Genetic diversity analysis in American cotton (<i>Gossypium hirsutum</i> L.)

Naik, B. Mansingh; Satish, Y; Babu, D. Ratna

doi:10.5958/0975-928x.2016.00137.x

Cited by 9 publications

(9 citation statements)

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“…High heritability (83.76%) coupled with high genetic advance as per cent of mean (23.69%) was observed for plant height. It was in accordance with the findings of Vinodhana et al, (2013), Pujer et al, (2014), Naik et al, (2016), Shao et al, (2016), Khokher et al, (2017 and Adsare and Salve (2017).…”

Section: Resultssupporting

confidence: 92%

“…The GCV and PCV values were found to be higher and the difference between them is high indicating a major influence of environment over the phenotypic development of the trait. The results were in confirmation with those reported by Vineela et al, (2013), Latif et al, (2015), Dahiphale et al, (2015), Naik et al, (2016) and Khokher et al, (2017).…”

Section: Resultssupporting

confidence: 91%

“…Hence direct selection may be effective. Similar findings were also reported by Dinakaran et al, (2012), Pujer et al, (2014), Naik et al, (2016), Adsare and Salve (2017) and Khokher et al, (2017).…”

Section: Resultssupporting

confidence: 88%

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Genetic variability studies for yield, yield attributing and fibre quality traits in cotton (Gossypium hirsutum L.)

uti¹,

Sowmya²,

J.M.³

et al. 2019

Int.J.Curr.Microbiol.App.Sci

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Section: Resultssupporting

confidence: 92%

Section: Resultssupporting

confidence: 91%

See 1 more Smart Citation

Genetic variability studies for yield, yield attributing and fibre quality traits in cotton (Gossypium hirsutum L.)

uti¹,

Sowmya²,

J.M.³

et al. 2019

Int.J.Curr.Microbiol.App.Sci

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“…The PCA scores for 40 black gram genotypes in the first three principal components were computed and were considered as three axes as X, Y and Z and squared distance of each genotype from these three axes were calculated (Table 2). 2014 [11] in finger millet; Naik et al, 2016 [12] in cotton; Priya et al, 2017 [13] in rice; Ayesha and Babu., 2018 [14] in foxtail millet and Priya et al, 2019 [15] in mung bean to indicate the successful hybrid combination to obtain superior hybrids or transgressive segregants depending on the gene action guiding different traits.…”

Section: Resultsmentioning

confidence: 99%

Principal components of genetic diversity in black gram [Vigna mungo (L.) Hepper]

Ayesha¹,

Babu²,

Rajesh³

et al. 2021

Pharma Innovation

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Forty black gram [Vigna mungo (L.) Hepper] genotypes were evaluated using principal component analysis to estimate the extent of genetic diversity for ten different yield and its component traits. The first three principal components viz., PC I, PC II and PC III with eigen values more than one contributed around 80% of the variability for the genotypes studied. PC I contributed 46.834% towards variability and the traits responsible for its contribution are viz., number of clusters per plant, grain yield per plant, number of branches per plant and number of seeds per pod. The second axis (PC II) contributed 18.951% variability and variation at this axis is due to the accumulated genetic variation of traits viz., days to 50% flowering, days to maturity, grain yield per plant and number of clusters per plant. While PC III and PC IV accumulated 13.807% and 5.765% respectively. Therefore on a cumulative note, first four axes contributed about 85.357% of total variance among 10 characters for all the forty genotypes under study. In the current investigation, four lines (TU 94-2, PU 31, IPU 94-1 and LBG 623) are identified from the depicted 2D & 3D figures as diverse genotypes, which may yield transgressive segregants or heterotic F1s based on nature of gene action of the trait in question.

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“…Cluster IX has the maximum mean value for traits viz., the number of clusters per plant, the number of pods per plant, pod length, test weight and grain yield per plant. Similar usage of genetic distance analysis through Mahalanobis' D 2 statistics (Tocher's method) in obtaining the respective cluster diagram and dendrogram to understand the genetic diversity was earlier employed in various crops (Naik et al, 2016 in American cotton; Gowsalya et al, 2017 in blackgram;Shivani et al, 2018 in rice; of the cluster with a high inter-cluster gap and a high mean value for key traits are likely to be more promising.…”

Section: Fig 2 Intra and Inter-cluster Distance Of 40 Blackgram Genotypes In Ten Clusters Based On Tocher's Methodsmentioning

confidence: 99%

Estimation of genetic distances among various genotypes of blackgram (Vigna mungo (L.) Hepper) using D2 statistics

2021

EJPB

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The genetic distance assessment of forty blackgram genotypes was conducted employing Mahalanobis' D 2 statistics considering ten quantitative characters. All the studied genotypes were grouped in ten discrete clusters, among which cluster I was indeed the largest with thirteen genotypes followed by cluster V with eight genotypes, cluster IV with seven genotypes and cluster II with five genotypes. Cluster IX was digenotypic, other clusters III, VI, VII, VIII and X were all solitary. Cluster IV and IX had the greatest inter-cluster gap followed by cluster VIII and IX, clusters VII and IX, clusters II and IX, clusters III and IX, clusters V and IV, clusters IX and Cluster X and between cluster VI and IX, implying that a successful breeding programme can be begun by selecting diverse lines to improve productivity and other yield-related traits. In the current investigation, cluster X, cluster VI, cluster IV and cluster VIII were considered divergent enough and found to be the best. Hence, genotypes from these clusters viz., TU 94-2 from cluster IX, PU 31 from cluster VI, IPU 94-1 from cluster IV and LBG 623 from cluster VIII can be used in the crossing programme for additional genetic enhancement. Cluster IX had the highest mean score for traits viz., the number of clusters per plant, the number of pods per plant, pod length, test weight and grain yield per plant. The number of pods per plant provided the most to genetic diversity succeeded by the number of clusters per plant, days to maturity, plant height, pod length and test weight. As a result, in a crossing programme, selecting and utilising genotypes based on these traits will be more rewarding. Furthermore, taking into account the genotype disposition in various clusters, one can perform different possible crosses to produce heterotic hybrids or transgressive segregants, based on the nature of gene action regulating the traits.

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Genetic diversity analysis in American cotton (Gossypium hirsutum L.)

Cited by 9 publications

References 0 publications

Genetic variability studies for yield, yield attributing and fibre quality traits in cotton (Gossypium hirsutum L.)

Genetic variability studies for yield, yield attributing and fibre quality traits in cotton (Gossypium hirsutum L.)

Principal components of genetic diversity in black gram [Vigna mungo (L.) Hepper]

Estimation of genetic distances among various genotypes of blackgram (Vigna mungo (L.) Hepper) using D2 statistics

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