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.

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 Morphometrics of the tribe Merremieae Austin (Convolvulacae) from India

2014 ◽  
Vol 21 (2) ◽  
pp. 121-128
Author(s):  
S. A. Deshmukh ◽  
Vinod B. Shimpale
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Principal Component ◽  
Vital Role ◽  
Leaf Length ◽  
Petiole Length ◽  
Quantitative Characters ◽  
Plant Taxon ◽  
And Cluster Analysis ◽  
The Relationship

Sixteen species of the tribe Merremieae Austin (Convolvulaceae) from India were morphometrically analyzed with the help of Principal component analysis (PCA) and cluster analysis to explain the relationship between them. PCA showed that quantitative characters like corolla breadth, fruit breadth and length of paracot leaf play important role in bringing together all the species in the same tribe while the characters like leaf length, leaf breadth, petiole length, pedicel length, calyx length and calyx breadth play vital role in the delimitation of taxa within the tribe Merremieae. Cluster analysis and dendrogram revealed that, the genus Operculina S. Manso is segregated from Merremia Denns. ex Endlich.; genus Hewittia Wight. & Arn. is very close to Merremia, probably originated from M. aegyptia (L.) Urban and M. dissecta (Jacq.) Hall. f. cluster and genus Xenostegia Austin & Staples is isolated in the separate cluster.DOI: http://dx.doi.org/10.3329/bjpt.v21i2.21350Bangladesh J. Plant Taxon. 21(2): 121-128, 2014 (December)

scholarly journals Assessment of genetic variability for micronutrient content and agro-morphological traits in rice (Oryza sativa L.)

2020 ◽  
Vol 80 (02) ◽  
Author(s):  
P. Madhubabu ◽  
R. Surendra ◽  
K. Suman ◽  
M. Chiranjeevi ◽  
R. Abdul Fiyaz ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Oryza Sativa L ◽  
Development Program ◽  
Principal Component ◽  
Component Analysis ◽  
High Yield ◽  
Polished Rice ◽  
Iron And Zinc

Assessment of rice genetic diversity is critical step for trait specific varietal development program. In the present study, a collection of 281 Indian germplasm accessions were evaluated for genetic diversity study using 30 agro-morphological characters and grain iron and zinc contents in brown and polished rice. To identify the pattern of relatedness and associations, cluster analysis and principal component analysis coupled with correlation were used. Cluster analysis grouped 281 accessions into six main groups. Cluster 4 is the largest and had accessions with higher yield, zinc and iron content. Six components of principal component analysis indicated 76.4% of the total variation. The Principal Component (PC)1 showed 19.05%, while, PC2, PC3, PC4, PC5 and PC6 exhibited 14.23%, 13.61%, 11.58%, 7.59%, and 6.71% variability, respectively. Among the germplasm, three accessions IC145407, IC145357 and IC248034 have shown significant iron and zinc content in polished rice along with desirable grain yield. The information presented here will be useful in the development of rice varieties with high yield and micronutrient content.

scholarly journals GENETIC DIVERSITY AND PARENTS SELECTION FROM EXOTIC RICE (Oryza sativa L.) GERMPLASM

2012 ◽  
Vol 25 (1) ◽  
pp. 11-16
Author(s):  
A. A. Mamun ◽  
N. A. Ivy ◽  
M. G. Rasul ◽  
M. M. Hossain
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Oryza Sativa ◽  
Oryza Sativa L ◽  
Principal Component ◽  
Component Analysis ◽  
Rice Genotypes ◽  
Total Divergence ◽  
Five Axes

Genetic divergence among fifty exotic rice genotypes along with two check varieties were estimated using D2 and principal component analysis. The study was undertaken to select suitable donor parents for use in improved breeding program of Bangabandhu Sheikh Mujibur Rahman Agricultural University in 2009. Principal component analysis (PCA) revealed that the first five axes accounted for 58.10% of the total variation. As per cluster analysis, the genotypes were grouped into seven clusters consisting 11, 16, 7, 11, 1, 2 and 4 genotypes which revealed that there exist considerable diversity among the genotypes. Considering the magnitude of genetic distance, contribution of different characters towards the total divergence and magnitude of cluster means for different characters, the genotypes RG-BU-08-057, 61, 65, 67, 69, 71, 85, 86, 88, 94, 96, 98 and 99 might be selected as a suitable parent for future hybridization program.DOI: http://dx.doi.org/10.3329/bjpbg.v25i1.17007

scholarly journals Multivariate Analysis in Lentil (Lens culinaris L.)

1970 ◽  
Vol 23 (1) ◽  
pp. 9-12 ◽  
Author(s):  
AA Jewel ◽  
AK Chowdhury ◽  
AKMM Alam ◽  
MA Latif ◽  
MM Hassan
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Seed Weight ◽  
Lens Culinaris ◽  
Principal Component ◽  
Plot Yield ◽  
Days To Maturity ◽  
Cluster Distance ◽  
100 Seed Weight

Genetic divergence among 22 genotypes of lentil was estimated using D2 and principal component analysis. The genotypes under study fell into four clusters. The intra-cluster value was the maximum in cluster I and the minimum in cluster II. The inter-cluster distance was larger than the intra-cluster distance in all the cases suggesting the wider genetic diversity among the genotypes of different groups. The inter-cluster value indicated maximum distance between cluster I and II than cluster III and IV. Thus the genetically diverged genotypes of the clusters could be used as parent in hybridization program to get desirable genotypes. Cluster I had the highest mean for days to maturity, plant height, pods/plant and per plot yield while cluster II and III had the highest days to first flowering and 100 seed weight, respectively. Genotypes with these characters in respective groups would, therefore, offer a good scope of improvement of lentil through selection.   Key words: Lentil; cluster analysis; divergence; hybridization DOI: http://dx.doi.org/10.3329/bjpbg.v23i1.9312 BJPBG 2010; 23(1): 9-12

Phytolith analysis of Cyperaceae from the Pampean region, Argentina

2009 ◽  
Vol 57 (6) ◽  
pp. 512 ◽  
Author(s):  
Mariana Fernández Honaine ◽  
Alejandro F. Zucol ◽  
Margarita L. Osterrieth
Keyword(s):  
Principal Component Analysis ◽  
Comparative Analysis ◽  
Principal Component ◽  
Robust Pca ◽  
Xylem Parenchyma ◽  
Qualitative And Quantitative ◽  
Pampean Region ◽  
Quantitative Characters ◽  
Qualitative Characters ◽  
First Time

Cyperaceae, along with Poaceae, is the main silica accumulator. Although the anatomical-taxonomic and palaeobotanical relevance of phytoliths has been well established, there are no studies that deal with the qualitative and quantitative aspects of the phytolith production or differentiate phytoliths from the different organs in Cyperaceae. Toward the construction of a detailed database of phytolith production, we describe in the present paper the phytoliths of leaves, culms and fruits of Cyperaceae from Pampean region (Argentina). Phytoliths were extracted by a calcination technique. Qualitative and quantitative characters and percentages of phytolith morphotypes were subject to principal component analysis to analyse their taxonomic relevance. For some sedges, values of phytolith content and a comparative analysis of leaves, culms and fruit phytoliths are presented here for the first time. Diverse tissues such as epidermis, xylem, parenchyma and sclerenchyma produced phytoliths. The most abundant morphotypes were conical phytoliths, which showed differences in the base shape and in their size between organs. Leaf/culm cones have a rounded, rectangular or square base; typical fruit cones have a polygonal base and they are bigger and more robust. PCA showed that quantitative and qualitative characters of cones, along with the percentages of morphotypes, allowed group distinction.

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