Assessment of genetic divergence using Mahalanobis D2and principal component analysis of qualitative and quantitative characters in pomegranate genotypes under sub-tropics

2015 ◽  
Vol 72 (4) ◽  
pp. 451
Author(s):  
Dimpy Raina ◽  
W.S. Dhillon ◽  
P.P.S. Gill ◽  
N.P. Singh
Keyword(s):  
Principal Component Analysis ◽  
Genetic Divergence ◽  
Principal Component ◽  
Component Analysis ◽  
Qualitative And Quantitative ◽  
Quantitative Characters

Taxonomic revision of the Colombian Tityus (Archaeotityus) (Scorpiones, Buthidae) species: a morphological and morphometric approach, with a description of a new species

Zootaxa ◽  
2019 ◽  
Vol 4660 (1) ◽  
pp. 1-94
Author(s):  
JAIRO A. MORENO-GONZÁLEZ ◽  
RANULFO GONZÁLEZ O. ◽  
EDUARDO FLÓREZ D.
Keyword(s):  
Principal Component Analysis ◽  
New Species ◽  
New Records ◽  
Principal Component ◽  
Taxonomic Revision ◽  
Component Analysis ◽  
Morphological Characters ◽  
Species Level ◽  
Qualitative And Quantitative ◽  
A New Species

We present a taxonomic revision of the Colombian Tityus (Archaeotityus) species based on morphological and morphometric evidence. We examined more than 385 specimens and evaluated new and previously used qualitative and quantitative morphological characters. We redescribe the Colombian species and present morphological characters for both sexes and an emended diagnosis for the subgenus Tityus (Archaeotityus). We describe a new species Tityus guane sp. nov. from Santander department, Colombia, Tityus betschi Lourenço 1992 is synonymized with Tityus parvulus Kraepelin, 1914, and Tityus wayuu Rojas-Runjaic & Armas, 2007 is synonymized with Tityus tayrona Lourenço, 1991. We measured 186 specimens and performed a multivariate principal component analysis (PCA) for 34 selected morphometric ratios for each sex. We found that a few morphological ratios support species level distinctions within the Colombian species. We provide updated distributional maps with new records and an identification key for both sexes. Furthermore, we provide an updated checklist for the subgenus and a discussion about the character systems used within Tityus (Archaeotityus). The new morphological characters proposed and the traditional morphometry examined with a PCA are useful for studying Tityus (Archaeotityus) taxonomy.

scholarly journals Investigation of Cotton Germplasm for Genetic Divergence Regarding Yield Related Trait Using Principal Component Analysis

2020 ◽  
Author(s):  
Qudrat Ullah ◽  
Muhammad Zulfiqar Ahmad ◽  
Kalim Ullah ◽  
Obaidullah Sayal ◽  
Arshad Jamil ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Genetic Divergence ◽  
Principal Component ◽  
Component Analysis ◽  
Main Cluster ◽  
Total Variability ◽  
Yield Related Trait ◽  
And Cluster Analysis ◽  
Related Trait

Abstract Background: Cotton is a vital fiber and cash crop in Pakistan. Genetic diversity of a germplasm play an important role for cotton breeding. One hundred and two germplasm of upland cotton were investigated for genetic divergence regarding yield related attributes using principal component analysis. The research was carried out in RCB design with 2 replications. Experiment data was recorded on various qualitative and quantitative parameters and were subjected to principal components analysis (PCA) and cluster analysis.Results: PCA result showed that only four components were considered on account of their eigenvalue greater than 1 which contributed 65% to the total variability. Score plot showed that the suncrop-6, tipu-9, TJ-max, Deebal, CRIS-543, TH-20, Tahafuz-7, Eagle, BS-80, IUB-69, BH-221, NIAB-1048, and NIAB BT-2 showed the vertex of polygon and resulted as most divergent germplasm. Similarly cluster analysis also categorized the yield related traits into 5 main cluster. Cluster-1 contain 20 germplasm, cluster-II contain 16, and cluster-III, cluster-IV, and cluster-V comprise 13, 16, and 37 germplasm, respectively.Conclusion: Based on results, it was recommended that these genetically diverse germplasm might be used as parents that could be utilized in upcoming breeding programs.

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.

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.

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

Principal Component Analysis for Yield and its Attributing Traits in Aromatic Landraces of Rice (Oryza sativa L.)

2021 ◽  
Vol 12 (5) ◽  
pp. 303-308
Author(s):  
Maumita Burman ◽  
◽  
Sunil Kumar Nair ◽  
Arvind Kumar Sarawgi ◽  
◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Grain Yield ◽  
Principal Components ◽  
Principal Component ◽  
Component Analysis ◽  
Spikelet Fertility ◽  
Quantitative Characters ◽  
Eigen Value ◽  
1000 Grain Weight ◽  
Panicle Weight

The present investigation was carried out in Kharif 2019 (July to November) to estimate the relative contribution of various traits for total genetic variability present in aromatic landraces by Principal Component Analysis. Here 90 aromatic rice landraces along with six check varieties were evaluated for 13 quantitative characters by Principal Component Analysis. Principal Component Analysis showed that, out of 13 quantitative characters studied, only five principal components (PCs) exhibited more than 1.00 eigen value and showed about 81.62% cumulative variability among the traits studied. Out of the five principal components exhibiting more than 1.00 eigen value PC1 had the highest variability (25.12%) followed by PC2 (21.8%). The first principal component PC1 was positively contributed mainly by two characters viz., Grain Length and 1000 grain weight. The second principal component PC2 was contributed mostly by three characters like grain yield plant-1, panicle weight and spikelet fertility percentage. The third principal component PC3 is positively associated with panicle weight, grain yield plant-1 and spikelet fertility percentage. The fourth principal component PC4 is positively associated with spikelet fertility percentage, Grain Length/ Breadth ratio and fertile grains panicle-1. The fifth principal component PC5 is positively associated with total grains per panicle-1, grain width and 1000 grain weight. All the principal components were showing positive contribution for yield and its attributing traits. These variations can be exploited in crop improvement programme for developing high yielding varieties.

scholarly journals CLASSIFICATION OF LIDAR DATA OVER BUILDING ROOFS USING K-MEANS AND PRINCIPAL COMPONENT ANALYSIS

2018 ◽  
Vol 24 (1) ◽  
pp. 69-84
Author(s):  
Renato César dos Santos ◽  
Mauricio Galo ◽  
Vilma Mayumi Tachibana
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Real Data ◽  
Component Analysis ◽  
Lidar Data ◽  
Qualitative And Quantitative ◽  
Quantitative Analyses ◽  
Geometric Primitives ◽  
Different Levels

Abstract: The classification is an important step in the extraction of geometric primitives from LiDAR data. Normally, it is applied for the identification of points sampled on geometric primitives of interest. In the literature there are several studies that have explored the use of eigenvalues to classify LiDAR points into different classes or structures, such as corner, edge, and plane. However, in some works the classes are defined considering an ideal geometry, which can be affected by the inadequate sampling and/or by the presence of noise when using real data. To overcome this limitation, in this paper is proposed the use of metrics based on eigenvalues and the k-means method to carry out the classification. So, the concept of principal component analysis is used to obtain the eigenvalues and the derived metrics, while the k-means is applied to cluster the roof points in two classes: edge and non-edge. To evaluate the proposed method four test areas with different levels of complexity were selected. From the qualitative and quantitative analyses, it could be concluded that the proposed classification procedure gave satisfactory results, resulting in completeness and correctness above 92% for the non-edge class, and between 61% to 98% for the edge class.

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