Anatomy and morphology suggest a hybrid origin of Zamia katzeriana (Zamiaceae)

Phytotaxa ◽  
2016 ◽  
Vol 270 (3) ◽  
pp. 161 ◽  
Author(s):  
MIGUEL A. PÉREZ-FARRERA ◽  
ANDREW P. VOVIDES ◽  
CHRISTIAN RUIZ-CASTILLEJOS ◽  
SONIA GALICIA ◽  
ANGÉLICA CIBRIÁN-JARAMILLO ◽  
...  
Keyword(s):  
Principal Component ◽  
Distinct Species ◽  
Hybrid Origin ◽  
Stomatal Index ◽  
Multivariate Statistical ◽  
Southern Mexico ◽  
Histological Techniques ◽  
Significant Difference ◽  
Discriminant Analyses ◽  
Leaflet Anatomy

The validity of Zamia splendens has been debated, mainly as a result of its synonymy under Z. katzeriana. Field explorations have uncovered previously unknown populations, and some do not appear to match the circumscription of Z. katzeriana. Some populations are morphologically more similar to, and often sympatric with, Z. loddigesii. This study aims at clarifying the morphological and anatomical distinction between the three taxa. To study the morphological variation, a total of 88 individuals from four populations were sampled, these spanning the geographical range of the three cycads in southern Mexico. Univariate, principal component and discriminant analyses of 12 vegetative morphological variables were carried out. To study variation in leaflet anatomy, three individuals per population were analysed for nine anatomical variables and their stomatal index. Standard plant histological techniques and bright field light microscopy were used for observations and measurements of leaflet anatomical variables. Both morphological and anatomical variables were analysed by multivariate statistical methods. Principal component and discriminant analyses on both morphological and anatomical variables and the stomatal index have shown a significant difference between the populations (P = <0.0002) with scatter diagram dispersion indicating three distinctive groups, with Z. katzeriana values consistently intermediate between those of Z. splendens and Z. loddigesii. Some individuals of Z. katzeriana have a leaflet morphology and anatomy similar to Z. loddigesii, yet others resemble Z. splendens. The three taxa comprise distinct species and we propose the acceptance of Z. splendens as independent from Z. katzeriana. The intermediate placement of Z. katzeriana in the analyses suggests a hybrid origin with Z. splendens and Z. loddigesii as putative ancestors.

scholarly journals Skull morphometrics of adult male Antartic fur seal, Arctocephalus gazella, and South American fur seal A. australis

2005 ◽  
Vol 95 (3) ◽  
pp. 261-267 ◽  
Author(s):  
Gustavo A. Daneri ◽  
César M. García Esponda ◽  
Luciano J. M. De Santis ◽  
Laura Pla
Keyword(s):  
Adult Male ◽  
Multivariate Analyses ◽  
Principal Component ◽  
Distinct Species ◽  
South American ◽  
Arctocephalus Gazella ◽  
Multivariate Statistical Analyses ◽  
Multivariate Statistical ◽  
Antarctic Fur Seal ◽  
Fur Seal

The skull morphometrics of adult male Antarctic fur seal, Arctocephalus gazella (Peters, 1875) and South American fur seal, A. australis (Zimmermann, 1783) were investigated using a collection of 45 and 38 skulls, respectively. Eighteen measurements were taken for each specimen. Comparative univariate and multivariate statistical analyses included standard statistics, one-way analysis of variance, principal component analysis and discriminant analysis. Individual variation was relatively high for some variables, as expressed by the coefficient of variation. Skulls of A. gazella were larger than those of A. australis for all but two variables: squamosal jugal suture and rostral length. Both species differed significantly as shown by both univariate and multivariate analyses. The discriminant function correctly classified all specimens. The standardized canonical coefficients showed that the variables which most contribute to the differentiation between species were, in decreasing order, the rostral length, palatal length, palatal width at postcanine 5 and braincase width. The present study corroborates that A. gazella and A. australis are phenotipically distinct species.

scholarly journals Optimal Spectral Wavelengths for Discriminating Orchard Species Using Multivariate Statistical Techniques

2019 ◽  
Vol 12 (1) ◽  
pp. 63
Author(s):  
Mozhgan Abbasi ◽  
Jochem Verrelst ◽  
Mohsen Mirzaei ◽  
Safar Marofi ◽  
Hamid Reza Riyahi Bakhtiari
Keyword(s):  
Precision Agriculture ◽  
Tree Species ◽  
Near Infrared ◽  
Principal Component ◽  
Field Measurements ◽  
Hyperspectral Data ◽  
Visible Range ◽  
Species Discrimination ◽  
Multivariate Statistical ◽  
Significant Difference

Sustainable management of orchard fields requires detailed information about the tree types, which is a main component of precision agriculture programs. To this end, hyperspectral imagery can play a major role in orchard tree species mapping. Efficient use of hyperspectral data in combination with field measurements requires the development of optimized band selection strategies to separate tree species. In this study, field spectroscopy (350 to 2500 nm) was performed through scanning 165 spectral leaf samples of dominant orchard tree species (almond, walnut, and grape) in Chaharmahal va Bakhtiyari province, Iran. Two multivariable methods were employed to identify the optimum wavelengths: the first includes three-step approach ANOVA, random forest classifier (RFC) and principal component analysis (PCA), and the second employs partial least squares (PLS). For both methods we determined whether tree species can be spectrally separated using discriminant analysis (DA) and then the optimal wavelengths were identified for this purpose. Results indicate that all species express distinct spectral behaviors at the beginning of the visible range (from 350 to 439 nm), the red edge and the near infrared wavelengths (from 701 to 1405 nm). The ANOVA test was able to reduce primary wavelengths (2151) to 792, which had a significant difference (99% confidence level), then the RFC further reduced the wavelengths to 118. By removing the overlapping wavelengths, the PCA represented five components (99.87% of variance) which extracted optimal wavelengths were: 363, 423, 721, 1064, and 1388 nm. The optimal wavelengths for the species discrimination using the best PLS-DA model (100% accuracy) were at 397, 515, 647, 1386, and 1919 nm.

scholarly journals Avaliação da Qualidade da Água em Microbacias Hidrográficas do Extremo Sul da Bahia, Brasil

2020 ◽  
Vol 13 (5) ◽  
pp. 2447
Author(s):  
Reinaldo Brandi Abreu Bifano ◽  
Catarina Da Rocha Marcolin ◽  
Maria Otávia Silva Crepaldi ◽  
Raquel Viana Quinelato ◽  
Adriana Tiemi Ramos Okumura ◽  
...  
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Urban Areas ◽  
Principal Component ◽  
Water Quality Assessment ◽  
Multivariate Statistical ◽  
Rainy Period ◽  
Physical Chemical ◽  
Significant Difference

Este estudo teve como objetivo avaliar a qualidade da água das microbacias dos rios Jardim e Mutari, situadas no Extremo Sul da Bahia, através da avaliação de parâmetros físicos, químicos, microbiológicos e do uso e ocupação da terra. Para isso foram realizadas quatro coletas, em abril, maio, julho e outubro de 2019, em 8 pontos amostrais, selecionados de acordo com possíveis fontes pontuais e difusas de poluição. Foram analisados os parâmetros temperatura, potencial hidrogeniônico (pH), salinidade, oxigênio dissolvido (OD), demanda bioquímica de oxigênio (DBO), nitrito, nitrato, amônia, nitrogênio total (NT), fósforo total (PT), sólidos dissolvidos totais, coliformes totais e termotolerantes, que foram comparados com o estabelecido pela CONAMA n° 357/2005. Já as análises de uso e ocupação da terra, foram realizadas utilizando o software QGIS. Com os resultados obtidos observou-se que os parâmetros pH, OD, DBO, PT e NT apresentaram valores em desacordo com o permitido pela legislação, principalmente nos pontos próximos às áreas urbanizadas. A análise estatística multivariada PCA, permitiu identificar diferenças na qualidade da água das microbacias no período seco e chuvoso.Já o teste Kruskal-Wallis indicou diferença significativa entre os ambientes analisados. Nossos resultados indicam que é de suma importância a tomada de ações por parte do poder público que visem minimizar os impactos causados pelo uso e ocupação desordenada da terra e atividades agrícolas na qualidade da água dessas bacias hidrográficas. Cabe destacar também a importância de ações voltadas a educação ambiental principalmente da população ribeirinha.  Water Quality Assessment in Hydrographic Watersheds in the Extreme South of Bahia, BrazilA B S T R A C TThis study aimed to evaluate the water quality of the Jardim and Mutari rivers, located in southern Bahia, by means of evaluating physical, chemical and microbiological parameters and land use and occupation. Four campaigns were carried out in April, May, July, and October, 2019, at 8 stations, selected according to possible punctual and diffusive sources of pollution. The water quality results were compared with that established by CONAMA n.º 357/2005and the Water Quality Index (IQA) was calculated from these. For data analysis, Principal Component Analysis (PCA) was also performed and Kruskal-Wallis tests were applied, using the PAST software.The land use and occupation analyses were performed using the QGIS software. We observed that the pH, OD, DBO, PT and NT were in disagreement with those allowed by the legislation, mainly near urban areas. The multivariate statistical analysis PCA, allowed to identify differences in the water quality of the watersheds in the dry and rainy period. The Kruskal-Wallis test indicated a significant difference between the environments analyzed.The supervised classification confirmed the need to recover areas along the riverbed within the analyzed micro-basins.Our results indicate it is crucial that public authorities act to minimize the impacts caused by the disorderly urban occupation and agricultural activities. It is also worth mentioning the importance of actions aimed at environmental education, mainly of the riverside population.Keywords: water quality, physical, chemical and biological parameters, hydrographic basins, rivers. 

Statistical Analsysis to Evaluate Heavy Metal Pollution in the Air Obatained by Moss Technique in Hanoi and its Surrounding Region

2019 ◽  
Vol 29 (3SI) ◽  
pp. 411
Author(s):  
N. H. Quyet ◽  
Le Hong Khiem ◽  
V. D. Quan ◽  
T. T. T. My ◽  
M. V. Frontasieva ◽  
...  
Keyword(s):  
Heavy Metal ◽  
Statistical Analysis ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
Principal Component ◽  
Multivariate Statistical ◽  
Five Factors ◽  
Heavy Metal Elements ◽  
Surrounding Areas ◽  
Potential Pollution

The aim of this paper was the application of statistical analysis including principal component analysis to evaluate heavy metal pollution obtained by moss technique in the air of Ha Noi and its surrounding areas and to evaluate potential pollution sources. The concentrations of 33 heavy metal elements in 27 samples of Barbula Indica moss in the investigated region collected in December of 2016 in the investigated area have been examined using multivariate statistical analysis. Five factors explaining 80% of the total variance were identified and their potential sources have been discussed.

It is better an approximate answer to the right question than the exact answer to the wrong question : the case of the psychometric analysis of the ASQ:SE

2020 ◽  
Author(s):  
Luis Anunciacao ◽  
janet squires ◽  
J. Landeira-Fernandez
Keyword(s):  
Internal Structure ◽  
Statistical Methods ◽  
Principal Component ◽  
Psychological Theory ◽  
Published Data ◽  
Multivariate Statistical ◽  
Exact Answer ◽  
Wide Range ◽  
Ages And Stages Questionnaire ◽  
The Right

One of the main activities in psychometrics is to analyze the internal structure of a test. Multivariate statistical methods, including Exploratory Factor analysis (EFA) and Principal Component Analysis (PCA) are frequently used to do this, but the growth of Network Analysis (NA) places this method as a promising candidate. The results obtained by these methods are of valuable interest, as they not only produce evidence to explore if the test is measuring its intended construct, but also to deal with the substantive theory that motivated the test development. However, these different statistical methods come up with different answers, providing the basis for different analytical and theoretical strategies when one needs to choose a solution. In this study, we took advantage of a large volume of published data (n = 22,331) obtained by the Ages and Stages Questionnaire Social-Emotional (ASQ:SE), and formed a subset of 500 children to present and discuss alternative psychometric solutions to its internal structure, and also to its subjacent theory. The analyses were based on a polychoric matrix, the number of factors to retain followed several well-known rules of thumb, and a wide range of exploratory methods was fitted to the data, including EFA, PCA, and NA. The statistical outcomes were divergent, varying from 1 to 6 domains, allowing a flexible interpretation of the results. We argue that the use of statistical methods in the absence of a well-grounded psychological theory has limited applications, despite its appeal. All data and codes are available at https://osf.io/z6gwv/.

scholarly journals Inhibition of Kynurenine Metabolism and Its Effect in Mitochondrial Function in Hepatocellular Carcinoma

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 124-125
Author(s):  
Raul Castro-Portuguez ◽  
Samuel Freitas ◽  
George Sutphin
Keyword(s):  
Hepatocellular Carcinoma ◽  
Mitochondrial Function ◽  
De Novo ◽  
Principal Component ◽  
Kynurenine Pathway ◽  
The Cancer Genome Atlas ◽  
Wilcoxon Test ◽  
Nad Synthesis ◽  
Significant Difference ◽  
Kynurenine Metabolism

Abstract Hepatocellular carcinoma (HCC) is the most prevalent cancer in the liver. The majority of ingested tryptophan is processed in the liver through the kynurenine pathway, the endpoint of which is de novo NAD+ biosynthesis. Dysregulation of tryptophan-kynurenine metabolism and NAD+ synthesis may promote mitochondrial malfunction, tumor reprogramming, and carcinogenesis. Using a publicly available gene expression dataset from liver hepatocellular carcinoma (LIHC) samples available through The Cancer Genome Atlas (TCGA; n = 371), we employed Principal Component Analysis (PCA), hierarchical clustering, gene-pattern expression profiling, and survival analysis to cluster patients and determine overall survival. Our analysis of genes encoding kynurenine pathway enzymes determined that patients with high QPRT expression had a poor prognosis with decreased median survival, with no effect on the maximum survival. There is a significant difference in the survival between patients with high QPRT expression relative to patients with high HAAO/AFMID expression (HR = 1.2, [95% CI 0.5-1.8] P = 0.0181, Gehan-Breslow-Wilcoxon Test). Patients with high QPRT expression have higher survival rates compared with low QPRT expression (HR = 1.4, [95% CI 0.9-2.2] P = 0.0344, Gehan-Breslow-Wilcoxon Test). To test the consequences of kynurenine-pathway inhibition in mitochondrial function and morphology we use 4-Cl-3HAA, an irreversible HAAO inhibitor, and observed a small increase in mitochondrial fragmentation in HepG2 cells after 24 hours of treatment. We conclude that kynurenine metabolism may be useful as a biomarker to predict patient prognosis among HCC patients. In ongoing work, we are testing QPRT inhibitors in cell culture as a potential adjuvant for chemotherapies.

scholarly journals Characterization of the Volatile Profile of Cultivated and Wild-Type Italian Celery (Apium graveolens L.) Varieties by HS-SPME/GC-MS

2021 ◽  
Vol 11 (13) ◽  
pp. 5855
Author(s):  
Samantha Reale ◽  
Valter Di Cecco ◽  
Francesca Di Donato ◽  
Luciano Di Martino ◽  
Aurelio Manzi ◽  
...  
Keyword(s):  
Solid Phase ◽  
Principal Component ◽  
Apium Graveolens ◽  
Gas Chromatography Mass Spectrometry ◽  
Bioactive Metabolites ◽  
Chemical Components ◽  
Volatile Profile ◽  
Wild Type ◽  
Multivariate Statistical ◽  
Clear Differentiation

Celery (Apium graveolens L.) is a vegetable belonging to the Apiaceae family that is widely used for its distinct flavor and contains a variety of bioactive metabolites with healthy properties. Some celery ecotypes cultivated in specific territories of Italy have recently attracted the attention of consumers and scientists because of their peculiar sensorial and nutritional properties. In this work, the volatile profiles of white celery “Sedano Bianco di Sperlonga” Protected Geographical Indication (PGI) ecotype, black celery “Sedano Nero di Torricella Peligna” and wild-type celery were investigated using head-space solid-phase microextraction combined with gas-chromatography/mass spectrometry (HS-SPME/GC-MS) and compared to that of the common ribbed celery. Exploratory multivariate statistical analyses were conducted using principal component analysis (PCA) on HS-SPME/GC-MS patterns, separately collected from celery leaves and petioles, to assess similarity/dissimilarity in the flavor composition of the investigated varieties. PCA revealed a clear differentiation of wild-type celery from the cultivated varieties. Among the cultivated varieties, black celery “Sedano Nero di Torricella Peligna” exhibited a significantly different composition in volatile profile in both leaves and petioles compared to the white celery and the prevalent commercial variety. The chemical components of aroma, potentially useful for the classification of celery according to the variety/origin, were identified.

scholarly journals Chemical Fingerprinting of Cryptic Species and Genetic Lineages of Aneura pinguis (L.) Dumort. (Marchantiophyta, Metzgeriidae)

Molecules ◽  
2021 ◽  
Vol 26 (4) ◽  
pp. 1180
Author(s):  
Rafał Wawrzyniak ◽  
Wiesław Wasiak ◽  
Beata Jasiewicz ◽  
Alina Bączkiewicz ◽  
Katarzyna Buczkowska
Keyword(s):  
Cluster Analysis ◽  
Cryptic Species ◽  
Plant Material ◽  
Chemical Constituents ◽  
Principal Component ◽  
Molecular Data ◽  
Rapid Identification ◽  
Multivariate Statistical ◽  
Genetic Lineages ◽  
Marker Compounds

Aneura pinguis (L.) Dumort. is a representative of the simple thalloid liverworts, one of the three main types of liverwort gametophytes. According to classical taxonomy, A. pinguis represents one morphologically variable species; however, genetic data reveal that this species is a complex consisting of 10 cryptic species (named by letters from A to J), of which four are further subdivided into two or three evolutionary lineages. The objective of this work was to develop an efficient method for the characterisation of plant material using marker compounds. The volatile chemical constituents of cryptic species within the liverwort A. pinguis were analysed by GC-MS. The compounds were isolated from plant material using the HS-SPME technique. Of the 66 compounds examined, 40 were identified. Of these 40 compounds, nine were selected for use as marker compounds of individual cryptic species of A. pinguis. A guide was then developed that clarified how these markers could be used for the rapid identification of the genetic lineages of A. pinguis. Multivariate statistical analyses (principal component and cluster analysis) revealed that the chemical compounds in A. pinguis made it possible to distinguish individual cryptic species (including genetic lineages), with the exception of cryptic species G and H. The classification of samples based on the volatile compounds by cluster analysis reflected phylogenetic relationships between cryptic species and genetic lineages of A. pinguis revealed based on molecular data.

scholarly journals Multivariate Analysis as a Tool for Quantification of Conformational Transitions in DNA Thin Films

2021 ◽  
Vol 11 (13) ◽  
pp. 5895
Author(s):  
Kristina Serec ◽  
Sanja Dolanski Babić
Keyword(s):  
Thin Films ◽  
Learning Algorithm ◽  
Principal Component Regression ◽  
Principal Component ◽  
Conformational Transitions ◽  
Cancer Diagnostics ◽  
Dna Conformation ◽  
Support Vector ◽  
Multivariate Statistical ◽  
The Impact

The double-stranded B-form and A-form have long been considered the two most important native forms of DNA, each with its own distinct biological roles and hence the focus of many areas of study, from cellular functions to cancer diagnostics and drug treatment. Due to the heterogeneity and sensitivity of the secondary structure of DNA, there is a need for tools capable of a rapid and reliable quantification of DNA conformation in diverse environments. In this work, the second paper in the series that addresses conformational transitions in DNA thin films utilizing FTIR spectroscopy, we exploit popular chemometric methods: the principal component analysis (PCA), support vector machine (SVM) learning algorithm, and principal component regression (PCR), in order to quantify and categorize DNA conformation in thin films of different hydrated states. By complementing FTIR technique with multivariate statistical methods, we demonstrate the ability of our sample preparation and automated spectral analysis protocol to rapidly and efficiently determine conformation in DNA thin films based on the vibrational signatures in the 1800–935 cm−1 range. Furthermore, we assess the impact of small hydration-related changes in FTIR spectra on automated DNA conformation detection and how to avoid discrepancies by careful sampling.

scholarly journals STATISTICAL MULTIVARIATE ANALYSIS APPLIED TO ENVIRONMENTAL CHARACTERIZATION OF SOIL IN SEMIARID REGION1

2019 ◽  
Vol 32 (1) ◽  
pp. 200-210
Author(s):  
Antônio Italcy de Oliveira Júnior ◽  
Luiz Alberto Ribeiro Mendonça ◽  
Sávio de Brito Fontenele ◽  
Adriana Oliveira Araújo ◽  
Maria Gorethe de Sousa Lima Brito
Keyword(s):  
Organic Matter Content ◽  
Principal Component ◽  
Matter Content ◽  
Multivariate Statistical ◽  
Statistical Tool ◽  
Environmental Characterization ◽  
Hierarchical Grouping ◽  
Two Factors ◽  
Total Data

ABSTRACT Soil is a dynamic and complex system that requires a considerable number of samples for analysis and research purposes. Using multivariate statistical methods, favorable conditions can be created by analyzing the samples, i.e., structural reduction and simplification of the data. The objective of this study was to use multivariate statistical analysis, including factorial analysis (FA) and hierarchical groupings, for the environmental characterization of soils in semiarid regions, considering anthropic (land use and occupation) and topographic aspects (altitude, moisture, granulometry, PR, and organic-matter content). As a case study, the São José Hydrographic Microbasin, which is located in the Cariri region of Ceará, was considered. An FA was performed using the principal component method, with normalized varimax rotation. In hierarchical grouping analysis, the “farthest neighbor” method was used as the hierarchical criterion for grouping, with the measure of dissimilarity given by the “square Euclidean distance.” The FA indicated that two factors explain 75.76% of the total data variance. In the analysis of hierarchical groupings, the samples were agglomerated in three groups with similar characteristics: one with samples collected in an area of the preserved forest and two with samples collected in areas with more anthropized soils. This indicates that the statistical tool used showed sensitivity to distinguish the most conserved soils and soils with different levels of anthropization.

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