Multivariate Analysis of Quantitative Traits in Field Pea (Pisum sativum var. arvense)

2021 ◽  
Author(s):  
Vijay Pratap ◽  
Vijay Sharma ◽  
Hitesh Kumar ◽  
Kamaluddin . ◽  
Gaurav Shukla ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Principal Component ◽  
Component Analysis ◽  
Background Field ◽  
Field Pea ◽  
Grain Legume ◽  
High Genetic Diversity ◽  
Eigen Value ◽  
Cluster Distance ◽  
Hybridization Programme

Background: Field pea is one of the important cool season grain legume crops cultivated in India. In this investigation, experimental material i.e. eighty germplasm lines of field pea with four checks (IPF 4-9, Adarsh, Ambika and IPFD 10-12) were evaluated to determine the estimates of genetic diversity in the test genotypes.Methods: The data were recorded on thirteen quantitative characters for the study of genetic diversity. The mean data of each characters were subjected to cluster analysis by using D2 Mahalanobis clustering method. The principle component analysis (PCA) for measuring genetic divergence was done by XLSTAT and R 4.0 statistical package. Result: Eighty-four germplasms including checks were categorized into five distinct clusters, indicates the occurrence of high genetic diversity in the evaluated set of germplasm. Between cluster III and IV highest inter-cluster distance was observed, indicates the maximum diversity among genotypes of these clusters. Considerable differences were observed for cluster mean among different distinct clusters for all the thirteen characters. The hybridization programme involving genotypes from cluster III and cluster IV may be used to isolate suitable segregants. Principal component analysis grouped different traits under study into thirteen principal components (PCs) in which only five PCs with eigen value greater than 1 accounted 70.97% of total variation present in genotypes. The traits falling to these five PCs may be given due importance in field pea improvement programmes.

↵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 Multivariate analysis of genetic diversity in Phytophthora pod rot resistant exotic cocoa germplasm

2020 ◽  
pp. 202-212
Author(s):  
S.A. Veeresh ◽  
J.S. Minimol ◽  
B. Suma ◽  
P.S. Panchami ◽  
K.S. Shilpa
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Research Work ◽  
Principal Component ◽  
High Variability ◽  
Qualitative And Quantitative ◽  
Quantitative Characters ◽  
Eigen Value ◽  
Hybridization Programme

The current research work was carried out to evaluate the genetic diversity associated with thirty cocoa accessions resistant to Phytophthora. The cluster analysis and principal component analysis evaluated the genetic variability among the different genotypes. The highest number of genotypes were observed in cluster III (8) when qualitative traits were considered. In quantitative cluster analysis, most of the genotypes were placed in separate clusters due to high variability in the germplasm. Principal component (PC) analysis showed that the first three PCs with more than one Eigen-value contributed to 79.9 per cent of variability for different traits. When qualitative and quantitative characters were considered along with resistant reaction, clusters with genotypes highly resistant to Phytophthora pod rot were observed. Hybridization programme involving these resistant hybrids belonging to diverse clusters will result in high yielding hybrids with ample resistance.

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 Assessment of Genetic Diversity in Nigella (Nigella sativa L.) Collections Using Principle Component Analysis

2019 ◽  
pp. 1-11
Author(s):  
S. P. Singh ◽  
Avinash Kumar ◽  
Banshidhar . ◽  
Sandeep Kumar Suman ◽  
Ashutosh Kumar ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Principle Component Analysis ◽  
Nigella Sativa ◽  
Block Design ◽  
Component Analysis ◽  
Rapid Improvement ◽  
Principle Component ◽  
Randomized Block Design ◽  
Eigen Value ◽  
Cluster Distance

Seventeen land races of Nigella along with one released variety (Rajendra Shyama) as a check; collected at farmer’s field from different parts of Bihar were evaluated in Randomized Block Design with three replications at Seed production Farm, TCA, Dholi, Bihar during Rabi 2015-16 to identify  diverse Nigella genotypes. Principle component analysis (PCA) showed that first three PCs had >1.00 Eigen value and accounted to 84.71% of total variation. Rotated component matrix for various traits revealed that PC1 was strongly associated with secondary branches/plant followed by yield/plant, length of fruit, fruit per plant, primary branches/plant, height of the plant, days to 50% flowering and grains/plant. The traits that mostly contributed to PC2 were grains/plant followed by height of the plant and width of fruit whereas, days to maturity followed by width of fruit, height of the plant, days to 50% flowering and length of fruit contributed mostly to the PC3.  The characters that contributed most to the PC4 were height of the plant, fruit/plant and length of fruit. Therefore, intensive selection procedures can be adopted to bring about rapid improvement of above mentioned traits. The k-mean of different clusters indicated that genotype falling in cluster III possess high values for all the traits under study indicating their potentiality as a parent in hybridization programmes for further improvement of Nigella. Highest inter-cluster distance was noted between cluster III and V indicating the genetic diversity among genotypes of these two clusters. Therefore, genotypes from these two clusters are recommended to use in hybridization programmes for further improvement.

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.

scholarly journals Genetic diversity analysis of parental lines for hybrid development in rice (Oryza sativa L.)

2013 ◽  
Vol 37 (4) ◽  
pp. 617-624 ◽  
Author(s):  
MJ Hasan ◽  
Umma Kulsum ◽  
MMH Rahman ◽  
MMH Chowdhury ◽  
AZMKA Chowdhury
Keyword(s):  
Genetic Diversity ◽  
Oryza Sativa L ◽  
Principal Component ◽  
Mean Value ◽  
Cluster Distance ◽  
Parental Lines ◽  
Almost All ◽  
Yield Maximization ◽  
Hybrid Development ◽  
Panicle Weight

Genetic divergence of 40 parental lines comprising 30 restorer and 10 maintainer lines were studied through Mohalanobis's D2 and principal component analysis for eleven characters. Genotypes were grouped into five different clusters. Cluster V comprised maximum number of genotypes (thirteen) followed by cluster I and II. The inter-cluster distance was maximum between clusters I and V (13.495) indicating wide genetic diversity between these two clusters followed by the distance between cluster I and 11 (9.489), cluster IV, and cluster V (8.969) and cluster I and cluster III (8.039). The minimum inter-cluster distance was observed between cluster II and cluster III (3.034) followed by cluster 111 and cluster IV (3.834) and cluster II and cluster V (4.945) indicating that the genotypes of these clusters were genetically close. The intra cluster distance in the entire five clusters was more or less low which indicated that the genotypes within the same cluster were closely related. Among the characters panicle weight contributed most for divergence in the studied parental lines. Difference in cluster means existed for almost all the characters studied. Highest mean value for number of effective tillers (7.8), days to 50% flowering (95.5), panicles/m2 (192.6), panicle weight (2.9), spikelet fertility (84.8), number of grains/panicle (177.8), days to maturity (123.6), and grain yield/plot (1065.5) were observed in cluster I indicated the parental lines fallen in this cluster having the genetic potentiality to contribute better for yield maximization of hybrid rice. DOI: http://dx.doi.org/10.3329/bjar.v37i4.14386 Bangladesh J. Agril. Res. 37(4): 617-624, December 2012

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  

Genetic diversity based on cluster and principal component analysis in wheat and triticale genotypes

2015 ◽  
Vol 16 (4) ◽  
pp. 712
Author(s):  
Bhanu Priya ◽  
Sunil Diyali ◽  
Subhra Mukherjee ◽  
M. Srinivasarao
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis

scholarly journals Estimation of Genetic Diversity among Genotypes of Fodder Oat based on Principal Component Analysis

2017 ◽  
Vol 8 (6) ◽  
pp. 807-810
Author(s):  
Monica Jyoti Kujur ◽  
◽  
A. K. Mehta ◽  
S. K. Bilaiya ◽  
Prakarti Patil ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis
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