun

doi:10.20546/ijcmas.2020.902.011

Cited by 6 publications

(7 citation statements)

References 2 publications

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“…The contribution of remaining traits in manifestation of genetic divergence was low or zero. Similar observation was recorded by (Anderson, 1957;Rao, 1952 [2,16,14,17,8,22,9] .…”

Section: Resultssupporting

confidence: 87%

“…Maximum genetic distance was observed between the parents WLS and G18, whereas minimum distance was observed between the parents VL111 and S8481. Similar findings were reported by (Farzana Jabeen et al, 2007;Nehvi et al, 2008;Singh et al, 2019; Kushwaha et al, 2020) [7,14,22,9] in case of maize. The contribution of traits under study towards divergence is summarized in Table 5.0.…”

Section: Resultssupporting

confidence: 86%

“…Genetic diversity is generally associated with geographical diversity, but the former is not necessarily directly related with geographical distribution. A comparison of the mean values of ten traits for different clusters showed considerable differences among them (Table 2 [20,11,1,22,9] . The highest inter cluster distance (Table 3.0) was recorded between cluster II and III (4.88) followed by cluster I and III (4.67).…”

Section: Resultsmentioning

confidence: 99%

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Assessment of genetic diversity in inbred lines of maize (Zea mays L.) and its relationship with heterosis

Suman¹,

Kumar²,

Kumar³

et al. 2020

Int. J. Chem. Stud.

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The genetic divergence among thirteen genotypes of maize were estimated by using Mahalanobis D 2 statistic for ten characters. The genotypes were grouped into three clusters. Cluster I comprised 11 parental genotypes (CLQR, VL111, R4093, R6429, S8481, S8200, CML490, HK1, WLS, CLQRC and G18), while Cluster II (CLQ25) and III (CG18) were mono-genotypic. The highest inter cluster distance was recorded between cluster II and III (4.88) followed by cluster I and III (4.67). Maximum genetic distance was observed between the parents WLS and G18, whereas minimum distance was observed between the parents VL111 and S8481 suggesting more variability in genetic makeup of the genotypes included in these clusters. Cluster I comprising of 11 genotypes have maximum mean values for number of kernels per row and number of kernels row per cob while minimum mean values for plant height and ear height. Cluster II containing only CLQ25 have maximum mean values for ear girth and grain yield per plant. The highest contribution in the manifestation of total genetic divergence was exhibited by grain yield per plant (28.63%) followed by ear girth (28.47%), ear length (19.23%), number of kernel per row (11.50), number of kernels row per cob (10.04). Out of 30 crosses, 11 crosses showed positive significant heterobeltiosis for grain yield per plant. The crosses CLQ25 × CLQR and WLS × R4093 belongs to high divergent class. It could be concluded that genetic diversity can be utilized as a reliable parameter for predicting heterosis in hybrids.

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“…The contribution of remaining traits in manifestation of genetic divergence was low or zero. Similar observation was recorded by (Anderson, 1957;Rao, 1952 [2,16,14,17,8,22,9] .…”

Section: Resultssupporting

confidence: 87%

Section: Resultssupporting

confidence: 86%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Assessment of genetic diversity in inbred lines of maize (Zea mays L.) and its relationship with heterosis

Suman¹,

Kumar²,

Kumar³

et al. 2020

Int. J. Chem. Stud.

Self Cite

View full text Add to dashboard Cite

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“…The highest intra-cluster distance observed in cluster I which indicates that the germplasm of cluster I was more diverged than any other cluster. There was comparative divergence of one cluster from another and higher divergence seen between clusters III and IV (2717.76) followed by clusters I and IV(1760.59), selection of lines to use them as parents for hybridization programme from these clusters will result in unique genotypes and generation of promising crossed material as proposed by [1,4,[11][12][13][14][15][16][17][18].…”

Section: Resultsmentioning

confidence: 99%

Assessment of Genetic Diversity in Sesame (Sesamum indicum L.) Based on Agro-Morphological Traits

Mohanty

Singh

et al. 2020

CJAST

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Genetic divergence among parents is of paramount importance in selecting them for hybridization programme for crop improvement. Genetic divergence was assessed among 30 sesame genotypes which were evaluated in RBD with an objective to classify and understand the nature and magnitude of genetic diversity with regard to grain yield, yield components and quality traits using Mahalanobis D2 statistics. The genotypes differed significantly regarding the characters studied and displayed marked divergence and were grouped into four clusters following Tocher’s method. Cluster I had twenty-seven genotypes while the Cluster II, cluster III and cluster IV were monogenotypic comprised only one genotype each. The oil content exhibited maximum contribution towards divergence. The maximum inter cluster distance was recorded between cluster III and IV (2717.76) followed by cluster I and IV (1760.59), cluster II and III (991.96), cluster I and II (695.67), cluster I and III (637.32) and cluster II and IV (584.59) indicating the chances of getting high yielding recombinants would be better if the crosses are made among the genotypes of these groups under timely sown condition. The genotypes in cluster III and cluster IV, due to maximum inter cluster distance between them, exhibited high degree of genetic diversity and thus may be utilized under inter varietal hybridization programme (transgressive breeding) for getting high yielding recombinants. The analysis of divergence indicated significant differences among parental lines for all the agro-morphological characters. Based on results obtained in the present investigation, it is concluded that the allelic diversity can be used for future breeding program. The traits under study are largely associated with each other and should be taken into consideration either simultaneously or alone for selecting a high yielding sesame genotype.

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“…"Quantifying the level of divergence in experimental materials is highly valuable for identifying divergent genotypes that can be utilized in hybridization to generate new variations" [7]. The Mahalanobis D 2 [8] statistic has been widely recognized as a powerful tool for plant breeders to select suitable parental genotypes with a broader range of variability for various traits [9]. "The utilization of multivariate analysis tools like principal component analysis (PCA) has been found to be effective in assessing phenotypic diversity, identifying genetically distant Cluster s of genotypes, and selecting key traits that contribute to overall variation in genotypes.…”

Section: Introductionmentioning

confidence: 99%

Multivariate Analysis to Study Genetic Diversity for Yield and its Attributing Traits in Rice (Oryza sativa L.)

Kumar,

Vimal,

Meena

et al. 2024

IJECC

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The present investigation was carried out with 72 germplasm lines and three checks of rice (Oryza sativa L.) were grown at Crop Research Station, Masodha conducted in the GPB farm, Acharya Narendra Deva University of Agriculture and Technology, Kumarganj, Ayodhya (U.P.) during Kharif June 2022- February 2023. Data on 10 characters, including grain yield per plant focused on diversity and PCA analysis. This investigation involved the analysis of 72 rice germplasm lines alongside three checks, showcasing extensive variation in agronomic and morphological traits. The study utilized Non-hierarchical Euclidean cluster analysis to assess genetic diversity. The pseudo F-test determined the optimal grouping of 75 genotypes into six distinct clusters. Cluster distribution revealed varying genotype compositions, with Cluster V comprising the highest entries (20), followed by Clusters I, VI, and II. Intra- and inter-cluster distances illustrated significant variability among clusters, emphasizing genetic diversity. Examining agronomic traits across these clusters revealed noteworthy variations in days to 50% flowering, days to maturity, plant height, and productive tillers. Panicle length, flag leaf area, biological yield, harvest index, 1000-grain weight, and grain yield per plant also exhibited cluster-specific variations. These findings provide valuable insights for rice breeding programs, facilitating targeted enhancements of specific agronomic traits within the rice population, thus contributing to the development of more resilient and productive rice varieties.

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Study of Genetic Divergence in Lowland Rice Genotypes of Bihar

Cited by 6 publications

References 2 publications

Assessment of genetic diversity in inbred lines of maize (Zea mays L.) and its relationship with heterosis

Assessment of genetic diversity in inbred lines of maize (Zea mays L.) and its relationship with heterosis

Assessment of Genetic Diversity in Sesame (Sesamum indicum L.) Based on Agro-Morphological Traits

Multivariate Analysis to Study Genetic Diversity for Yield and its Attributing Traits in Rice (Oryza sativa L.)

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