scholarly journals MULTIVARIATE ANALYSIS OF THE STEM ANATOMICAL CHARACTERS OF TERMINALIA L. (COMBRETACEAE) IN EGYPT

2021 ◽  
Vol 16 (3) ◽  
pp. 359-387
Author(s):  
Nahed Waly ◽  
Heba Moustafa ◽  
Rim Hamdy ◽  
Ashraf Soliman
Keyword(s):  
Multivariate Analysis ◽  
Principal Component ◽  
Vessel Diameter ◽  
Comparative Investigation ◽  
Microscopical Examination ◽  
Ecological Data ◽  
Stem Anatomy ◽  
Minor Characters ◽  
Fiber Wall ◽  
Anatomical Characters

A comparative investigation of the anatomical characters through a microscopical examination of the prepared transverse sections of the stem was carried out. Six plates with 32 photomicrographs were provided to convincingly show the considerable variations of anatomical characters within the nine examined species. The matrix of 18 anatomical characters which included nine quantitative and nine qualitative was applied for the clustering analysis (CA) followed by the principal component analysis (PCA) using the Multivariate Analysis of Ecological Data, PC-ORD. The results exhibited significant variations among the species resulting in the construction of an artificial key; this key accurately represents a sufficient tool to display the considerable variation among the recognized species prominently. The distinction between Terminalia L., 1767 species based on significant variations in the elements of stem anatomy; axial parenchyma and ray characteristics were considered as important parameters, while vessel diameter, fiber wall thickness, etc. were considered minor characters to differentiate between the studied species. The potential usefulness of the differentiation of these species properly maintains a profound efficiency in pharmaceutical and traditional medicine.

scholarly journals Anatomía comparada del leño de Maytenus en el Noroeste de Argentina (Sudamérica)

2014 ◽  
Vol 20 (2) ◽  
pp. 95-110 ◽  
Author(s):  
Ana María Giménez ◽  
Juana Graciela Moglia ◽  
M. E. Figueroa ◽  
J. A. Díaz-Zírpolo ◽  
Federico Calatayu
Keyword(s):  
Principal Component Analysis ◽  
Wood Anatomy ◽  
Principal Component ◽  
Vessel Diameter ◽  
Diagnostic Features ◽  
Northwestern Argentina ◽  
Diameter Fibre ◽  
Microscopic Features ◽  
Anatomical Characters ◽  
Comparative Wood Anatomy

Comparative wood anatomy of Maytenus in Northwestern Argentina (South America)This paper is a comparative wood anatomy study of four species of the genus Maytenus living in Northwest Argentina: Maytenus vitisidaea, M. viscifolia, M. spinosa and M. cuezzoi. The specimens were collected in Santiago del Estero and Salta, Argentina and wood samples are safeguarded in the collection of the LAM (Laboratory of Wood Anatomy), Faculty of Forestry of Santiago del Estero University (UNSE), Argentina. The terminology used followed the IAWA List of Microscopic Features for Hardwood Identification. The diagnostic features of wood anatomical characters were evaluated by employing statistical methods such as Cluster Analysis (CA) and Principal Component Analysis (PCA). PCA showed vessel diameter, fibre wall, and ray width to be significant variables. CA showed M. cuezzoi and M. viscifolia to have the highest affinity.Anatomía comparada del leño de Maytenus en el Noroeste de Argentina (Sudamérica)El presente trabajo es un estudio de anatomía comparada de madera de cuatro especies del género Maytenus del Noroeste Argentino:Maytenus vitis-idaea, M. viscifolia, M. spinosa y M. cuezzoi. Las muestras fueron recolectadas en Santiago del Estero y Salta, Argentinay se salvaguardan en la colección del LAM (Laboratorio de Anatomía de Madera), Facultad de Ciencias Forestales de la Universidad deSantiago del Estero (UNSE), Argentina. Se empleó la terminología de IAWA (Lista de caracteres anatómicos del xilema de angiospermas).Los caracteres anatómicos de madera fueron evaluados mediante métodos estadísticos tales como análisis de conglomerados (AC) y elAnálisis de Componentes Principales (PCA). El PCA mostró como variables significativas el diámetro de vasos, el espesor de pared de lasfibras y el ancho de radios. El CA mostró que M. cuezzoi y M. viscifolia tienen alta afinidad específica.

Species delimitation of some Argyreia (Convolvulaceae) using phenetic analyses: insights from leaf anatomical data reveal a new species

Botany ◽  
2018 ◽  
Vol 96 (4) ◽  
pp. 217-233 ◽  
Author(s):  
Natthaphong Chitchak ◽  
Paweena Traiperm ◽  
G. Staples ◽  
Pantamith Rattanakrajang ◽  
Pirada Sumanon
Keyword(s):  
New Species ◽  
Principal Component ◽  
Morning Glory ◽  
Ecological Data ◽  
Conservation Assessment ◽  
Operational Taxonomic Units ◽  
Sectioning Method ◽  
Species Complexes ◽  
Anatomical Characters ◽  
A New Species

Argyreia Lour. is one of the most taxonomically complex genera of the morning glory family (Convolvulaceae). The number of named species is now 135, and new species are regularly being described. There are several species complexes that are morphologically similar and difficult to tell apart. Therefore, the aim of this study is to explore the species identification criteria for Argyreia, especially new sources for taxonomically informative characters. Ten accessions representing three morphologically similar Argyreia operational taxonomic units (OTUs) were collected and their anatomical characters were investigated using the leaf peeling technique and paraffin sectioning method. Anatomical character states were analyzed using two phenetic analysis methods: clustering analysis (CA) and principal component analysis (PCA). Three distinct clusters were clearly separated in both PCA and CA at the internal similarity coefficient of 0.48 with a high R-value of 0.89757. Nineteen effectively distinguishable character states were derived from the high loadings of the first two components. In conclusion, two of the separated groups were matched with known species, and the third separated group is here delineated as a new species. Therefore, a new species, Argyreia gyrobracteata Traiperm & Chitchak, is described and illustrated together with ecological data and a preliminary conservation assessment.

scholarly journals Principal Component Analysis in Biometric, Pulp Quality and Anatomical Properties of Thronless Bamboo (Bambusa balcooa)

2019 ◽  
pp. 350-355
Author(s):  
N. Krishnakumar ◽  
S. Umesh Kanna ◽  
K. T. Parthiban
Keyword(s):  
Principal Component Analysis ◽  
Principal Components ◽  
Tamil Nadu ◽  
Principal Component ◽  
Component Analysis ◽  
Vessel Diameter ◽  
Pulp Yield ◽  
Bambusa Balcooa ◽  
Anatomical Characters ◽  
The Impact

Aims: To estimate the impact, connection and association among the biometric attributes, pulping qualities and anatomical characters in Bambusa balcooa. Place and Duration of Study: The study was conducted across the agro climatic regions viz., North Eastern Zone, Northern Zone, Western Zone, Cauvery Delta Zone and Southern Zone of Tamil Nadu, India during 2017-2018. Methodology: The Principal Components Analysis (PCA) was examined to establish the numbers of clusters using Statistical Package for Social Studies (SPSS) version 16.0.1 software in order to identify the patterns of variation (PCA). The principal component analysis was computed using the equation PCA = Σa jXj. Results: The PCA separated into three cluster principal components among the nineteen parameters studied. Out of nineteen principal components generated, twelve principal components had contributed positively on pulp yield. Among these twelve traits, maximum contribution to the pulp yield was observed by the traits viz., numbers of culms, hollocellulose, kappa number, tear index, burst index, fibre wall thickness and vessel diameter with respect to Bambusa balcooa. Conclusion: The results showed some relationships between the biometric attributes, pulping qualities and anatomical characters in Bambusa balcooa. PCA was shown to be a useful tool for assessing the impact and connection for further research.

scholarly journals The Development of Athlete Performance Capabilities Index (APCI) Model for Male U12 Player Selection using Multivariate Analysis

2018 ◽  
Vol 7 (4.34) ◽  
pp. 97
Author(s):  
Mohamad Razali Abdullah ◽  
Hafizan Juahir ◽  
N. Mohamad Shukri ◽  
N. A. Fuat ◽  
N. A. Mohd Ros ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Factor Score ◽  
Principal Component ◽  
Factor Loading ◽  
Group Classification ◽  
Performance Group ◽  
Two Factors ◽  
Low Performance ◽  
High Factor Loading ◽  
Athlete Performance

This study develops an Athlete Performance Capabilities Index (APCI) model using multivariate analysis for selecting the best player of under twelve (U12).  Measurement of anthropometrics and physical fitness were evaluated among 178 male players aged 12±0.52 years. Factor score derived by Principal Component Analysis were used to obtain a model for APCI and Discriminant Analysis (DA) were conducted to validate the correctness of group classification by APCI. Result was found two factors with eigenvalues greater than 1 were extracted which accounted for 62.00% of the variations present in the original variables. The two factors were used to obtain the factor score coefficients explained by 35.72% and 26.67% of the variations in athlete performance respectively. Factor 1 revealed high factor loading on fitness compared to Factor 2 as it was significantly related to anthropometrics. A model was obtained using standardized coefficient of factor 1. Three clusters of performance were shaped in view by categorizing APCI ≥ 75%, 25% ≤ APCI < 75% and APCI < 25% as high, moderate and low performance group respectively. Three discriminated variables out of thirteen variables were obtained using Forward and Backward stepwise mode of DA, which were weight, standing broad jump, and 40 meters’ speed. Such variables were established as essential indicator for selecting the best player among male U12.   

Multivariate Analysis of Ecological Data with ade4

2018 ◽  
Author(s):  
Jean Thioulouse ◽  
Stéphane Dray ◽  
Anne-Béatrice Dufour ◽  
Aurélie Siberchicot ◽  
Thibaut Jombart ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Ecological Data

scholarly journals Multivariate analysis as a tool for measuring the stability of morphometric traits in Lycopersicon plants from in vitro culture

2000 ◽  
Vol 23 (2) ◽  
pp. 479-493 ◽  
Author(s):  
Guillermo Pratta ◽  
Roxana Zorzoli ◽  
Liliana Amelia Picardi
Keyword(s):  
Multivariate Analysis ◽  
In Vitro Culture ◽  
Principal Component ◽  
Eigenvalues And Eigenvectors ◽  
Morphometric Traits ◽  
Regenerated Plants ◽  
Phenotypic Structure ◽  
Regeneration Cycle ◽  
The Stability

The phenotypic stability of morphometric traits in Lycopersicon spp. (stem perimeter at the base, middle and top, and number of flowers per cluster) was measured by multivariate analysis through a progeny test in order to estimate the genetic stability of these traits. Principal components were calculated for two groups of Lycopersicon spp., non-regenerated plants and the progeny of regenerated plants. Analysis of variance was performed to support principal component analysis. Both groups presented similar eigenvalues and eigenvectors, while no significant differences were found between any of the traits studied. These results indicated that the phenotypic structure was the same among the progeny of regenerated and non-regenerated plants, so that no variation would occur in in vitro culture. Multivariate analysis proved to be an appropriate methodology for the measurement of the stability of morphometric traits after one regeneration cycle.

scholarly journals Use of Highly Discriminating Morphological Characters and Isozymes in the Study of Spanish Chestnut Cultivars

2006 ◽  
Vol 131 (6) ◽  
pp. 770-779 ◽  
Author(s):  
Santiago Pereira-Lorenzo ◽  
María Belén Díaz-Hernández ◽  
Ana María Ramos-Cabrer
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Multivariate Analysis ◽  
Castanea Sativa ◽  
Principal Component ◽  
Market Value ◽  
Morphological Characters ◽  
Minor Importance ◽  
Breeding Programs ◽  
And Cluster Analysis

Morphological characters (six traits) and isozymes (four systems, five loci) were used to discriminate between Spanish chestnut cultivars (Castanea sativa Mill.) from the Iberian Peninsula. A total of 701 accessions (representing 168 local cultivars) were analyzed from collections made between 1989 and 2003 in the main chestnut growing areas: 31 were from Andalucía (12 cultivars), 293 from Asturias (65 cultivars), 25 from Castilla-León (nine cultivars), four from Extremadura (two cultivars) and 348 from Galicia (80 cultivars). Data were synthesized using multivariate analysis, principal component analysis, and cluster analysis. A total of 152 Spanish cultivars were verified: 58 cultivars of major importance and 94 of minor importance, of which 18 had high intracultivar variation. Thirty-seven cultivars were clustered into 14 synonymous groups. Six of these were from Galicia, one from Castilla-León (El Bierzo), four from Asturias, one from Asturias and Castilla-León (El Bierzo), and two from Asturias, Castilla-León (El Bierzo), and Galicia. The chestnut cultivars from Galicia and Asturias were undifferentiated in genetic terms, indicating that they are not genetically isolated. Overall, chestnut cultivars from southern Spain showed the least variation. Many (58%) of Spanish cultivars produced more than 100 nuts/kg; removing this low market-value character will be a high priority. The data obtained will be of use in chestnut breeding programs in Spain and elsewhere.

scholarly journals Inferência Exploratória de Dados Espaço-Temporal da Precipitação Pluviométrica no Nordeste Brasileiro

2020 ◽  
Vol 13 (5) ◽  
pp. 2019
Author(s):  
Jhon Lennon Bezerra da Silva ◽  
Geber Barbosa De Albuquerque Moura ◽  
Marcos Vinícios Da Silva ◽  
Roni Valter De Souza Guedes ◽  
Pabrício Marcos Oliveira Lopes ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Multivariate Analysis ◽  
Temporal Variability ◽  
Principal Component ◽  
Component Analysis ◽  
Northeastern Brazil ◽  
Annual Rainfall ◽  
Intermittent Rivers ◽  
Rainfall Patterns ◽  
Brazilian Northeast

A gestão eficiente dos recursos hídricos no Nordeste brasileiro torna-se fundamental diante do regime hidrológico dos rios intermitentes, dos quais muitos são extremamente críticos. Todavia estes dependem de um regime pluviométrico irregular, tanto em escala de tempo mensal quanto anual. Objetivou-se determinar a variabilidade espaço-temporal da precipitação pluviométrica total anual, averiguando-se, também, as regiões com padrões de precipitação semelhantes por técnicas de análise multivariada (clusters e componentes principais) no Nordeste do Brasil. Foram analisados dados de precipitação pluviométrica total anual, entre os anos de 1995 e 2016, de 37 diferentes estações meteorológicas do INMET, estas situadas nos limites territoriais dos nove estados do Nordeste brasileiro. A análise de clusters verificou a formação de quatro grupos distintos, com padrões semelhantes de precipitação nas regiões dentro dos grupos, conforme também observado na análise de componentes principais. A padronização e/ou variabilidade espaço-temporal da precipitação pluviométrica dos municípios analisados mostrou-se está intimamente associada as condições das estações do ano e anomalias climatológicas, aos fatores de uso e ocupação do solo, condições de altitude e relevo, tais quais favorecem na formação e estabilidade de chuvas menores ou maiores no Nordeste brasileiro. A análise multivariada de cluster e componentes principal identificaram padrões e semelhanças pluviométricas de grupos, nos diferentes estados do Nordeste do Brasil entre os anos de 1995 e 2016. Exploratory Inference of Spatial-Temporal Data of Rainfall in the Brazilian Northeast ABSTRACTThe efficient management of water resources in the Northeast of Brazil is essential in view of the hydrological regime of intermittent rivers, of which many are extremely critical, as they depend on an irregular rainfall regime, both on a monthly and annual time scale. The objective of this study was to determine the spatial and temporal variability of the annual total rainfall, also investigating the regions with similar rainfall patterns by multivariate analysis techniques (clusters and principal components) in Brazilian Northeast. Data from total annual rainfall between the years 1995 and 2016, of 37 different INMET weather stations were analyzed, located within the territorial limit of the nine states of Brazilian Northeast. Cluster analysis verified the formation of four distinct groups, with similar precipitation patterns in the regions within the groups as also observed in the principal component analysis. The pattern and/or spatial-temporal variability of rainfall in the municipalities analyzed was shown to be intimately associated with the conditions of the year and climatic anomalies stations, and the factors of land use and occupation, altitude and relief conditions, such as favoring the formation and stability of minor or major rain in the Brazilian Northeast. Multivariate cluster and principal component analysis identified rainfall patterns and similarities of groups, in the different states of Northeastern Brazil between the years 1995 and 2016.Keywords: multivariate analysis, climate change, semiarid, regional climate patterns.

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