scholarly journals A morphometric study on Senecio erucifolius (Asteraceae) from Poland and its taxonomic implications

2016 ◽  
Vol 85 (2) ◽  
Author(s):  
Marek Podsiedlik ◽  
Renata Nowińska ◽  
Leszek Bednorz
Keyword(s):  
Discriminant Analysis ◽  
Lateral Lobe ◽  
Principal Component ◽  
Morphological Diversity ◽  
Leaf Length ◽  
Morphometric Study ◽  
Stepwise Discriminant Analysis ◽  
Morphological Heterogeneity ◽  
Middle Leaf ◽  
Tubular Flower

Twenty-three populations of <em>Senecio erucifolius</em> were sampled to study morphological diversity of the species in Poland. A total of 690 shoots, leaves, capitula, flowers, and fruits were characterized in respect to 27 quantitative traits and were subjected to morphometric analyses. Principal component analysis made it possible to distinguish two groups of individuals, corresponding to two infraspecific taxa – <em>S. erucifolius</em> subsp. <em>tenuifolius</em> (19 populations) and <em>S. erucifolius</em> subsp. <em>erucifolius</em> (four populations). The characters of the greatest importance in differentiating these two subspecies included the length of the upper lobe of the middle leaf, the width of the upper lobe, the width of the longest lateral lobe, the width of the upper lobe at the base, and the length of the tubular flower. Six of the 27 morphological features significantly differentiated populations within subspecies <em>erucifolius</em> according to a stepwise discriminant analysis. The length of the middle leaf, length of the tubular flower and width of the upper lobe at the base contributed most to the discrimination between the investigated populations. The discriminant analysis also showed considerable morphological heterogeneity of the 19 populations classified as subspecies <em>tenuifolius</em>. Seventeen characters significantly differentiated the populations, with the length of the achene and the ratio between the length and the width of the achene as the most important ones.

scholarly journals The phytochemical and morphological diversity analysis of Ziziphus nummularia (Burm.f.) Wight & Arn. populations in South of Iran

2020 ◽  
Vol 48 (2) ◽  
pp. 588-603
Author(s):  
Kourosh ZANDIFAR ◽  
Hassanali NAGHID BADI ◽  
Ali MEHRAFARIN ◽  
Majid G. NOHOOJI
Keyword(s):  
Wild Population ◽  
Principal Component ◽  
Morphological Diversity ◽  
Hierarchical Cluster ◽  
Leaf Length ◽  
Wild Populations ◽  
Significant Difference ◽  
In The Wild ◽  
Ziziphus Nummularia ◽  
High Diversity

Ziziphus nummularia is a multipurpose and tropical tree with medicinal, nutritional, industrial, and economic values. This tree, which belongs to the Rhamnaceae family, is originated from the South of Asia and North of Africa. This research was carried out to investigate the phytochemical and morphological diversity of 20 wild populations collected from different Southern regions of Iran. Statistical significant difference ranges between population were found in respect to saponin of the leaf (2.2-5.4 mg/g) and fruit (1.2-3.2 mg/g), phenol of the leaf (0.7-2.9 mg/g) and fruit (0.03-0.4 mg/g), tannin of the leaf (0.8-3.5 mg/g) and fruit (1.5-1.7 mg/g), and flavonoid of the leaf (3.3-4.3 mg/g) and fruit (1.5-2.4 mg/g). A factor analysis based on principal component analysis (PCA) revealed that the first three components (PC1-PC3) explain 79.04% of total variations. The first component (PC1) is explained by the most important traits of the PCA coefficient such as the leaf saponin, width of the end leaf, fruit saponin, length of the end leaf, leaf length and width, and leaf phenol with 42% of the total variation. Hierarchical cluster analysis divided the populations into four main groups with high diversity. In general, the Izeh Tarakab population had the highest content of leaf and fruit saponin. The content of leaf and fruit saponin as the major secondary metabolite could be a good determinant for detecting diversity in the wild population of Z. nummularia.

scholarly journals Genetic Diversity and Taxonomic Studies of Allium Akaka and A. Elburzense Native to Iran Using Morphological Characters

2017 ◽  
Vol 25 (1) ◽  
pp. 99-115 ◽  
Author(s):  
Sajad Jafari ◽  
Mohammad Reza Hassandokht ◽  
Mahdi Taheri ◽  
Abdolkarim Kashi
Keyword(s):  
Principal Component ◽  
Morphological Diversity ◽  
Hierarchical Cluster ◽  
Dry Weight ◽  
Morphological Characters ◽  
Leaf Length ◽  
Seed Length ◽  
Allium Species ◽  
Fresh Vegetables ◽  
Wild Accessions

AbstractTwo Allium species (A. akaka S.G. Gmelin and A. elburzense W.) native to Iran are used locally as the fresh vegetables and in medical therapy. They are not cultivated, but are collected from the wild, thus, will soon be threatened with extinction. In this study, the diversity of 15 wild accessions (4 accessions of A. elburzense endemic of Iran and 11 accessions of A. akaka) collected from the north-western part of Iran were evaluated with the use of 16 qualitative and 16 quantitative characteristics. The morphological characters with high heritability included leaf length, flower number in umbel, inflorescence diameter, leaf dry weight, bulb fresh weight, weight of 100 seeds, seed length and seed length/width. Results of the principal component analysis indicated that 92.52% of the observed variability was explained by the first six components. The first two components explained about 64.74% of the total observed variability. The first and third hierarchical cluster analysis included all accessions of A. akaka. The accessions of A. elburzense, except one, were placed in a separate cluster. These morphological descriptors can successfully apply for evaluating morphological diversity of Allium wild accessions and can help in horticultural usage.

scholarly journals Morphological variation of wild peppers (Capsicum spp.) from the state of Tabasco, Mexico

2018 ◽  
pp. 115 ◽  
Author(s):  
Julio C. V.-Ventura, Efrain de la Cruz-Lazaro ◽  
Rodolfo Osorio- Osorio ◽  
Pablo Preciado- Rangel
Keyword(s):  
Morphological Variability ◽  
Principal Component ◽  
Morphological Diversity ◽  
Fruit Shape ◽  
Field Trips ◽  
Leaf Length ◽  
The State ◽  
Mean Values ◽  
Capsicum Spp ◽  
Branch Density

The pepper (Capsicum spp.) is one of the most important vegetables in Mexico. The aim of this study was to collect wild peppers and characterize in situ their morphological diversity. From January to November 2015, field trips were made to 54 locations in 15 municipalities in the state of Tabasco, Mexico; 131 collections were obtained in which a total of 23 plant, flower and fruit variables were evaluated. With the mean values of the variables, principal component (PC) and cluster analyses were performed. The first three PCs explained 65.2% of total morphological variability, with the variables fruit length, fruit shape, fruit width, leaf width, leaf length, plant height and branch density providing a greater explanation for the diversity. Cluster analysis grouped the 131 collections into two groups, one formed by the morphotypes 'Amashito', 'Garbanzo' and 'Ojo de cangrejo', with characteristics of C. annuum var. Glabriusculum, and the second group with the morphotype 'Pico de paloma' with characteristics of the species C. frutescens L. It is concluded that the wild peppers of the State of Tabasco have morphological diversity, which must be preserved as a genetic resource of interest.

scholarly journals Genome-wide selection of discriminant SNP markers for breed assignment in indigenous sheep breeds

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Mohammad Hossein Moradi ◽  
Amir Hossein Khaltabadi-Farahani ◽  
Mehdi Khodaei-Motlagh ◽  
Mahdi Kazemi-Bonchenari ◽  
John McEwan
Keyword(s):  
Discriminant Analysis ◽  
Statistical Method ◽  
Principal Component ◽  
Snp Markers ◽  
Sheep Breed ◽  
Stepwise Discriminant Analysis ◽  
Linear Discriminant ◽  
Sheep Breeds ◽  
Indigenous Sheep ◽  
True Population

AbstractThe assignment of an individual to the true population of origin is one of the most important applications of genomic data for practical use in animal breeding. The aim of this study was to develop a statistical method and then, to identify the minimum number of informative SNP markers from high-throughput genotyping data that would be able to trace the true breed of unknown samples in indigenous sheep breeds. The total numbers of 217 animals were genotyped using Illumina OvineSNP50K BeadChip in Zel, Lori-Bakhtiari, Afshari, Moqani, Qezel and a wild-type Iranian sheep breed. After SNP quality check, the principal component analysis (PCA) was used to determine how the animals allocated to the groups using all genotyped markers. The results revealed that the first principal component (PC1) separated out the two domestic and wild sheep breeds, and all domestic breeds were separated from each other for PC2. The genetic distance between different breeds was calculated using FST and Reynold methods and the results showed that the breeds were well differentiated. A statistical method was developed using the stepwise discriminant analysis (SDA) and the linear discriminant analysis (LDA) to reduce the number of SNPs for discriminating 6 different Iranian sheep populations and K-fold cross-validation technique was employed to evaluate the potential of a selected subset of SNPs in assignment success rate. The procedure selected reduced pools of markers into 201 SNPs that were able to exactly discriminate all sheep populations with 100% accuracy. Moreover, a discriminate analysis of principal components (DAPC) developed using 201 linearly independent SNPs revealed that these markers were able to assign all individuals into true breed. Finally, these 201 identified SNPs were successfully used in an independent out-group breed consisting 96 samples of Baluchi sheep breed and the results indicated that these markers are able to correctly allocate all unknown samples to true population of origin. In general, the results of this study indicated that the combined use of the SDA and LDA techniques represents an efficient strategy for selecting a reduced pool of highly discriminant markers.

scholarly journals Morphometric Study of Several Species of the Genus Jatropha Linn. (Euphorbiaceae)

2016 ◽  
Vol 8 (2) ◽  
pp. 211-215
Author(s):  
Opeyemi Saheed KOLAWOLE ◽  
Abdullahi Alanamu ABDULRAHAMAN ◽  
Mahboob Adekilekun JIMOH ◽  
Felix Ayotunde OLADELE
Keyword(s):  
Principal Component ◽  
Leaf Length ◽  
Leaf Width ◽  
Morphometric Study ◽  
Width Ratio ◽  
Fruit Length ◽  
Jatropha Gossypifolia ◽  
Length Width ◽  
Positive Correlations ◽  
And Cluster Analysis

Morphological parameters of several Jatropha species, namely Jatropha curcas L., Jatropha gossypifolia L., Jatropha podagrica Hook., Jatropha integerrima Jacq. and Jatropha multifida L. were subjected to quantitative analysis within the present study. Twelve traits of the leaves, fruits and seeds were analysed: leaf length, leaf width, leaf length/width ratio, petiole length, petiole width, fruit length, fruit width, fruit length/width ratio, seed length, seed width, fruit stalk length and fruit stalk width were subjected to Principal Component Analysis (PCA) and cluster analysis. Highly significant positive correlations have been noted, while negative correlation was observed between leaf width and leaf length/width ratio, fruit width and leaf length/width ratio. Traits such as leaf length, leaf width and leaf length/width ratio contributed significantly along with other traits to discriminate the studied Jatropha species.  J. podagrica and J. integerrima were found to have more similarities, with a stronger coefficient of agglomeration (69.072) than J. curcas and J. podagrica with 315.028 coefficient of agglomeration respectively. The generated dendrogram showed the relationship between the studied Jatropha species, whereas great affinity was noted between J. podagrica and J. multifida as compared with J. gossypifolia and J. integerrima which are distantly related. The closeness observed between J. podagrica and J. multifida is in line with their current sub-generic grouping.

scholarly journals Acoustic detection of a scallop bed from a single-beam echosounder in the St. Lawrence

2005 ◽  
Vol 62 (5) ◽  
pp. 966-983 ◽  
Author(s):  
Estelle Hutin ◽  
Yvan Simard ◽  
Philippe Archambault
Keyword(s):  
Discriminant Analysis ◽  
Acoustic Signal ◽  
Benthic Communities ◽  
Principal Component ◽  
Ground Truth ◽  
Training Data ◽  
Stepwise Discriminant Analysis ◽  
Single Beam ◽  
Before And After ◽  
Iceland Scallop

Abstract Single-beam seabed echoes combined with epi-macrobenthos photographs were used to remotely detect a scallop bed and characterize the specific acoustic signal of Iceland scallop (Chlamys islandica). A dense scallop bed was surveyed in 2002, with a QTC VIEW Series IV acoustic ground-discrimination system (AGDS) connected to a 38 kHz, 7° split-beam SIMRAD EK60 scientific echosounder. In 2003, a 50 kHz, 42° single-beam SUZUKI ES-2025 echosounder was connected to a QTC VIEW Series V AGDS. The QTC VIEW data were analysed with QTC IMPACT following the standard procedures and classified into acoustic classes. Several approaches were tested: unsupervised and supervised survey strategies directed to specific benthic communities. The SIMRAD EK60 seabed volume-backscattering strength (Sv) was submitted to a principal component analysis (PCA), before and after removal of a depth trend, and the scores on the first 10 principal components were classed by a K-means cluster analysis. The same seabed Sv data were submitted to stepwise discriminant analysis whose training data sets were defined with the ground-truth photographs using different groupings: biotope types, community types, and finally scallop-density classes. All the QTC AGDS approaches failed to reveal the scallop bed, community structures, or biotopes. The QTC classifications mimicked the bathymetry with a strong correlation of the acoustic classes with depth. The seabed Sv PCA + K-means approach presented similar depth-dependence, but, the PCA + K-means on the Sv residuals revealed the scallop bed. The discriminant analysis was the best solution for the scallop density with a general classification success rate of 75% and up to 91% for the highest density class. The Sv signature of the scallop bed is presented, and the most discriminant part of the acoustic signal is identified.

scholarly journals Morphological Variation and Discriminating Traits of Kersting’s Groundnut Accessions

2021 ◽  
Author(s):  
Gilles Y. Chodaton ◽  
Eric Etchikinto Agoyi ◽  
Thomas A. Houndété ◽  
Konoutan M. Kafoutchoni ◽  
Hospice S. Sossou ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Quantitative Traits ◽  
Pearson Correlation ◽  
Principal Component ◽  
High Yield ◽  
Grain Legume ◽  
Stepwise Discriminant Analysis ◽  
Limited Information ◽  
Lattice Design ◽  
Kersting’S Groundnut

Abstract Kersting’s groundnut [Macrotyloma geocarpum (Harms) Maréchal & Baudet] (KG) is a nutritious, subterranean grain legume in West and Central Africa. Only limited information is available on the morphological traits that can discriminate accessions; without such information, appropriate breeding strategies cannot be devised. This study aimed to identify discriminating traits and assess the diversity among accessions of Kersting’s groundnut. Eighty-one KG accessions from Benin and Burkina Faso were evaluated based on 29 qualitative and quantitative traits. An experiment was conducted using an Alpha lattice design with three replications. Standardized Shannon-Weaver index (H') and descriptive statistics were calculated for qualitative traits. Pearson correlation coefficients, stepwise discriminant analysis, principal component analysis, cluster analysis and canonical discriminant analysis were conducted. Results showed that accessions varied greatly based on growth habit (H'= 0.68), flower color (H' = 0.50), seed-eye shape (H' = 0.47), and stem pigmentation (H' = 0.41). Eight quantitative traits, viz., seed width, seed thickness, number of branches per plant, petiole length, days to 50% flowering, number of seeds per pod, pod width, and pod length, were found to significantly discriminate the accessions. Accessions were grouped into three clusters based on quantitative traits. Cluster 1 had accessions with late flowering and good vegetative growth, Cluster 2 contained accessions with high germination percentage and Cluster 3 had accessions with high yield performance. Seed length varied greatly among accessions, thus indicating the potential for improving yield via seed size.

scholarly journals A fast and low-cost approach to quality control of alcohol-based hand sanitizer using portable near infrared spectrometer and chemometrics

2021 ◽  
pp. 096703352098731
Author(s):  
Adenilton C da Silva ◽  
Lívia PD Ribeiro ◽  
Ruth MB Vidal ◽  
Wladiana O Matos ◽  
Gisele S Lopes
Keyword(s):  
Quality Control ◽  
Discriminant Analysis ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Chemical Components ◽  
Linear Discriminant ◽  
Hand Sanitizer

The use of alcohol-based hand sanitizers is recommended as one of several strategies to minimize contamination and spread of the COVID-19 disease. Current reports suggest that the virucidal potential of ethanol occurs at concentrations close to 70%. Traditional methods of verifying the ethanol concentration in such products invite potential errors due to the viscosity of chemical components or may be prohibitively expensive to undertake in large demand. Near infrared (NIR) spectroscopy and chemometrics have already been used for the determination of ethanol in other matrices and present an alternative fast and reliable approach to quality control of alcohol-based hand sanitizers. In this study, a portable NIR spectrometer combined with classification chemometric tools, i.e., partial least square discriminant analysis (PLS–DA) and linear discriminant analysis with successive algorithm projection (SPA–LDA) were used to construct models to identify conforming and non-conforming commercial and laboratory synthesized hand sanitizer samples. Principal component analysis (PCA) was applied in an exploratory data study. Three principal components accounted for 99% of data variance and demonstrate clustering of conforming and non-conforming samples. The PLS–DA and SPA–LDA classification models presented 77 and 100% of accuracy in cross/internal validation respectively and 100% of accuracy in the classification of test samples. A total of 43% commercial samples evaluated using the PLS–DA and SPA–LDA presented ethanol content non-conforming for hand sanitizer gel. These results indicate that use of NIR spectroscopy and chemometrics is a promising strategy, yielding a method that is fast, portable, and reliable for discrimination of alcohol-based hand sanitizers with respect to conforming and non-conforming ethanol concentrations.

Identification and Quantification of Metamizole in Traditional Herbal Medicines using Spectroscopy FTIR-ATR combined with Chemometrics

2021 ◽  
pp. 4413-4419
Author(s):  
Dharmastuti Cahya Fatmarahmi ◽  
Ratna Asmah Susidarti ◽  
Respati Tri Swasono ◽  
Abdul Rohman
Keyword(s):  
Discriminant Analysis ◽  
Herbal Medicine ◽  
Ftir Spectroscopy ◽  
Herbal Medicines ◽  
Principal Component ◽  
Attenuated Total Reflection ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Precision Data

The study aims to develop an effective, efficient, and reliable method using Fourier Transform Infrared (FTIR) spectroscopy with Attenuated Total Reflection (ATR) combined with chemometric for identifying the synthetic drug in Indonesian herbal medicine known as Jamu. Jamu powders, Metamizole, and the binary mixture of Jamu and Metamizole were measured using FTIR-ATR at the mid-infrared region (4000-650 cm-1). The obtained spectra profiles were further analyzed by Principal Component Analysis, Partial Least Square Regression, Principal Component Regression, and Discriminant Analysis. Jamu Pegel Linu (JPL), Jamu Encok (JE), Jamu Sakit Pinggang (JSP), Metamizole (M), and adulterated Jamu by Metamizole were discriminated well on PCA score plot. PLSR and PCR showed the accuracy and precision data to quantify JPL, JE, and JSP, and each adulterated by M with R2 value > 0,995 and low value of RMSEC and RMSEP. Discriminant Analysis (DA) was successfully grouping Jamu and Metamizole without any misclassification. A combination of FTIR spectroscopy and chemometrics offered useful tools for detecting Metamizole in traditional herbal medicine.

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