Numerical taxonomy of hybridizing Lepomis (Centrarchidae) in Lake Opinicon, Ontario

1976 ◽  
Vol 54 (1) ◽  
pp. 42-47 ◽  
Author(s):  
P. W. Colgan ◽  
P. K. Ballantyne ◽  
M. V. H. Wilson
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Reproductive Behavior ◽  
Numerical Taxonomy ◽  
Parental Species ◽  
Morphological Characters ◽  
Lepomis Gibbosus ◽  
Discriminant Functions ◽  
Body Depth ◽  
Using Data

Cluster analysis of hybridizing Lepomis gibbosus (pumpkinseedsl and L. macrochirus (bluegills)collecled in Lake Opinicon, Ontario, using data on 20 morphological characters in 108 specimens, revealed three groups, the two parental species and a group of hybrids, all of which were clearly separated by discriminant analysis. Discriminant functions based on the red opercular flap, the pharyngeal dentition, and body depth, correctly assigned all specimens to the appropriate group. Discriminant functions are also reported for external characters only, but the assignment to groups is not perfect. A sample of L. gibbosus, taken from a locality in which other Lepomis species were not present, was found to be very similar to the Lake Opinicon sample of this species. The hybrids of Lake Opinicon do not appear to backcross frequently with the parental species, possibly because of nonintermediacy in reproductive behavior.

scholarly journals A phenetic study of the genus Rasahus Amyot & Serville (Heteroptera, Reduviidae)

1990 ◽  
Vol 1 (3) ◽  
pp. 131-144
Author(s):  
María Coscarón
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Morphological Characters ◽  
Basal Plate ◽  
Using Data ◽  
Diagnostic Importance

Cluster analysis by four methods and a principal component analysis were performed using data on 24 morphological characters of 27 species of the genus Rasahus (Peiratinae). The results obtained by the different techniques show general agreement. They confirm the present number of taxa and reveal the existence within the genus of three groups of species: scutellaris , hamatus and vittatus. The scutellaris group is constituted by R. aeneus (Walker), R. maculipennis (Lepelletier and Serville), R. bifurcatas Champion, R. castaneus Coscarón, R. guttatipennis (Stål), R. flavovittarus Stål, R. costarricensis Coscarón, R. scutellaris (Fabricius), R. atratus Coscarón, R. peruensis Coscarón, R. paraguayensis Coscarón, R. surinamensis Coscarón, R. albomaculatus Mayr, R. brasiliensis Coscarón and R. sulcicollis (Serville).The hamatus group contains R. rufiventris (Walker), R. hamatus (Fabricius), R. amapaensis Coscarón, R. arcitenens Stål, R. limai Pinto, R. angulatus coscarón, R. thoracicus Stål, R. biguttatus (Say), R. arcuiger (Stål), R. argentinensis Coscarón and R. grandis Fallou. The vittatus group contains R. vittatus Coscarón. The characters used to separate the groups of species are: shape of the pygophore, shape of the parameres, basal plate complexity, shape of the postocular region and hemelytra pattern. Illustrations of the structures of major diagnostic importance are included.

scholarly journals Effects of Media and Frame Rates on Hyperactivated Bovine Sperm Motility and an Analysis of Sperm Motility Subpopulation Structures in Sex-Sorted and Non-Sorted Semen

2021 ◽  
Author(s):  
Chihiro Kanno ◽  
Sun-Sik Kang ◽  
Kentaro Q. Sakamoto ◽  
Yojiro Yanagawa ◽  
Seiji Katagiri ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Sperm Motility ◽  
Computer Assisted ◽  
Motile Sperm ◽  
Progressive Motility ◽  
Bovine Sperm ◽  
Using Data ◽  
Effects Of Media ◽  
Oviductal Fluid

We attempted to establish an objective method to accurately evaluate the motility of bull sperm and examined the effects of media for sperm suspensions and frame rates on data of computer-assisted sperm motility analysis (CASA). Sperm incubated in Brackett and Oliphant medium (BO) more clearly showed hyperactivation-like motility than those in synthetic oviductal fluid. Sperm images captured at 150 frames per second (fps) showed a trajectory that was closer to the real pathway than those at other frame rates (30, 50, and 75 fps). We then examined the characteristics of sex-sorted and non-sorted semen using a cluster analysis followed by a discriminant analysis of sperm motility in BO at 150 fps. The results indicated that sex-sorted semen contained sperm with hyperactivation-like motility as the main subpopulation immediately after thawing and this subpopulation decreased after 2-h incubation. The main subpopulation in non-sorted semen had progressive motility that was maintained during incubation. In conclusion, usage of BO for sperm suspensions and capturing sperm motility at 150 fps by CASA were appropriate for evaluating bovine sperm motility. A discriminant analysis using data from a cluster analysis of motile sperm has the ability to accurately describe differences in the structures of sperm motility subpopulations.

scholarly journals Morphometry analysis and seed germination of Amaranthus cruentus, A. retroflexus and their hybrid (A. × turicensis)

2011 ◽  
Vol 49 (No. 8) ◽  
pp. 364-369 ◽  
Author(s):  
V. Lanta ◽  
P. Havránek ◽  
V. Ondřej
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Parental Species ◽  
Chromosome Analysis ◽  
Canonical Discriminant Analysis ◽  
Day Length ◽  
Morphometric Study ◽  
Amaranthus Cruentus ◽  
Morphometry Analysis ◽  
Germination Experiment

A morphometric study of Amaranthus cruentus, A. retroflexus and their hybrid, A. × turicensis based on 75 plant samples (750 inflorescences), collected throughout the Olomouc-Holice area (Czech   Republic), is presented. Using multivariete methods (including cluster analysis and canonical discriminant analysis), the existence of three groupings of plants was proven. The hybrid exhibited intermediate values of the width and length of female tepals, length of awl-shaped bracts, and seed size when compared with parental species. A germination experiment showed that dark seeds of A. × turicensis as well as dark seeds of A. retroflexus germinate scarcely and independently on the day length while light seeds of A. cruentus germinate promptly and markedly better under a short day regime. The chromosome analysis showed that A. retroflexus, A. cruentus, and A. × turicensis have the same chromosome number 34.

Morphometric analysis of Polish members of the Potentilla subsect. Collinae in Poland

Biologia ◽  
2010 ◽  
Vol 65 (2) ◽  
Author(s):  
Jeremi Kołodziejek
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Morphometric Analysis ◽  
Numerical Taxonomy ◽  
Principal Component ◽  
Morphological Characters ◽  
Length Ratio ◽  
Operational Taxonomic Units ◽  
Petal Length ◽  
Flower Diameter

AbstractMethods of numerical taxonomy, i.e. Cluster Analysis, Principal Component Analysis (PCA), Discriminant Function (DF) and Correspondence Analysis (CA), have been used to analyse 132 Operational Taxonomic Units of Potentilla subsect. Collinae. Among 53 morphological characters (20 quantitative and 33 qualitative), the most useful appeared following: bent inflorescence, flower diameter, width of epicalyx segments, length and width of petal, length ratio of calyx to petals, length ratio of calyx to epicalyx segments, shape of carpel style, presence of basal leaves during flowering, number of leaflets on basal leaves, upper and lower surfaces of leaf blades, pattern of pubescence of calyx, nervation of leaves as well as number and size of teeth of the central leaflet. The following taxa were distinguished in the investigated subsection: P. collina Wibel s.str.; P. thyrsiflora Hülsen ex Zimmeter; P. silesiaca R. Uechtr.; P. wimannania Günther et Schummel; P. leucopolitana P.J. Müll.; P. karoi R. Uechtr. ex Zimmeter; P. schultzii P.J. Müll. ex F. W. Schultz; P. koernickei R. Uechtr. ex Zimmeter; P. leucopolitanoides Błocki; P. ×sholziana Callier; P. leucopolitana P.J. Müller × P. incana P. Gaertner, B. Meyer & Scherb.); P. × tynieckii Błocki (P. argentea L. × P. leucopolitana P.J. Müll.).

scholarly journals Pengelompokan 33 Aksesi Kakao Berdasarkan Karakter Morfologi Komponen Buah

2017 ◽  
Vol 4 (2) ◽  
pp. 67
Author(s):  
Edi Wardiana ◽  
Juniaty Towaha ◽  
Syafaruddin Syafaruddin
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Discriminant Analysis ◽  
Hierarchical Cluster Analysis ◽  
Morphological Character ◽  
Hierarchical Cluster ◽  
Dry Weight ◽  
Morphological Characters ◽  
Fresh Weight ◽  
Experimental Station

<em>Identification and grouping of diverse cacao accessions based on morphological character of pod components is important in breeding activities to generate superior varieties. This study aimed to grouping 33 cocoa accessions based on morphological characters of pod components, conducted at Pakuwon Experimental Station, Sukabumi, West Java, at an altitude of 450 asl with Latosol soil and B type climate (Schmidt and Fergusson), from January until December 2015. Observation was taken on 33 cacao accessions of Kaliwining (KW), planted in 2012 with 3 m x 3 m spacing under 26 years old Genjah Salak coconut trees as shading. Ten mature pods were randomly harvested from 10 cocoa plants of each accession at respective two seasons (February and December 2015). The variables observed were 7 characters of pod components i.e.: (1) fresh weight of pod, (2) number of beans, (3) fresh weight of beans, (4) dry weight of beans, (5) fresh weight of pod husk, (6) number of pod furrow, and (7) fresh weight of pulp. Data were analyzed by factor analysis followed by hierarchical cluster analysis in Ward's method and discriminant analysis. The result showed that 19 accessions were classified as high in bean and pod husk component characters, 9 accessions were classified as high in pulp characters, and 5 accessions i.e. KW 162, KW 528, KW 570, KW 571, and KW 720 were classified as high in all characters of pod components, and potential as parents in generating superior cacao varieties.</em>

Comparison of Examinees’ and Doctors’ Judgement of Health Status Using Data in an AMHTS

1984 ◽  
Vol 23 (01) ◽  
pp. 15-22
Author(s):  
Y. Sekita ◽  
T. Ohta ◽  
M. Inoue ◽  
H. Takeda
Keyword(s):  
Health Status ◽  
Discriminant Analysis ◽  
Explanatory Power ◽  
Laboratory Data ◽  
Subjective Symptom ◽  
Health Conditions ◽  
Testing System ◽  
Multiple Discriminant Analysis ◽  
Canonical Axis ◽  
Using Data

SummaryJudgements of examinees’ health status by doctors and by the examinees themselves are compared applying multiple discriminant analysis. The doctors’ judgements of the examinees’ health status are studied comparatively using laboratory data and the examinees’ subjective symptom data.This data was obtained in an Automated Multiphasic Health Testing System. We discuss the health conditions which are significant for the judgement of doctors about the examinees. The results show that the explanatory power, when using subjective symptom data, is fair in the case of the doctors’ judgement. We found common variables, such as nervousness, lack of perseverance etc., which form the first canonical axis.

Classifying the Past: Discriminant Analysis and its Application to Medieval Farming Systems

1996 ◽  
Vol 8 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Ken Bartley
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Processing Time ◽  
Farming Systems ◽  
Frame Of Reference ◽  
Analytical Models ◽  
Successful Implementation ◽  
Medieval Period ◽  
The Past ◽  
Livestock Management

This paper discusses the need for nationally based analytical models of the medieval period. The use of cluster analysis as a method for classifying demesne farms, by the crops they grew and their livestock management, is explained. Successful implementation of cluster analysis requires both the existence of a large base sample, to permit isolation of specific groupings within the data, and access to considerable processing time. The paper concludes by demonstrating how discriminant analysis can provide an efficient and systematic way of classifying even a single manor within a national frame of reference.

Multivariate consumption profiling (MCP) for intelligent meter systems: a methodology to define categories and levels

2010 ◽  
Vol 10 (5) ◽  
pp. 710-720 ◽  
Author(s):  
J. L. Solanas ◽  
M. R. Cussó
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Multivariate Analysis ◽  
Discriminant Analysis ◽  
Reference Population ◽  
Statistical Analyses ◽  
Conceptual Schema ◽  
Data Variability ◽  
Water Companies ◽  
Analyse Data

Multivariate Consumption Profiling (MCP) is a methodology to analyse the readings made by Intelligent Meter (IM) systems. Even in advanced water companies with well supported IM, full statistical analyses are not performed, since no efficient methods are available to deal with all the data items. Multivariate Analysis has been proposed as a convenient way to synthesise all IM information. MCP uses Factor Analysis, Cluster Analysis and Discriminant Analysis to analyse data variability by categories and levels, in a cyclical improvement process. MCP obtains a conceptual schema of a reference population on a set of classifying tables, one for each category. These tables are quantitative concepts to evaluate consumption, meter sizing, leakage and undermetering for populations and groupings and individual cases. They give structuring items to enhance “traditional” statistics. All the relevant data from each new meter reading can be matched to the classifying tables. A set of indexes is computed and thresholds are used to select those cases with the desired profiles. The paper gives an example of a MCP conceptual schema for five categories, three variables, and five levels, and obtains its classifying tables. It shows the use of case profiles to implement actions in accordance with the operative objectives.

Effect of Topography on Maize Grains Elemental Profile: A Chemometric Approach

2020 ◽  
Vol 16 (8) ◽  
pp. 1079-1087
Author(s):  
Jorgelina Z. Heredia ◽  
Carlos A. Moldes ◽  
Raúl A. Gil ◽  
José M. Camiña
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Microwave Plasma ◽  
Emission Spectrometry ◽  
Linear Discriminant ◽  
Maize Seeds ◽  
Elemental Profile ◽  
Mineral Profile ◽  
Topographic Characteristics

Background: The elemental composition of maize grains depends on the soil, land and environment characteristics where the crop grows. These effects are important to evaluate the availability of nutrients with complex dynamics, such as the concentration of macro and micronutrients in soils, which can vary according to different topographies. There is available scarce information about the influence of topographic characteristics (upland and lowland) where culture is developed with the mineral composition of crop products, in the present case, maize seeds. On the other hand, the study of the topographic effect on crops using multivariate analysis tools has not been reported. Objective: This paper assesses the effect of topographic conditions on plants, analyzing the mineral profiles in maize seeds obtained in two land conditions: uplands and lowlands. Materials and Methods: The mineral profile was studied by microwave plasma atomic emission spectrometry. Samples were collected from lowlands and uplands of cultivable lands of the north-east of La Pampa province, Argentina. Results: Differentiation of maize seeds collected from both topographical areas was achieved by principal components analysis (PCA), cluster analysis (CA) and linear discriminant analysis (LDA). PCA model based on mineral profile allowed to differentiate seeds from upland and lowlands by the influence of Cr and Mg variables. A significant accumulation of Cr and Mg in seeds from lowlands was observed. Cluster analysis confirmed such grouping but also, linear discriminant analysis achieved a correct classification of both the crops, showing the effect of topography on elemental profile. Conclusions: Multi-elemental analysis combined with chemometric tools proved useful to assess the effect of topographic characteristics on crops.

scholarly journals Diversity of Common Bean Landraces Collected in the Western and Eastern Carpatien

2011 ◽  
Vol 39 (No. 3) ◽  
pp. 73-83 ◽  
Author(s):  
O. Horňáková ◽  
M. Závodná ◽  
M. Žáková ◽  
J. Kraic ◽  
F. Debre
Keyword(s):  
Cluster Analysis ◽  
Common Bean ◽  
Morphological Characters ◽  
Molecular Data ◽  
Seed Traits ◽  
Phaseolus Vulgaris L ◽  
Growth Type ◽  
Banding Patterns ◽  
Polymorphism Detection ◽  
Thousand Seed Weight

The study of diversity in common bean was based on morphological and agronomical characteristics, differentiation of collected accessions by morphological and molecular markers, detection of genetic variation, and duplicates detection in bean landraces. The analysed 82 accessions of common bean (Phaseolus vulgaris L.) were collected in the Western andEastern Carpatien as landrace mixtures. Their seeds were segregated and pooled according to their characteristics; they were further multiplicated, and introduced into the collection. An extensive variation in plant and seed traits was discovered in thirty-three morphological and agronomical characteristics. Nevertheless, some of the accessions were identical in these characteristics. Cluster analysis grouped genotypes into two main branches, reflecting the growth type, seed size parameters, and thousand-seed weight. Molecular differentiation studies were performed by multilocus polymorphism detection in microsatellite and minisatellite DNA regions. Cluster analysis based on molecular data also grouped genotypes but no linkage to morphological traits was revealed. Bean accessions with very similar or identical morphological characters were clearly distinguished by DNA banding patterns. The presence of duplicates was excluded. &nbsp;

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