scholarly journals Morphologic and Agronomic Diversity of Brassica napus Crops

2008 ◽  
Vol 133 (1) ◽  
pp. 48-54 ◽  
Author(s):  
Pilar Soengas ◽  
Maria Elena Cartea ◽  
Pablo Velasco ◽  
Guillermo Padilla ◽  
Amando Ordás
Keyword(s):  
Cluster Analysis ◽  
Brassica Napus ◽  
Agronomic Traits ◽  
Genetic Relationships ◽  
Winter Season ◽  
Principal Component ◽  
Group Method ◽  
Pair Group ◽  
Total Variability ◽  
And Cluster Analysis

A Brassica napus L. crop called nabicol traditionally has been grown by farmers in northwestern Spain for many years and is an important horticultural product during the winter season. The relationship of nabicol to other B. napus crops has been studied based on simple sequence repeat (SSR) data. However, molecular and morphologic classifications often disagree. The objectives of this research were to study the morphologic and agronomic relationships of nabicol landraces to other B. napus crops and to compare those relationships with the ones already known, based on SSR data. Thirty-five B. napus populations from different geographic origins and uses were evaluated. Data were recorded on 17 morphologic and agronomic traits. Principal component analysis and cluster analysis were performed to classify the populations. Eight principal components (94% of the total variability) were standardized to produce the Mahalanobis' generalized distances, and a cluster analysis was conducted using the unweighted pair group method with arithmetic averages. There are no major differences between B. napus var. pabularia (DC.) Rchb. (nabicol, couve-nabiça, forage rape) and B. napus var. oleifera DC. (oilseed rape), and they probably share a common origin. Rape kale (B. napus var. pabularia) and rutabaga [B. napus var. napobrassica (L.) Rchb.] cultivars are separated from the rest and probably they have an independent origin or domestication. Molecular and morphologic classifications are complementary, and both are necessary to classify germplasm correctly and to clarify genetic relationships among B. napus crops.

scholarly journals Assessment of Physicochemical Properties of Tequila Brands: Authentication and Quality

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Alejandra Carreon-Alvarez ◽  
Amaury Suárez-Gómez ◽  
Florentina Zurita ◽  
Sergio Gómez-Salazar ◽  
J. Felix Armando Soltero ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Refractive Index ◽  
Physicochemical Properties ◽  
Analysis Of Variance ◽  
Principal Component ◽  
Component Analysis ◽  
Total Variability ◽  
And Cluster Analysis ◽  
Physicochemical Data

Several physicochemical properties were measured in commercial tequila brands: conductivity, density, pH, sound velocity, viscosity, and refractive index. Physicochemical data were analyzed by Principal Component Analysis (PCA), cluster analysis, and the one-way analysis of variance to identify the quality and authenticity of tequila brands. According to the Principal Component Analysis, the existence of 3 main components was identified, explaining the 87.76% of the total variability of physicochemical measurements. In general, all tequila brands appeared together in the plane of the first two principal components. In the cluster analysis, four groups showing similar characteristics were identified. In particular, one of the clusters contains some tequila brands that are not identified by the Regulatory Council of Tequila and do not meet the quality requirements established in the Mexican Official Standard 006. These tequila brands are characterized by having higher conductivity and density and lower viscosity and refractive index, determined by one-way analysis of variance. Therefore, these economical measurements, PCA, and cluster analysis can be used to determinate the authenticity of a tequila brand.

Morphometric analysis in different geographical populations of Varroa destructor (Acari: Varroidae) associated with Apis mellifera colonies in Iran

2018 ◽  
Vol 23 (10) ◽  
pp. 1915
Author(s):  
Mahsa Farjamfar ◽  
Alireza Saboori ◽  
Jamasb Nozari ◽  
Vahid Hosseininaveh
Keyword(s):  
Apis Mellifera ◽  
Morphometric Analysis ◽  
Varroa Destructor ◽  
Principal Component ◽  
Group Method ◽  
Dorsal Shield ◽  
Pair Group ◽  
Geographical Regions ◽  
Geographical Populations ◽  
And Cluster Analysis

Varroa destructor is a major ectoparasitic mite which feeds on the western honey bee, Apis mellifera hemolymph. Morphometric analysis of V. destructor in Iran was performed in order to detect differences within some populations of the species. Totally, 145 female mites were collected from A. mellifera colonies in different geographical regions in Iran and Europe (Spain and France). Eight morphological variables were measured: 1) length of dorsal shield (LDS), 2) width of dorsal shield (WDS), 3) length of genital shield (LGS), 4) width of genital shield (WGS), 5) length of metapodal shield (LMS), 6) width of metapodal shield (WMS), 7) length of anal shield (LAS) and 8) width of the anal shield (WAS). The ratios of LDS/WDS, WDS/LDS, LGS/WGS and LAS/WAS were also calculated. Multivariate analyses demonstrated significant differences in means of body length (LDS) and body width (WDS) between populations. Using principal component analysis (PCA) and cluster analysis with pair group method, five morphological groups were established. PCA analyses were also shown one morphotype, A3, between samples. Collectively, our findings suggest a wide phenotypic plasticity within the populations of Varroa mite in Iran.

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 Genetic Variability of 21 Tea Genotypes [Camellia sinensis (L.) O. Kuntze] Based on RAPD Markers

2018 ◽  
Vol 5 (2) ◽  
pp. 77
Author(s):  
Budi Martono ◽  
Syafaruddin Syafaruddin
Keyword(s):  
Genetic Diversity ◽  
Cluster Analysis ◽  
Genetic Similarity ◽  
Binary Data ◽  
Rapd Markers ◽  
Group Method ◽  
Breeding Programs ◽  
Pair Group ◽  
Monomorphic Band ◽  
And Cluster Analysis

<em>Knowing the genetic diversity in the tea germplasms collection is one of important conditions for assembling new superior varieties. Information of genetic diversity can be obtained through analysis using RAPD molecular markers. The study aimed to determine the genetic diversity of 21 tea genotypes based on RAPD markers. The research was conducted in Integrated Laboratory, Seameo Biotrop, Bogor, from July to September 2013. Genomic DNA was isolated from 21 tea genotypes leaf samples, then amplified with primer OPA 03, OPA 05, OPB 04, OPB 06, OPC 06, and OPD 08. Electrophoresis result was converted into binary data. The genetic similarity and cluster analysis calculation was done using NTSYS-pc version 2.10. In this research, 50 polymorphic bands (94,34%) and 3 monomorphic band (5,66%) were obtained. Cluster analysis based on Nei's genetic distance using the unweighted pair-group method with arithmatic (UPGMA) divided 21 tea genotypes into two groups at a genetic similarity value of 0,48. Group 1 consisted of 20 tea genotypes, while the second group comprised only a one genotype (Sin 27). The range of genetic similarity matrix was between 28%–92%, the lowest genetic similarity (28%) was found between GMB 4 and Sin 27 genotypes, while the highest (92%) was found between AS 2 and AS 1 genotypes. The information obtained can be utilized in breeding programs with the support of agronomic characters as well as in the conservation of tea germplasm.</em>

scholarly journals Selection of the Most Discriminating Morphological Qualitative Variables for Characterization of Fig Germplasm

2010 ◽  
Vol 135 (3) ◽  
pp. 240-249 ◽  
Author(s):  
Esther Giraldo ◽  
Margarita López-Corrales ◽  
José Ignacio Hormaza
Keyword(s):  
Principal Components ◽  
Principal Component ◽  
Group Method ◽  
Germplasm Collections ◽  
Pair Group ◽  
Morphological Studies ◽  
Production Type ◽  
Qualitative Variables ◽  
Total Variability

Most descriptor lists for the characterization of genetic resources in plants include a large number of traits whose evaluation is a lengthy and expensive process making the characterization of large germplasm collections difficult. Consequently, to facilitate the study and the conservation of germplasm, it is important to select carefully the most informative variables for each species. In this work, we applied sequential statistical procedures to select the most discriminant variables in fig (Ficus carica L.) from the initial 134 qualitative variables studied. A total of 34 variables was finally selected and broken down in 97 characters that were grouped by principal component analysis in 11 principal components that explain 93.34% of the total variability. The unweighted pair group method with arithmetic mean dendrogram derived from a similarity matrix generated using the Pearson's correlation coefficient among the 11 principal components selected classifies the cultivars in four main groups mainly based in the production type. These results show that redundant information can be obtained in morphological studies with a large number of variables resulting from correlation between variables. Consequently, a carefully selected and reduced number of highly discriminating variables can allow efficient fig germplasm characterization and discrimination resulting in significant savings of time and resources.

Palynological observations on the genus Gundelia L. (Asteraceae) growing in Turkey

Phytotaxa ◽  
2021 ◽  
Vol 502 (1) ◽  
pp. 51-66
Author(s):  
MEHMET FIRAT ◽  
SELAMI SELVİ
Keyword(s):  
Pollen Morphology ◽  
Pollen Grains ◽  
Principal Component ◽  
Polar Axis ◽  
Morphological Characters ◽  
Group Method ◽  
Pair Group ◽  
Equatorial Diameter ◽  
Polar Diameter ◽  
And Cluster Analysis

The pollen morphology of 17 taxa of Gundelia, of which 13 taxa are endemic to Turkey, was investigated by light microscopy (LM) and scanning electron microscopy (SEM). In this study, the pollen morphology of 16 taxa except G. tournefortii was investigated for the first time. The quantitative data were analyzed by descriptive statistics and multivariate statistics. The pollen grains are oblate spheroidal and prolate spheroidal in shape with the polar diameter of 37.01–61.2 μm and the equatorial diameter of 31.2–63.4 μm. The smallest pollen grains were observed in G. anatolica, G. rosea and G. tournefortii, while the largest pollen grains were observed in G. vitekii, G. komagenensis and G. colemerikensis. Pollen ornamentation is echinate in LM and echinate-microperforate in SEM. Statistically, the relationships between pollen characters of the examined taxa were identified using Principal Component Analysis (PCA) and Clustering Analyzis. In addition, a dendrogram was constructed by applying UPGMA based on the determined 15 pollen morphological characters, and the degree of their relationship was discussed. Polar axis, equatorial diameter and colpus length were the major explanations of the pollen morphological characters’ total variation in PCA. Pair group method was used to divide the main pollen taxa into three groups based on the pollen morphology by using arithmetic averages analysis (PCA scatterplot and cluster analysis). As a result, the pollen shape, polar axis, equatorial diameter and spine length were important characters distingushing the taxa from each other. We found some matches and mismatches between pollen and morphological characters, whose significance requires further study.

Genetic diversity among varieties of the native forage grass Trichloris crinita based on AFLP markers, morphological characters, and quantitative agronomic traits

Genome ◽  
2006 ◽  
Vol 49 (8) ◽  
pp. 906-918 ◽  
Author(s):  
Pablo F Cavagnaro ◽  
Juan B Cavagnaro ◽  
José L Lemes ◽  
Ricardo W Masuelli ◽  
Carlos B Passera
Keyword(s):  
Genetic Diversity ◽  
Cluster Analysis ◽  
Biomass Production ◽  
Agronomic Traits ◽  
Morphological Characters ◽  
Group Method ◽  
Aflp Data ◽  
Basal Diameter ◽  
Pair Group ◽  
Upgma Cluster Analysis

We assessed the genetic diversity in Trichloris crinita (Poaceae) varieties from South America, using AFLPs, morphological characters, and quantitative agronomic traits. Owing to the importance of this species for range grazing, we first characterized the varieties based on forage productivity. Biomass production varied 9 fold among the materials evaluated. Analysis of AFLP fingerprints allowed the discrimination of all varieties with a few selected primer combinations. Pair-wise genetic similarities, using marker data, ranged from 0.31 to 0.92 (Jaccard coefficients). Marker-based unweighted pair group method with arithmetic averaging (UPGMA) cluster analysis did not show geographical clustering, but rather grouped the varieties according to their biomass production. We identified 18 markers associated with biomass production, of which 8 showed complete correlation (r = 1.00) with this trait. These DNA markers can be used to assist selection for high forage productivity in T. crinita. Cluster analysis using morphological and quantitative characters revealed 4 distinct groups of varieties, clearly separated according to their biomass yield. The variables foliage height and basal diameter were strongly correlated with biomass production and these phenotypic markers can be used to select productive plants. The relations among the varieties based on AFLP data were significantly correlated with those based on agronomic and morphological characters, suggesting that the 2 systems give similar estimates of genetic relations among the varieties.Key words: AFLP fingerprinting, genetic diversity, Trichloris crinita, morphology, biomass production.

scholarly journals Genetic diversity in table grapes based on RAPD and microsatellite markers

2011 ◽  
Vol 46 (9) ◽  
pp. 1035-1044 ◽  
Author(s):  
Patrícia Coelho de Souza Leão ◽  
Sérgio Yoshimitsu Motoike
Keyword(s):  
Genetic Diversity ◽  
Microsatellite Markers ◽  
Genetic Relationships ◽  
Similarity Index ◽  
Genetic Distances ◽  
Table Grape ◽  
Group Method ◽  
Molecular Characteristics ◽  
Table Grapes ◽  
Pair Group

The objective of this work was to analyze the genetic diversity of 47 table grape accessions, from the grapevine germplasm bank of Embrapa Semiárido, using 20 RAPD and seven microsatellite markers. Genetic distances between pairs of accessions were obtained based on Jaccard's similarity index for RAPD data and on the arithmetic complement of the weighted index for microsatellite data. The groups were formed according to the Tocher's cluster analysis and to the unweighted pair‑group method with arithmetic mean (UPGMA). The microsatellite markers were more efficient than the RAPD ones in the identification of genetic relationships. Information on the genetic distance, based on molecular characteristics and coupled with the cultivar agronomic performance, allowed for the recommendation of parents for crossings, in order to obtain superior hybrids in segregating populations for the table grape breeding program of Embrapa Semiárido.

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