CHEMOMETRIC QUANTITATIVE ANALYSIS OF PYRIDOXINE HCl AND THIAMINE HCl IN A VITAMIN COMBINATION BY PRINCIPAL COMPONENT ANALYSIS, CLASSICAL LEAST SQUARES, AND INVERSE LEAST SQUARES TECHNIQUES

2001 ◽  
Vol 34 (3) ◽  
pp. 279-288 ◽  
Author(s):  
Erdal Dinç ◽  
Dumitru Băleanu ◽  
Feyyaz Onur
Keyword(s):  
Principal Component Analysis ◽  
Quantitative Analysis ◽  
Least Squares ◽  
Principal Component ◽  
Component Analysis ◽  
Least Squares Techniques

scholarly journals Multivariate statistical analysis of tropane alkaloids in Anisodus tanguticus (Maxim.) Pascher from different regions to trace geographical origins

2021 ◽  
Author(s):  
Chen Chen ◽  
Jingjing Li ◽  
Feng Xiong ◽  
Bo Wang ◽  
Yuanming Xiao ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Quantitative Analysis ◽  
Discriminant Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Geographical Origin ◽  
Principal Component ◽  
Tropane Alkaloids ◽  
Component Analysis ◽  
Tibet Plateau

Abstract Anisodus tanguticus (Maxim.) Pascher is an important Tibetan folk medicine and the source of tropane alkaloids (TAs) grown in Qinghai-Tibet Plateau. There are marked differences in quality of A. tanguticus from geographic areas. The aim of present research was to establish a method for the quantitative analysis of TAs coupled with chemometrics analysis to trace geographical origins. Qualitative analysis of TAs in A. tanguticus was carried out using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry and quantitative analysis of TAs in different plant organs from different geographical origin was achieved. Contents of TAs were subjected to the principal component analysis, and orthogonal partial least-squares discriminant analysis. The contents of the three marker compounds (anisodamine, anisodine and atropine) in the roots and acrial parts of A. tanguticus were positive correlated and varied significantly from different geographical origins. Principal component analysis, and orthogonal partial least-squares discriminant analysis results showed excellent discrimination between different geographical origin of A. tanguticus. This study could provide comprehensive evaluation and further utilization of A. tanguticus resources.

Quantitative analysis of interspecific and ontogenetic variation in Osteoglossum species (Teleostei: Osteoglossiformes: Osteoglossidae)

Zootaxa ◽  
2006 ◽  
Vol 1239 (1) ◽  
pp. 49 ◽  
Author(s):  
MARIA E.C. LEAL ◽  
VIVIANNE B. DE SANT-ANNA
Keyword(s):  
Principal Component Analysis ◽  
Quantitative Analysis ◽  
Intraspecific Variation ◽  
Principal Component ◽  
Component Analysis ◽  
Growth Trajectories ◽  
Ontogenetic Variation ◽  
Morphometric Characters ◽  
Interspecific And Intraspecific Variation

Patterns of interspecific and intraspecific variation were investigated on samples of postembryos, juveniles, and adults of the two species of the osteoglossid genus Osteoglossum (O. bicirrhosum and O. ferreirai). Twenty-two morphometric characters were analyzed, utilizing principal component analysis (PCA) that discriminate ontogenetic classes and between species. The results showed differences in both categories. Morphometric characters related to dorsal and anal fin lengths proved to be the most important in taxonomic recognition. The comparison of growth trajectories for these characters showed that growth offset for O. bicirrhosum overlaps with growth onset for O. ferreirai, which may be indicative of a peramorphic morphology in the latter species.

scholarly journals Modelos PCA a partir de conjuntos de datos con información faltante. ¿Se afectan sus propiedades?

SaberEs ◽  
2010 ◽  
Author(s):  
María Susana Vitelleschi ◽  
Directora: Marta Beatriz Quaglino
Keyword(s):  
Principal Component Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Expectation Maximization ◽  
Principal Component ◽  
Component Analysis

En este trabajo se aborda la problemática de la construcción de modelos PCA (Principal Component Analysis) a partir de conjuntos de datos con información faltante. Se trabaja sobre tres situaciones diferentes con relación a la matriz de datos originales. En cada situación se generaron pérdidas a través de mecanismos aleatorios y no aleatorios, en diferentes porcentajes en una sola variable por vez, seleccionada mediante dos criterios: la que más contribuye y menos contribuye en la formación de la primera componente principal. A partir de cada conjunto de datos incompletos se construye el modelo PCA utilizando: Casos Completos, Nonlinear Iterative Partial Least Squares (NIPALS) y Expectation Maximization (EM). Se comparan los resultados con los obtenidos a través del conjunto de datos originales. Se definen una serie de medidas para estudiar cómo se afectan los resultados según la dimensión de la matriz de datos, el porcentaje y el mecanismo de pérdida, con relación a: bondad del ajuste, bondad de predicción, vectores cargas, ortonormalidad de la matriz de cargas y ortogonalidad de la matriz de “scores”.

Comparison and Discrimination of Artemisia argyi and Artemisia lavandulifolia by Gas Chromatography-Mass Spectrometry-Based Metabolomic Approach

2019 ◽  
Vol 102 (6) ◽  
pp. 1814-1821 ◽  
Author(s):  
Long Guo ◽  
Dan Zhang ◽  
Lei Wang ◽  
Zijing Xue ◽  
Mei Guo ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Least Squares ◽  
Volatile Compounds ◽  
Partial Least Squares ◽  
Herbal Medicines ◽  
Principal Component ◽  
Component Analysis ◽  
Chemical Markers ◽  
Artemisia Argyi ◽  
Metabolomic Approach

Abstract Background: Artemisia argyi and A. lavandulifolia are two morphologically similar herbal medicines derived from the Artemisia genus. Although the two Artemisia herbs have been used as herbal medicines for a long time, studies on their phytochemicals and bioactive compositions are still limited, and no research has been devoted to compare the volatile compounds in A. argyi and A. lavandulifolia. Objective: To compare the volatile constituents in A. argyi and A. lavandulifolia and to explore chemical markers for discrimination and quality evaluation of the two Artemisia herbal medicines. Methods: A GC-MS-based metabolomic approach was employed to compare and discriminate A. argyi and A. lavandulifolia from the aspect of volatile compounds. Multivariate statistical methods, including principal component analysis and orthogonal partial least-squares discriminate analysis, were applied to explore chemical markers for discrimination of the two Artemisia herbal medicines. Results: Thirty volatile compounds were identified, and the chemical profiles of volatile compounds in A. argyi and A. lavandulifolia were quite similar. Principal component analysis and orthogonal partial least-squares discrimination analysis results indicated that the two Artemisia herbal medicines could be distinguished effectively from each other. Ten volatile compounds were selected as potential chemical markers for discrimination of the two Artemisia herbal medicines. Conclusions: The GC-MS-based metabolomics could be an acceptable strategy for comparison and discrimination of A. argyi and A. lavandulifolia as well as authentication of herbal medicines derived from other closely related species. Highlights: GC-MS based metabolomic approach was firstly applied to compare and discriminate Artemisia argyi and Artemisia lavandulifolia.

scholarly journals Analysis of the procedures used in the forensic evaluation of illegal substances: a statistical approach to interpreting reports

2019 ◽  
Vol 8 (1) ◽  
pp. 7-23
Author(s):  
Aline Thaís Bruni ◽  
Ricardo Luís Yoshida ◽  
Arthur Serra Lopes Ferreira ◽  
Jesus Antonio Velho ◽  
Bruno Spinosa De Martinis ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Hierarchical Cluster Analysis ◽  
Labor Demand ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Component Analysis ◽  
Final Report

ResumoEste estudo utilizou ferramentas estatísticas para avaliar laudos forenses sobre substâncias ilegais. Avaliamos variáveis quanto às características da análise e abordamos a metodologia empregada pelos peritos. Perguntas baseadas no que é necessário para esclarecer a lei foram formuladas. Analisamos 1008 documentos oficiais de diferentes jurisdições, divididos em 504 conjuntos compostos por um laudo preliminar e um laudo definitivo para cada caso. Os laudos foram examinados por uma equação empírica formulada para fornecer um parâmetro denominado “Report Relevance” (Relevância do Laudo), que teve por finalidade classificar cada documento de acordo com uma pontuação relacionada à quantidade de informação contida. A validação do método foi realizada por análise multivariada de dados: Análise de Componentes Principais (Principal Component Analysis, PCA), Análise de Agrupamentos Hierárquicos (Hierarchical Cluster Analysis, HCA), Soft Independent Modeling of Class Analogy (SIMCA) e Mínimos Quadrados Parciais (Partial Least Squares, PLS). A análise quantitativa mostrou que os documentos foram bem produzidos, com boa qualidade, uma vez que a Relevância do Laudo apresentou valores em torno de 0,74 ± 0,08 para aqueles provenientes da Polícia Estadual. Em comparação, os documentos provenientes da Polícia Federal obtiveram valores em torno de 0,87 ± 0,05. Fatores que podem explicar essas diferenças e as melhores pontuações para os laudos federais incluem maior investimento em tecnologia e treinamento de pessoal, e menor demanda de mão-de-obra e rotina. Para ambas as forças policiais, alguns aspectos poderiam ser melhorados, como imagens das evidências coletadas ou procedimentos analíticos laboratoriais. Finalmente, a metodologia neste estudo pode ser adaptada para ser usada em outros tipos de investigação forense.Palavras-chave: Substâncias Ilícitas, Procedimentos Periciais, Análise MultivariadaAbstractThis study used statistical tools to evaluate forensic reports on illegal substances. We evaluated variables regarding the characteristics of the analysis and we addressed the methodology employed by the experts. Questions based on what is required to clarify the law were formulated. We have parsed 1008 official documents from different jurisdictions, divided into 504 sets comprised of a preliminary and a final report for each case. The reports were examined by an empirical equation formulated to provide a parameter called “Report Relevance”, which intended to classify each report according to a score related to the amount of information it contained.  The validation of the method was performed by multivariate data analysis: Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), Soft Independent Modeling of Class Analogy (SIMCA) and Partial Least Squares (PLS). Quantitative analysis showed that the expert documents were well produced, with good quality, since the Report Relevance showed values around 0.74 ± 0.08 for the reports from the State Police. By comparison, reports from the Federal Police obtained scores around 0.87 ± 0.05. Factors that might explain these differences and the better scores for the Federal reports include increased investment in technology and training of staff, and a lower labor demand and routine. For both police forces, some aspects could be improved, such as images of the collected evidence or laboratory analytical procedures. Finally, the methodology in this study can be adapted to be used in other kinds of forensic investigation.Keywords: Illegal Substances, Expertise Procedures, Multivariate Analysis.  

Sign in / Sign up

Export Citation Format

Share Document