Evaluation via multivariate techniques of scale factor variability in the rietveld method applied to quantitative phase analysis with X ray powder diffraction

ABSTRACT: The present work uses multivariate statistical analysis as a form of establishing the main sources of error in the Quantitative Phase Analysis (QPA) using the Rietveld method. The quantitative determination of crystalline phases using x ray powder diffraction is a complex measurement process whose results are influenced by several factors. Ternary mixtures of Al2O3, MgO and NiO were prepared under controlled conditions and the diffractions were obtained using the Bragg-Brentano geometric arrangement. It was possible to establish four sources of critical variations: the experimental absorption and the scale factor of NiO, which is the phase with the greatest linear absorption coefficient of the ternary mixture; the instrumental characteristics represented by mechanical errors of the goniometer and sample displacement; the other two phases (Al2O3 and MgO); and the temperature and relative humidity of the air in the laboratory. The error sources excessively impair the QPA with the Rietveld method. Therefore it becomes necessary to control them during the measurement procedure.

Aplicação de tratamento estatístico multivariante em dados de perfis de poços da Bacia de Sergipe-Alagoas

Utilizando-se dados do campo de Camorim (Bacia de Sergipe-Alagoas), foi testado e aplicado um conjunto de técnicas estatísticas multivariantes (análises de agrupamentos, de componentes principais e discriminante) no intuito de identificar as fácies, previamente definidas em poços testemunhados, por meio dos perfis, viabilizando o reconhecimento das mesmas nos demais poços não testemunhados da área. A segunda etapa do processo de determinação das fácies consistiu no emprego de métodos auxiliares (análises composicional e de seqüência de fácies), que, combinados com as técnicas multivariantes, propiciaram melhores resultados na calibração rocha-perfil. A determinação das fácies, uma vez estabelecida, possibilitou o refinamento do processo de avaliação de formações ao viabilizar o exame de cada fácies-reservatório, isoladamente. Assim, esse procedimento tornou possível a escolha, para cada litologia, dos parâmetros utilizados na interpretação dos perfis ao mesmo tempo em que permitiu a totalização em separado dos valores de espessura, porosidade e saturação dos fluidos, bem como a adoção de diferentes valores de corte (cut-offs) para cada grupo considerado. Outras aplicações incluíram a melhoria na estimativa da porosidade e da permeabilidade, a adaptação de algoritmos para o cálculo preliminar de porosidade, a confecção de mapas de fácies e a geração automática de seções estratigráficas. Finalmente, foram destacadas a perspectiva de integração desse estudo com sistemas estatísticos de descrição de reservatórios, outras técnicas de determinação de fácies em desenvolvimento e a retomada da utilização de métodos estatísticos multivariantes em dados de perfis, como ferramenta de exploração.

Discrimination of soybean seed lots by multivariate exploratory techniques

Physiological potential characterization of seed lots is usually performed by germination and vigor tests; however, the choice of a single test does not reflect such potential, once each test assesses seeds of differentiated mode. Multivariate techniques allow understanding structural dependence contained in each variable, as well as characterize groups of seed lots according to specific standards. The study aimed at evaluating variability among soybean seed lots and discriminate these lots by multivariate exploratory techniques as function of seed vigor. Experiment was performed with 20 soybean seed lots (10 lots cv. BRS Valiosa RR and 10 lots cv. M-SOY 7908 RR). Seed physiological potential was assessed by testing for: germination (standard, and under different water availability); vigor (accelerated aging and electrical conductivity); and field seedling emergence. Cluster analysis of seed lots, as well as Principal Component Analysis was performed using data obtained on all tests. Multivariate techniques allowed stratifying seed lots into two distinct groups. Principal Component Analysis showed that values obtained for variables: field seedling emergence, accelerated aging, and germination under different water availability were linked to BRS Valiosa RR; while to variables germination and electrical conductivity, were linked to M-SOY 7908 RR.

Multivariate approach in the selection of superior soybean progeny which carry the RR gene

Efficiency in the use of genetic variability, whether existing or created, increases when properly explored and analysed. Incorporation of biotechnology into breeding programs has been the general practice. The challenge for the researcher is the constant development of new and improved cultivars. The aim of this experiment was to select progenies with superior characteristics, whether or not carriers of the RR gene, derived from bi-parental crosses in the soybean, with the help of multivariate techniques. The experiment was carried out in a family-type experimental design, including controls, during the agricultural year 2010/2011 and 2011/2012 in Jaboticabal in the Brazilian State of São Paulo. From the F3 generation, phenotypically superior plants were selected, which were evaluated for the following traits: number of days to flowering; number of days to maturity; height of first pod insertion; plant height at maturity; lodging; agronomic value; number of branches; number of pods per plant; 100-seed weight; number of seeds per plant; grain yield per plant. Given the results, it appears possible to select superior progeny by principal component analysis. Cluster analysis using the K-means method links progeny according to the most important characteristics in each group and identifies, by the Ward method and by means of a dendrogram, the structure of similarity and divergence between selected progeny. Both methods are effective in aiding progeny selection.

Abordagem multivariada, perfil composicional e construção de curva de calibração para predição do teor de óleo em Jatropha curcas L

Pós-graduação em Agronomia (Genética e Melhoramento de Plantas) - FCAV

Multivariate curve resolution analysis applied to time-resolved synchrotron X-ray Absorption Spectroscopy monitoring of the activation of copper alumina catalyst

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Comprehensive two-dimensional gas chromatography combined to multivariate data analysis for detection of disease-resistant clones of Eucalyptus

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A tool for controlling accelerometers. Secondary calibration data

Vibration monitoring requires acceleration transducers capable of providing data with high precision. Accelerometers are the most frequently used vibration transducers. Their calibration plays an important role in measuring vibrations and is a key component in ensuring the integrity of the vibration measurement. For managing secondary calibration data of accelerometers, a database computer system was implemented. The implementation of this software has been an important step forward in providing a wide range of analysis and display tools. This paper reviews the main concepts involving accelerometer secondary calibration and describes the tool developed and the methods used in its development. (C) 2013 Academie des sciences. Published by Elsevier Masson SAS. All rights reserved.

Multivariate analysis of the temporal variability of sugarcane ripening in south-eastern Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Why is it so difficult to identify a single indicator of water stress in plants? A proposal for a multivariate analysis to assess emergent properties

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multivariate Development and Validation of a Stability-Indicating HPLC Method for the Determination of Glimepiride in Tablets

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Filtros UV na água de abastecimento público na região da bacia hidrográfica tietê-jacaré: desenvolvimento de método, estudo de ocorrência e concentrações ambientais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Eletrodos impressos descartáveis e de carbono vítreo modificados com grafeno e compósito de nanotubos de carbono-quitosana aplicados na determinação de corantes de cabelo

Pós-graduação em Química - IQ

Fast determination of beef quality parameters with time-domain nuclear magnetic resonance spectroscopy and chemometrics

The noteworthy of this study is to predict seven quality parameters for beef samples using time-domain nuclear magnetic resonance (TD-NMR) relaxometry data and multivariate models. Samples from 61 Bonsmara heifers were separated into five groups based on genetic (breeding composition) and feed system (grain and grass feed). Seven sample parameters were analyzed by reference methods; among them, three sensorial parameters, flavor, juiciness and tenderness and four physicochemical parameters, cooking loss, fat and moisture content and instrumental tenderness using Warner Bratzler shear force (WBSF). The raw beef samples of the same animals were analyzed by TD-NMR relaxometry using Carr-Purcell-Meiboom-Gill (CPMG) and Continuous Wave-Free Precession (CWFP) sequences. Regression models computed by partial least squares (PLS) chemometric technique using CPMG and CWFP data and the results of the classical analysis were constructed. The results allowed for the prediction of aforementioned seven properties. The predictive ability of the method was evaluated using the root mean square error (RMSE) for the calibration (RMSEC) and validation (RMSEP) data sets. The reference and predicted values showed no significant differences at a 95% confidence level.

Multivariate analysis for animal selection in experimental research

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)