An investigation of the taxonomy of Hordeum capense and H. secalinum (Poaceae: Triticeae)

1989 ◽  
Vol 67 (2) ◽  
pp. 594-599 ◽  
Author(s):  
Bernard R. Baum ◽  
L. Grant Bailey
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
South African ◽  
Canonical Discriminant Analysis ◽  
Linear Classification ◽  
African Species ◽  
European Species ◽  
Nomenclatural Type ◽  
Logistic Discrimination ◽  
Prevailing View

That Hordeum capense, a South African species, and H. secalinum, a mainly European species, are conspecific, has been the prevailing view for the last 80 years because of a lack of distinguishing markers. In the present paper, morphological separability is demonstrated by means of cluster analysis, classificatory discriminant analysis, logistic discrimination, and canonical discriminant analysis. The performance of the linear classification functions are evaluated by the bootstrap and discussed. Lodicules and epiblasts were found to be good distinguishing markers. The nomenclatural type of H. secalinum has been designated as lectotype instead of the previously designated neotype.

Sapote mamey [Pouteria sapota (Jacquin) H.E. Moore & Stearn]: A potential fruit crop for subtropical regions of Michoacan, Mexico

2007 ◽  
Vol 87 (3) ◽  
pp. 537-544
Author(s):  
Jeannette Sofía Bayuelo-Jiménez ◽  
Norma Rivera Alcantar ◽  
Iván Ochoa
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Seed Weight ◽  
Titratable Acidity ◽  
Fruit Weight ◽  
Canonical Discriminant Analysis ◽  
Soluble Solids ◽  
Fruit Characteristics ◽  
Total Soluble Solids ◽  
Physical And Chemical

Genotypes of sapote mamey, Pouteria sapota [(Jacquin) H.E. Moore & Stearn] from central-western Michoacán in Mexico were characterized based on physical and chemical fruit characteristics. Cluster analysis of data indicated seven distinct genotype clusters. The greatest variability among clusters was attributed to physical and chemical fruit characteristics. Those were fruit weight, length, width, shape and texture; the ratio of fruit weight to seed weight; seed weight and length; mesocarp thickness and weight; epicarp weight; and the compositional components titratable acidity (TA), protein, total soluble solids (TSS), TSS to TA ratio and TSS to pH ratio. Canonical discriminant analysis was a used to identify the most desirable sapote mamey fruits based on physical (fruit and mesocarp weight) and compositional parameters. Two canonical discriminant functions explained >90% of the accumulated variation a mong the seven clusters of genotypes. Fruit weight, mesocarp thickness, and the ratio of total soluble solids to titratable acidity were dominant in the first function; and fruit weight and mesocarp thickness were dominant in the second. These morphological variables could be used for selecting sapote mamey trees with uniform fruit quality for either direct consumption or processing. Key words: Sapotaceae, sapote mamey, Pouteria sapota, cluster analysis, canonical discriminant analysis, fruit, morphological characterization

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.

scholarly journals Phenetic relationship between Lepisorus (J. SM.) Ching (Pteridophyta: Polypodiaceae) and its related genera

1970 ◽  
Vol 16 (2) ◽  
pp. 99-113 ◽  
Author(s):  
Wannachai Chatan ◽  
Thaweesakdi Boonkerd ◽  
Bernard R. Baum
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Multivariate Analyses ◽  
Canonical Discriminant Analysis ◽  
Plant Taxon ◽  
Group 3 ◽  
Anatomical Characters ◽  
Phenetic Relationship ◽  
Group 2 ◽  
Group 1

Multivariate analyses based on morphological and anatomical characters have been performed to investigate the phenetic relationship and to clarify the circumscriptions of the genus Lepisorus (J.Sm.) Ching and its related genera, namely Neocheiropteris Christ, Paragramma T. Moore and Platygyria Ching & S.K. Wu. The dendrogram of cluster analysis separated the plants into three groups at Gower similarity coefficient 0.75. Group 1 and Group 2 consisted of Neocheiropteris palmatopedata (Baker) H. Christ and four species of Platygyria, respectively. Group 3 was Neocheiropteris ensata Ching and two species of Paragramma deeply embedded in the Lepisorus s.s. Canonical discriminant analysis supported the classification inferred from the clustering results. Based on these results, Platygyria and N. palmatopedata should be recognized as distinct genera. On the other hand, N. ensata and the genus Paragramma should be merged to the genus Lepisorus.  Keywords: Lepisorus; Paragramma; Platygyria; Cluster analysis; Canonical discriminant analysis. DOI: 10.3329/bjpt.v16i2.3924 Bangladesh J. Plant Taxon. 16(2): 99-113, 2009 (December)

scholarly journals WOOD ANATOMY OF THE BRAZILIAN SPECIES OF SWARTZIA AND CONSIDERATIONS WITHIN THE TRIBE SWARTZIEAE

IAWA Journal ◽  
2002 ◽  
Vol 23 (4) ◽  
pp. 359-390 ◽  
Author(s):  
Veronica Angyalossy-Alfonso ◽  
Regis B. Miller
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Vessel Diameter ◽  
Diagnostic Value ◽  
Canonical Discriminant Analysis ◽  
Linear Combinations ◽  
Axial Parenchyma ◽  
Brazilian Species ◽  
Linkage Cluster ◽  
Strand Length

Fifty-one Brazilian species and varieties of Swartzia Schreber and eight other genera from the tribe Swartzieae were examined. Features with the greatest diagnostic value for the tribe are intervascular pit size, ray width and frequency, storied structure, axial parenchyma strand length, parenchyma band width, and vessel diameter. We analyzed the wood anatomical data using average linkage cluster analysis and canonical discriminant analysis. With weighted features, cluster analysis grouped the species and varieties of Swartzia into four distinct groups and tribe Swartzieae into seven groups. With unweighted features for both Swartzia and Swartzieae, the canonical discriminant analysis showed that linear combinations of the variables storied structure, number of tiers per millimetre, axial parenchyma strand length, ray height, intervascular pit size, and exclusively uniseriate rays were good discriminators among the groups. We discuss the grouping of the species of Swartzia and compare other genera within the tribe Swartzieae to the four groups of Swartzia.

scholarly journals Morphometrics characterization in White Fulani, Muturu and Pasundan cows

2021 ◽  
Vol 19 (3) ◽  
pp. 319
Author(s):  
Ridwan Olawale Ahmed ◽  
Widya Pintaka Bayu Putra ◽  
Johar Arifin ◽  
Semiu Folaniyi Bello
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Animal Study ◽  
Bos Indicus ◽  
Hierarchical Cluster ◽  
Canonical Discriminant Analysis ◽  
Morphometric Measurements ◽  
Breed Group ◽  
Chest Girth ◽  
White Fulani

<p class="MDPI17abstract"><strong>Objective: </strong>This study was aimed to characterize three different cattle breeds based on the morphometrics.</p><p class="MDPI17abstract"><strong>Methods: </strong>Five (5) morphometrics which include body length (BL), chest girth (CG), withers height (WH), rump length (RL) and chest depth (CD) were measured in each animal. A total of 119 cows belonging to White Fulani (40 heads), Muturu (40 heads) and Pasundan (39 heads) were used in this study. The age of animal study was 20.93±1.62 months (White Fulani), 21.63±1.75 months (Muturu) and 20.46±2.99 months (Pasundan). Hence, two statistical methods of canonical discriminant analysis (CDA) and hierarchical cluster analysis (HCA) methods were computed in this study to characterize of animals based on their morphometrics using SPSS 16.0 package.<strong></strong></p><p class="MDPI17abstract"><strong>Results: </strong>Mostly<strong> </strong>the morphometrics of White Fulani and Pasundan cows are similar while those of Muturu are significantly lower than the two other breeds. Four morphometric measurements of CG, RL, BL and WH were identified as a discriminator variables in animal study based on the CDA method. The CDA of morphometrics able to classify 85% (White Fulani), 100% (Muturu) and 74.4% (Pasundan) of the animal into their original breed group.<strong></strong></p><p class="MDPI17abstract"><strong>Conclusions: </strong>The closeness between observations from White Fulani and Pasundan might be due to them being both Zebu (<em>Bos indicus</em>) unlike the Muturu with a type breed of <em>Bos bracycheros</em>.<strong></strong></p>

scholarly journals The use of quantitative characters in determination of frequently misdiagnosed species within Lepidium L. sect. Dileptium (Brassicaceae)

2011 ◽  
Vol 78 (3) ◽  
pp. 221-227
Author(s):  
Adam Rostański ◽  
Paweł Wąsowicz
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Canonical Discriminant Analysis ◽  
Morphometric Study ◽  
Multivariate Methods ◽  
Species Determination ◽  
Quantitative Characters ◽  
Phenetic Relations

A morphometric study of the three species of <em>Lepidium</em> L. sect. <em>Dileptium</em> DC. is presented. Multivariate methods (cluster analysis and canonical discriminant analysis) were employed to investigate phenetic relations between examined individuals. As a result a set of quantitative characters useful in species determination was proposed and discussed.

Discriminant Analysis and its Applications in Epidemiology

1980 ◽  
Vol 19 (04) ◽  
pp. 220-226 ◽  
Author(s):  
P. A. Lachenbruch ◽  
W. R. Clarke
Keyword(s):  
Discriminant Analysis ◽  
Historical Review ◽  
Review Article ◽  
Logistic Discrimination

This review article discusses current use of discriminant analysis in epidemiology. Contents include historical review, simple extensions and generalizations, examples, evaluation of rules, logistic discrimination, and robustness.

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.

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