scholarly journals Taxonomic studies on the Chara section Hartmania in Poland based on morphological and molecular data

PhytoKeys ◽  
2019 ◽  
Vol 135 ◽  
pp. 71-90
Author(s):  
Jacek Urbaniak ◽  
Paweł Kwiatkowski
Keyword(s):  
Discriminant Analysis ◽  
Morphological Characteristics ◽  
Principal Component ◽  
Taxonomic Status ◽  
Component Analysis ◽  
Molecular Data ◽  
Morphological Features ◽  
Green Macroalgae ◽  
Molecular Group ◽  
Water Ecosystems

Charophytes are aquatic green macroalgae, which inhabit fresh and brackish water ecosystems. In this study, four species belonging to the genus Chara were examined to determine their taxonomic status. Morphological characteristics of the plant bodies as well as plastid psaB barcoding genes were applied to test the relations among Chara species. Plants were initially classified using morphological features into four species: C. baltica, C. hispida, C. polyacantha and C. rudis, and twelve quantitative characters were used in a principal component analysis and discriminant analysis to determine groupings among the species and to determine the morphological features that best separated the groups. In the component analysis and discriminant analysis, results showed that only C. polyacantha and partly C. baltica formed separate groups. The other species C. hispida and C. rudis were only partially distinguishable. All species from one molecular group, and no differentiation in the psaB variability between them has been found.

scholarly journals Morphological evaluation of common bean diversity in Bosnia and Herzegovina using the discriminant analysis of principal components (DAPC) multivariate method

Genetika ◽  
2013 ◽  
Vol 45 (3) ◽  
pp. 963-977 ◽  
Author(s):  
Jasmin Grahic ◽  
Fuad Gasi ◽  
Mirsad Kurtovic ◽  
Lutvija Karic ◽  
Mirha Djikic ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Common Bean ◽  
Bosnia And Herzegovina ◽  
Principal Components ◽  
Morphological Characteristics ◽  
Principal Component ◽  
Discriminant Functions ◽  
Factor Loadings ◽  
Geographical Regions ◽  
High Level

In order to analyze morphological characteristics of locally cultivated common bean landraces from Bosnia and Herzegovina (B&H), thirteen quantitative and qualitative traits of 40 P. vulgaris accessions, collected from four geographical regions (Northwest B&H, Northeast B&H, Central B&H and Sarajevo) and maintained at the Gene bank of the Faculty of Agriculture and Food Sciences in Sarajevo, were examined. Principal component analysis (PCA) showed that the proportion of variance retained in the first two principal components was 54.35%. The first principal component had high contributing factor loadings from seed width, seed height and seed weight, whilst the second principal component had high contributing factor loadings from the analyzed traits seed per pod and pod length. PCA plot, based on the first two principal components, displayed a high level of variability among the analyzed material. The discriminant analysis of principal components (DAPC) created 3 discriminant functions (DF), whereby the first two discriminant functions accounted for 90.4% of the variance retained. Based on the retained DFs, DAPC provided group membership probabilities which showed that 70% of the accessions examined were correctly classified between the geographically defined groups. Based on the taxonomic distance, 40 common bean accessions analyzed in this study formed two major clusters, whereas two accessions Acc304 and Acc307 didn?t group in any of those. Acc360 and Acc362, as well as Acc324 and Acc371 displayed a high level of similarity and are probably the same landrace. The present diversity of Bosnia and Herzegovina?s common been landraces could be useful in future breeding programs.

scholarly journals Analisis Metode Pengenalan Wajah Two Dimensial Principal Component Analysis (2DPCA) dan Kernel Fisher Discriminant Analysis Menggunakan Klasifikasi KNN (K- Nearest Neighbor)

2020 ◽  
Vol 2 (2) ◽  
pp. 29-38
Author(s):  
Abdur Rohman Harits Martawireja ◽  
Hilman Mujahid Purnama ◽  
Atika Nur Rahmawati
Keyword(s):  
Principal Component Analysis ◽  
Discriminant Analysis ◽  
Cross Validation ◽  
Nearest Neighbor ◽  
Principal Component ◽  
Component Analysis ◽  
K Nearest Neighbor ◽  
Fisher Discriminant Analysis ◽  
Fisher Discriminant ◽  
Kernel Fisher Discriminant Analysis

Pengenalan wajah manusia (face recognition) merupakan salah satu bidang penelitian yang penting dan belakangan ini banyak aplikasi yang menerapkannya, baik di bidang komersil ataupun di bidang penegakan hukum. Pengenalan wajah merupakan sebuah sistem yang berfungsikan untuk mengidentifikasi berdasarkan ciri-ciri dari wajah seseorang berbasis biometrik yang memiliki keakuratan tinggi. Pengenalan wajah dapat diterapkan pada sistem keamanan. Banyak metode yang dapat digunakan dalam aplikasi pengenalan wajah untuk keamanan sistem, namun pada artikel ini akan membahas tentang dua metode yaitu Two Dimensial Principal Component Analysis dan Kernel Fisher Discriminant Analysis dengan metode klasifikasi menggunakan K-Nearest Neigbor. Kedua metode ini diuji menggunakan metode cross validation. Hasil dari penelitian terdahulu terbukti bahwa sistem pengenalan wajah metode Two Dimensial Principal Component Analysis dengan 5-folds cross validation menghasilkan akurasi sebesar 88,73%, sedangkan dengan 2-folds validation akurasi yang dihasilkan sebesar 89,25%. Dan pengujian metode Kernel Fisher Discriminant dengan 2-folds cross validation menghasilkan akurasi rata rata sebesar 83,10%.

2D Image Matrix-Based Discriminator

2006 ◽  
pp. 258-286
Author(s):  
David Zhang ◽  
Xiao-Yuan Jing ◽  
Jian Yang
Keyword(s):  
Principal Component Analysis ◽  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Two Dimensional ◽  
Fisher Linear Discriminant ◽  
Linear Discriminant ◽  
Image Projection ◽  
Projection Techniques

This chapter presents two straightforward image projection techniques — two-dimensional (2D) image matrix-based principal component analysis (IMPCA, 2DPCA) and 2D image matrix-based Fisher linear discriminant analysis (IMLDA, 2DLDA). After a brief introduction, we first introduce IMPCA. Then IMLDA technology is given. As a result, we summarize some useful conclusions.

scholarly journals Development of a Piezoelectric-Based Odor Reproduction System

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 870
Author(s):  
Tengteng Wen ◽  
Dehan Luo ◽  
Yongjie Ji ◽  
Pingzhong Zhong
Keyword(s):  
Principal Component Analysis ◽  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Electronic Nose ◽  
Principal Component ◽  
Component Analysis ◽  
Piezoelectric Transducers ◽  
Linear Discriminant ◽  
Reproduction System ◽  
Machine Olfaction

Odor reproduction, a branch of machine olfaction, is a technology through which a machine represents various odors by blending several odor sources in different proportions and releases them. In this paper, an odor reproduction system is proposed. The system includes an atomization-based odor dispenser using 16 micro-porous piezoelectric transducers. The authors propose the use of an electronic nose combined with a Principal Component Analysis–Linear Discriminant Analysis (PCA–LDA) model to evaluate the effectiveness of the system. The results indicate that the model can be used to evaluate the system.

scholarly journals Morphological variability of acorns and its taxonomic significance in Quercus. from Turkey

2015 ◽  
Vol 43 (3) ◽  
pp. 293-299 ◽  
Author(s):  
Y Bakis ◽  
MT Babaç
Keyword(s):  
Principal Component Analysis ◽  
Morphological Variability ◽  
Morphological Characteristics ◽  
Principal Component ◽  
Component Analysis ◽  
Morphological Characters ◽  
Taxonomic Significance ◽  
Morphological Variations ◽  
Quercus Species ◽  
Different Populations

Morphological variations of acorn among and within the groups of Quercus species were studied. A total of 617 acorns belonging to 14 species representing all 3 sections of Quercus L. (Fagaceae) in Turkey were examined in this study. Specimens were collected from 47 different populations over both Anatolian and Thrace part of Turkey. Principal component analysis was used to analyze the morphological characteristics of acorns. Results obtained from this study demonstrate the use of morphological characters in differentiating the taxa of Quercus and Cerris sections studied. Another important finding is the introgression among the acorns of species within Quercus section DOI: http://dx.doi.org/10.3329/bjb.v43i3.21601 Bangladesh J. Bot. 43(3): 293-299, 2014 (December)

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