scholarly journals Genetic Diversity Of Some Restorer Lines For Hybrid Rice Development

1970 ◽  
Vol 36 (1) ◽  
pp. 21-28 ◽  
Author(s):  
MU Kulsum ◽  
MJ Hasan ◽  
H Begum ◽  
MM Billah ◽  
H Rahman
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Genetic Divergence ◽  
Hybrid Rice ◽  
Principal Component ◽  
Component Analysis ◽  
Spikelet Fertility ◽  
Restorer Line ◽  
Panicle Length ◽  
Cluster Distance

Genetic divergence of thirty six restorer lines was studied through Mohalanobis’s D2 and principal component analysis for nine characters. Genotypes were grouped into five different clusters. Cluster III comprised of maximum number of genotypes (eleven) followed by cluster I and IV. The inter-cluster distance was maximum between clusters II and IV (14.064) indicating wide genetic diversity between these two clusters followed by the distance between cluster II and V (10.353), cluster III and cluster IV (8.588). The minimum inter- cluster distance was observed between cluster I and cluster III (2.885) followed by cluster I and cluster V (4.359) and cluster III and cluster V (4.825) indicating that the genotypes of these clusters were genetically close. The intra cluster distance in the entire five clusters was less, which indicated that the genotypes within the same cluster were closely related. Among the characters, number of tillers/hill, panicle length, number of filled spikelets/ panicle, spikelet fertility % and yield/plant contributed most for divergence in the studied genotypes. It indicates that these parameters can contribute more for yield in hybrid rice development.   Keywords: Rice; restorer line; genetic divergence; D2. DOI: http://dx.doi.org/10.3329/bjar.v36i1.9226 BJAR 2011; 36(1): 21-28

scholarly journals Genetic Divergence in Chickpea (Cicer arietinum L.)

2012 ◽  
Vol 37 (1) ◽  
pp. 129-136
Author(s):  
MA Syed ◽  
MR Islam ◽  
MS Hossain ◽  
MM Alam ◽  
MN Amin
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Cicer Arietinum ◽  
Genetic Divergence ◽  
Principal Component ◽  
Mean Value ◽  
Breeding Programs ◽  
Cicer Arietinum L ◽  
Cluster Distance ◽  
High Yielding Varieties

Genetic diversity of 27 chickpea genotypes was studied through Mahalanobis D2 and Principal Component analysis. The genotypes under study fall into five clusters. The cluster II contained the highest number of genotypes (11) and Cluster I contained the lowest. Cluster I produced the highest mean value for number of pods per plant. The inter cluster distances were much higher than the intra cluster distances. Cluster V exhibited the highest intra cluster distance while the lowest distance was observed in cluster I. The highest inter cluster distance was observed between cluster I and II while the lowest was between cluster III and V. Considering all the characters, it was suggested that the genotypes BD6549, BD6603, and BD6548 could used as parents for future breeding programs to develop high yielding varieties of chickpea. DOI: http://dx.doi.org/10.3329/bjar.v37i1.11184 Bangladesh J. Agril. Res. 37(1): 129-136, March 2012  

scholarly journals Genetic Diversity Studies in Drought Tolerant Rice (Oryza sativa L.) Genotypes

2021 ◽  
Author(s):  
A. Sheeba ◽  
S. Mohan
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Association Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Large Set ◽  
Panicle Length ◽  
Rice Varieties ◽  
Drought Tolerant ◽  
Rice Genotypes

Background: Assessing the genetic diversity and relationship among breeding materials isan invaluable aid for any crop improvement programme. Principal component analysis (PCA) is a multivariate statistical technique attempt to simplify and analyze the inter relationship among a large set of variables in term of a relatively a small set of variables or components without losing any essential information of original data set. Methods: The present investigation was carried out to study the genetic diversity and relationship among the sixty five rice genotypes including popular rice varieties of Tamil Nadu, drought tolerant rice varieties, aerobic rice genotypes and land races. These genotypes were raised at Rice Research Station, Tiruvallur, during kharif, 2015 in randomized block design with three replications under aerobic condition. Data on eight yield and yield attributing traits were recorded and subjected to principal component analysis and association analysis. Result: In principal component analysis, PC1accounted for 22.91% and PC2 accounted for 19.53% of the total variation. The traits panicle length, no. of grains per panicle, plant height, days to 50% flowering, no of productive tillers per plant from the first two principal components accounted for major contribution to the total variability. Cluster analysis grouped the genotypes into six discrete clusters. The association analysis revealed that the traits viz., no. of productive tillers/plant, panicle length and hundred seed weight had positive association with higher direct effect on plot yield which could be used as selection criteria for developing high yielding rice varieties. The results of the present study have revealed the high level of genetic variation existing in the genotypes studied and explains the traits contributing for this diversity.

scholarly journals Genetic divergence analysis of lime

1970 ◽  
Vol 7 (1) ◽  
pp. 33-37 ◽  
Author(s):  
MM Rahman ◽  
MAZ Al Munsur
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Distribution Pattern ◽  
Leaf Area ◽  
Genetic Divergence ◽  
Principal Component ◽  
Maximum Contribution ◽  
Cluster Distance ◽  
Minimum Number ◽  
Total Divergence

Genetic divergence of 40 lime accessions was estimated using D2 and principal component analysis. The genotypes under study fell into 6 clusters. The distribution pattern indicated that the maximum number of genotypes were included in cluster III and the minimum number in cluster VI. The inter cluster distance in most of the cases were higher than the intra cluster distance indicating wider genetic diversity among the accessions of different groups. The highest inter cluster distance was observed between cluster II and III (1568.51) followed by cluster II and VI (1223.72) showing wide diversity among the groups. The highest intra-cluster distance was observed for the cluster III and the lowest for the cluster VI. Leaf area and number of stamen showed maximum contribution towards total divergence among the genotypes. Keywords: Genetic Divergence; Lime; PCA; Genetic diversity DOI: 10.3329/jbau.v7i1.4795 J. Bangladesh Agril. Univ. 7(1): 33-37, 2009

scholarly journals Genetic Diversity of Drought Tolerant Upland Rice (Oryza sativa L.) Genotypes

2016 ◽  
Vol 13 (2) ◽  
pp. 133-139 ◽  
Author(s):  
S Hossain ◽  
M Salim ◽  
M S Akter ◽  
S Afroz ◽  
M S Noman
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Oryza Sativa ◽  
Genetic Divergence ◽  
Upland Rice ◽  
Oryza Sativa L ◽  
Principal Component ◽  
Drought Tolerant ◽  
Cluster Distance ◽  
Total Divergence

Genetic divergence of thirty three drought tolerant rice (Oryza sativa L.) genotypes were studied through Mohalanobis’s D2 and principal component analysis for twelve characters. The genotypes were grouped into seven clusters. The cluster I and II were comprised of the maximum number of genotypes (eight) in each followed by cluster V containing five genotypes. The highest inter-cluster distance was in between cluster III and I (368.64) indicating a wide genetic diversity between these two clusters followed by clusters VII and III (346.04). The lowest inter-cluster distance was in between cluster IV and II (42.46) followed by cluster VI and IV (63.29) indicating that the genotypes of these clusters were genetically close. The intra cluster distance in the entire seven clusters was less, which indicate that the genotypes within the same clusters were closely related. Considering the magnitude of genetic distance, contribution of different characters towards the total divergence and magnitude of cluster means for different characters performance, BR 7391-2B-7, BR 7392-2B-25, BR 6855-2B-11-3-4, BR 6855-2B-11-3-5  from cluster I, genotypes BR 6976-2B-15, and Morichbati from cluster III, genotypes BR 7187-2B-2-5 from cluster IV, genotype BR 7187-2B-2-3 and BR 7181-2B-35-2 from cluster V and genotypes BR 6855-2B-11-3-7 and BRRI dhan 42 from the cluster VII are likely to perform better if used in hybridization program.The Agriculturists 2015; 13(2) 133-139

scholarly journals GENETIC DIVERSITY IN VEGETABLE PEA (Pisum sativum L.)

2013 ◽  
Vol 26 (1) ◽  
pp. 35-40
Author(s):  
M. Rahman ◽  
M. Hasan ◽  
R. N. Chowdhury ◽  
N. A. Ivy ◽  
M. M. Hossain
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Pisum Sativum ◽  
Genetic Divergence ◽  
Principal Component ◽  
Reducing Sugar ◽  
Pisum Sativum L ◽  
Close Relationship ◽  
Cluster Distance ◽  
Minimum Number

An investigation was carried out to identify the extent of genetic divergence of seventeen vegetable pea genotypes at the Bangabandhu Sheikh Mujibur Rahman Agricultural University, Bangladesh. Genetic divergence was estimated using D2 and principal component analysis. The genotypes under study fell into 4 clusters. The distribution pattern indicated that the maximum numbers of genotypes (6) were included in cluster II and cluster III and the minimum number in cluster IV (1). The inter-cluster distance was higher than the intra-cluster distance which indicated wider genetic diversity among the accessions of different groups. The highest inter-cluster distance was observed between II and IV. The lowest inter-cluster distance was observed between clusters II and III suggesting a close relationship among the genotypes of these two clusters. The highest intra-cluster distance was observed for the cluster II. The positive values of vector I and vector II for plant height, 50% flowering and non-reducing sugar indicated that these characters had the highest contribution towards the divergence among the pea genotypes. The genotypes of vegetable pea from cluster II and cluster IV maybe selected as parents in future hybridization program.DOI: http://dx.doi.org/10.3329/bjpbg.v26i1.19982

scholarly journals Genetic divergence in rapeseed-mustard (Brassica rapa L.)

2013 ◽  
Vol 38 (3) ◽  
pp. 417-423
Author(s):  
MH Khan ◽  
MM Ali ◽  
SR Vhuiyan ◽  
F Mahmud
Keyword(s):  
Principal Component Analysis ◽  
Genetic Variability ◽  
Analysis Of Variance ◽  
Brassica Rapa ◽  
Genetic Divergence ◽  
Principal Component ◽  
Component Analysis ◽  
Days To Maturity ◽  
Cluster Distance

An experiment was conducted at the experimental farm of Sher-e-Bangla Agricultural University, Dhaka, during November 2009 to February 2010 to study the genetic divergences of 32 genotypes of Brassica rapa L. through principal component analysis and Mohalanobis D2 analysis. Analysis of variance indicated that considerable genetic variability were existed among the 32 genotypes. On the basis of D2 analysis, the genotypes were grouped into 6 clusters. Cluster III had the maximum number of 11 genotypes, while the cluster IV and cluster V had only 2 genotypes each. The highest inter-cluster distance was observed between cluster I and V (21.871), while the lowest in the cluster II and III (4.237). The intra cluster distance was the maximum in cluster V (0.469) and minimum in cluster III (0.116). The characters yield per plant, number of siliquae per plant, and days to maturity were found prominent towards the genetic divergence. The genotypes G-15 and G-19 from cluster IV and G-1, G- 3, G-4, G-10, G-18, and G-24 from cluster I were suitable for creating more variability for higher yield per plant through hybridization DOI: http://dx.doi.org/10.3329/bjar.v38i3.16968 Bangladesh J. Agril. Res. 38(3): 417-423, September 2013

Genetic Diversity Assessment in Dolichos Bean (Lablab purpureus L.) Based on Principal Component Analysis and Single Linkage Cluster Analysis

2021 ◽  
Author(s):  
S.R. Singh ◽  
S. Rajan ◽  
Dinesh Kumar ◽  
V.K. Soni
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Single Linkage ◽  
Pod Yield ◽  
Diversity Assessment ◽  
Single Linkage Cluster ◽  
Linkage Cluster

Background: Dolichos bean occupies a unique position among the legume vegetables of Indian origin for its high nutritive value and wider climatic adaptability. Despite its wide genetic diversity, no much effort has been undertaken towards genetic improvement of this vegetable crop. Knowledge on genetic variability is an essential pre-requisite as hybrid between two diverse parental lines generates broad spectrum of variability in segregating population. The current study aims to assess the genetic diversity in dolichos genotypes to make an effective selection for yield improvement.Methods: Twenty genotypes collected from different regions were evaluated during year 2016-17 and 2017-18. Data on twelve quantitative traits was analysed using principal component analysis and single linkage cluster analysis for estimation of genetic diversity.Result: Principal component analysis revealed that first five principal components possessed Eigen value greater than 1, cumulatively contributed greater than 82.53% of total variability. The characters positively contributing towards PC-I to PC-V may be considered for dolichos improvement programme as they are major traits involved in genetic variation of pod yield. All genotypes were grouped into three clusters showing non parallelism between geographic and genetic diversity. Cluster-I was best for earliness and number of cluster/plant. Cluster-II for vine length, per cent fruit set, pod length, pod width, pod weight and number of seed /pod, cluster III for number of pods/cluster and pod yield /plant. Selection of parent genotypes from divergent cluster and component having more than one positive trait of interest for hybridization is likely to give better progenies for development of high yielding varieties in Dolichos bean.

↵Genetic Diversity and Principal Component Analysis in Mungbean [Vigna radiata (L.) Wilczek] under Rainfed Condition

2021 ◽  
Author(s):  
Deepak Gupta ◽  
Suresh Muralia ◽  
N.K. Gupta ◽  
Sunita Gupta ◽  
M.L. Jakhar ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Seed Yield ◽  
Agricultural Research ◽  
Principal Component ◽  
Component Analysis ◽  
Grain Legume ◽  
Research Station ◽  
Rainfed Condition

Background: Mungbean is a short duration grain legume widely grown in south and Southeast Asia. The extent of variability through Principal Component Analysis (PCA) and cluster analysis in promising mungbean genotypes should be known for possible yield improvement. A study was undertaken to work out the extent of variability among twenty four mungbean genotypes through cluster analysis and Principal Component Analysis (PCA). Methods: The experiment was laid out in a randomized block design with three replications during kharif 2018 and 2019 at the experimental field of Agricultural Research Station, Navgaon (Alwar) under rainfed condition. Result: Principal component analysis revealed that the first three main PCAs amounted 78.80% of the total variation among genotypes for different traits. Out of total principal components, PC1 accounts for maximum variability in the data with respect to succeeding components. Number of branches per plant (28.62%), number of clusters per plant (23.55%) and seed yield (15.58%) showed maximum per cent contribution towards total genetic divergence on pooled basis. Cluster analysis showed that genotypes fall into seven different clusters and their inter and intra cluster distance showed genetic diversity between different genotypes. The maximum number of genotypes i.e., 8 was found in cluster II followed by cluster III comprising of 6 genotypes. Genotypes RMG-1138 and IPM-02-03 representing the mono genotypic cluster signifies that it can be the most diverse variety and it would be the appropriate genotype for hybridization with ones present in other clusters to tailor the agriculturally important traits and ultimately to boost the seed yield in mungbean under rainfed conditions.

scholarly journals GENETIC DIVERGENCE ANALYSIS IN HRDC RICE (Oryza sativa L.) HYBRIDS IN BANGLADESH

2016 ◽  
Vol 27 (2) ◽  
pp. 25-32
Author(s):  
A. Ahmed ◽  
S. G. Shaon ◽  
M. S. Islam ◽  
P. S. Saha ◽  
M. M. Islam
Keyword(s):  
Genetic Divergence ◽  
Oryza Sativa L ◽  
Principal Component ◽  
Dry Season ◽  
Spikelet Fertility ◽  
Mean Values ◽  
Panicle Number ◽  
Cluster Distance ◽  
The Mean ◽  
Yield Maximization

Genetic divergence of 48 IRRI developed F1 rice hybrids were studied through Mahalanobis D2 and principal component analysis for ten characters in Gazipur and Pabna district during dry season 2012-13. Among 48 genotypes, cluster analysis resulted in five clusters following Ward’s method. During dry season for both regions, cluster I incorporated the highest number of genotypes. Significant differences among the genotypes but non-significant differences among replications were noticed for most of the parameters under study. The inter-cluster distance was larger than intra-cluster distance suggesting wider diversity among the genotypes. In Gazipur, the maximum inter-cluster D2 value was recorded between cluster III and V (6.69) and the minimum between cluster II and IV (0.69). The intra-cluster distance was maximum in cluster IV (3.60) and minimum in cluster I (0.33). In Pabna, maximum inter-cluster distance was exhibited between cluster IV and II (16.43) but minimum between cluster II and III (3.98). Maximum intra-cluster distance (4.40) was recorded in cluster IV whereas minimum in cluster I (0.83). Based on positive value of vector 1 and vector 2, panicle number m-2, spikelet fertility (%) and 1000-grain wt. (g) had maximum contribution towards genetic divergence among the characters studied. Cluster means indicated considerable differences in the mean values of different parameters. The highest cluster means for panicle weight (g), spikelet fertility (%), 1000 grain wt. (g) and grain yield (kg ha-1) were derived from cluster IV. Therefore, more prominence should be given to the lines under cluster IV that having genetic potentiality to contribute better for yield maximization of hybrid rice.

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