Multivariate Analysis, Genetic Diversity and Phenotypic Correlation of Nineteen Exotic Groundnut Accessions

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
YPJ AMARASINGHE ◽  
G . WIJESINGHE ◽  
R W PUSHPAKUMARA
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Growth Parameters ◽  
Principal Component ◽  
Phenotypic Correlation ◽  
Clustering Method ◽  
Yield Parameters ◽  
Arachis Hypogaea L ◽  
Semi Arid ◽  
Number Of Branches

19 Groundnut ( Arachis hypogaea L. ) genotypes receiv ed from International Crops Research Institute for Semi Arid T ropics (ICRISA T) India w ere ev aluated in a non replicated trial and the characters w ere subjected to multiv ariate analysis to study the v ariability within the genotypes. The first 5 axes of the principal component analysis captured 78% of the total v ariability and identified yield parameters such as number of pods per plant, pod w eight per plant and growth parameters such as number of branches per plant, plant spread, and pod characteristics as the characters contributing most to total v ariation. Phenotypic correlation analysis rev ealed that the yield has positiv e correlation with the characters such as number of pods per plant and number of branches per plant. W ards clustering method has grouped the genotypes into 3 distinct clusters. The results can be applied in order to strengthen the breeding program

Genetic Analysis of Chinese Cucumber Collections in the U.S. National Germplasm Collection

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 534e-534 ◽  
Author(s):  
J. Staub ◽  
Felix Sequen ◽  
Tom Horejsi ◽  
Jin Feng Chen
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Genetic Variation ◽  
Genetic Analysis ◽  
Allelic Variation ◽  
Germplasm Collection ◽  
Principal Component ◽  
Isozyme Loci ◽  
National Plant Germplasm System ◽  
The U.S

Genetic variation in cucumber accessions from China was assessed by examining variation at 21 polymorphic isozyme loci. Principal component analysis of allelic variation allowed for the depiction of two distinct groupings of Chinese accessions collected in 1994 and 1996 (67 accessions). Six isozyme loci (Gpi, Gr, Mdh-2, Mpi-2, Pep-gl, and Pep-la) were important in elucidating these major groups. These groupings were different from a single grouping of Chinese 146 accessions acquired before 1994. Allelic variation in Chinese accessions allowed for comparisons with other accessions in the U.S. National Plant Germplasm System (U.S. NPGS) collection grouped by continent and sub-continent. When Chinese accessions taken collectively were compared with an array of 853 C. sativus U.S. NPGS accessions examined previously, relationships differed between accessions grouped by country or subcontinent. Data indicate that acquisition of additional Chinese and Indian cucumber accessions would be strategically important for increasing genetic diversity in the U.S. NPGS cucumber collection.

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.

Study on the Ports Cluster in Region Ports Group

2014 ◽  
Vol 536-537 ◽  
pp. 1684-1687
Author(s):  
Quan Shan Xiao ◽  
Li Li Qu ◽  
Feng Rong Zhang ◽  
Xin Xu ◽  
Guo Cheng Zhao
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Clustering Method

In order to analyze and cluster the scale and categories among the Bohai ports group accurately and objectively, ports are expected to be divided among categories of regional port cluster. Considering ports scale can be affected by many different factors, and those factors have different organizations and units, so principal component analysis(PCA) was used to standardize those factors’ data and then calculated the standardize matrix. Afterwards, k-means clustering method was used to analyze the standardize matrix, achieving the goal of clustering ports and planing hierarchical ports layout.Finally,the cluster results can make significant guidance for the development of inter-port cooperation.

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

Genetic diversity in four cabbage populations based on UPOV and IPGRI description forms and allozyme variation

2001 ◽  
Vol 136 (3) ◽  
pp. 309-318 ◽  
Author(s):  
T. V. KOUTSOS ◽  
M. KOUTSIKA-SOTIRIOU
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Plant Genetic Resources ◽  
Principal Component ◽  
Allozyme Variation ◽  
Gene Frequencies ◽  
International Union ◽  
New Varieties ◽  
International Plant ◽  
Physiological Characters

Morphophysiological characters, designated as descriptors by the International Union for the Protection of New Varieties of Plants (UPOV) and the International Plant Genetic Resources Institute (IPGRI), and allozyme variation were used to study genetic diversity among four cabbage (Brassica oleracea L. var. capitata L.) open pollinated (OP) populations. The morphological and physiological characters, and gene frequencies among OP populations were analysed by using cluster (CA) and principal component analysis (PCA). Both methods gave the same clustering of OP populations. The relationships found among OP populations by analysing UPOV descriptors (30 characters) and IPGRI descriptors (30+14 characters) were similar. The relationships among OP populations obtained from gene frequencies were not similar to those obtained from morphophysiological characters, but two of the four OP populations were clustered together by both categories of data. The biggest correlation between the relationships among OP populations obtained from morphophysiological characters and those obtained from gene frequencies was r = −0·44 and r =−0·38 given by PCA and CA respectively. The importance of each character or allele with respect to the relationships among OP populations were also detected by PCA.

Sign in / Sign up

Export Citation Format

Share Document