998 resultados para Vitis, análise multivariada
Resumo:
The routine analysis for quantization of organic acids and sugars are generally slow methods that involve the use and preparation of several reagents, require trained professional, the availability of special equipment and is expensive. In this context, it has been increasing investment in research whose purpose is the development of substitutive methods to reference, which are faster, cheap and simple, and infrared spectroscopy have been highlighted in this regard. The present study developed multivariate calibration models for the simultaneous and quantitative determination of ascorbic acid, citric, malic and tartaric and sugars sucrose, glucose and fructose, and soluble solids in juices and fruit nectars and classification models for ACP. We used methods of spectroscopy in the near infrared (Near Infrared, NIR) in association with the method regression of partial least squares (PLS). Were used 42 samples between juices and fruit nectars commercially available in local shops. For the construction of the models were performed with reference analysis using high-performance liquid chromatography (HPLC) and refractometry for the analysis of soluble solids. Subsequently, the acquisition of the spectra was done in triplicate, in the spectral range 12500 to 4000 cm-1. The best models were applied to the quantification of analytes in study on natural juices and juice samples produced in the Paraná Southwest Region. The juices used in the application of the models also underwent physical and chemical analysis. Validation of chromatographic methodology has shown satisfactory results, since the external calibration curve obtained R-square value (R2) above 0.98 and coefficient of variation (%CV) for intermediate precision and repeatability below 8.83%. Through the Principal Component Analysis (PCA) was possible to separate samples of juices into two major groups, grape and apple and tangerine and orange, while for nectars groups separated guava and grape, and pineapple and apple. Different validation methods, and pre-processes that were used separately and in combination, were obtained with multivariate calibration models with average forecast square error (RMSEP) and cross validation (RMSECV) errors below 1.33 and 1.53 g.100 mL-1, respectively and R2 above 0.771, except for malic acid. The physicochemical analysis enabled the characterization of drinks, including the pH working range (variation of 2.83 to 5.79) and acidity within the parameters Regulation for each flavor. Regression models have demonstrated the possibility of determining both ascorbic acids, citric, malic and tartaric with successfully, besides sucrose, glucose and fructose by means of only a spectrum, suggesting that the models are economically viable for quality control and product standardization in the fruit juice and nectars processing industry.
Quantificação de açúcares com uma língua eletrónica: calibração multivariada com seleção de sensores
Resumo:
Este trabalho incide na análise dos açúcares majoritários nos alimentos (glucose, frutose e sacarose) com uma língua eletrónica potenciométrica através de calibração multivariada com seleção de sensores. A análise destes compostos permite contribuir para a avaliação do impacto dos açúcares na saúde e seu efeito fisiológico, além de permitir relacionar atributos sensoriais e atuar no controlo de qualidade e autenticidade dos alimentos. Embora existam diversas metodologias analíticas usadas rotineiramente na identificação e quantificação dos açúcares nos alimentos, em geral, estes métodos apresentam diversas desvantagens, tais como lentidão das análises, consumo elevado de reagentes químicos e necessidade de pré-tratamentos destrutivos das amostras. Por isso se decidiu aplicar uma língua eletrónica potenciométrica, construída com sensores poliméricos selecionados considerando as sensibilidades aos açucares obtidas em trabalhos anteriores, na análise dos açúcares nos alimentos, visando estabelecer uma metodologia analítica e procedimentos matemáticos para quantificação destes compostos. Para este propósito foram realizadas análises em soluções padrão de misturas ternárias dos açúcares em diferentes níveis de concentração e em soluções de dissoluções de amostras de mel, que foram previamente analisadas em HPLC para se determinar as concentrações de referência dos açúcares. Foi então feita uma análise exploratória dos dados visando-se remover sensores ou observações discordantes através da realização de uma análise de componentes principais. Em seguida, foram construídos modelos de regressão linear múltipla com seleção de variáveis usando o algoritmo stepwise e foi verificado que embora fosse possível estabelecer uma boa relação entre as respostas dos sensores e as concentrações dos açúcares, os modelos não apresentavam desempenho de previsão satisfatório em dados de grupo de teste. Dessa forma, visando contornar este problema, novas abordagens foram testadas através da construção e otimização dos parâmetros de um algoritmo genético para seleção de variáveis que pudesse ser aplicado às diversas ferramentas de regressão, entre elas a regressão pelo método dos mínimos quadrados parciais. Foram obtidos bons resultados de previsão para os modelos obtidos com o método dos mínimos quadrados parciais aliado ao algoritmo genético, tanto para as soluções padrão quanto para as soluções de mel, com R²ajustado acima de 0,99 e RMSE inferior a 0,5 obtidos da relação linear entre os valores previstos e experimentais usando dados dos grupos de teste. O sistema de multi-sensores construído se mostrou uma ferramenta adequada para a análise dos iii açúcares, quando presentes em concentrações maioritárias, e alternativa a métodos instrumentais de referência, como o HPLC, por reduzir o tempo da análise e o valor monetário da análise, bem como, ter um preparo mínimo das amostras e eliminar produtos finais poluentes.
Resumo:
Neste trabalho apresentamos a teoria da análise de correlação canónica, uma técnica de análise estatística multivariada para o estudo da relação, simultânea, entre dois, três ou mais grupos de variáveis. Descrevemos a natureza da correlação canónica com três ou mais variáveis, com modelos matemáticos, fazendo uma síntese dos métodos de generalização de correlação canónica nomeadamente o método Ssqcor, método Sumcor, método Ecart, método Maxvar, método Minvar, e o método de Carroll. Apresentamos uma aplicação utilizando dados provenientes do cálculo do Índice de Preços no Consumidor IPC, produzido pelo INE - STP (Instituto Nacional de Estatística de São Tomé e Príncipe), referente ao período 2010 a 2014. Estamos interessados em conhecer as correlações canónicas entre grupos de variáveis relacionadas com o cabaz de produtos pré-estabelecido para o cálculo do índice de preços no consumidor, concretamente os produtos alimentares (PA), produtos para bebidas (PB) e produtos não alimentares (PNA), constituindo assim os três grandes grupos de variáveis da nossa pesquisa.
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Tese (doutorado)—Universidade de Brasília, Faculdade de Economia, Administração e Contabilidade, Programa de Pós-Graduação em Administração, 2016.
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Uma importante propriedade dos Organossolos, e de outros solos com alto teor de C orgânico para predizer o potencial de uso e riscos de degradação, é o grau de subsidência (perda de massa e volume). Nos Organossolos ocorrem diferentes riscos de subsidência, resultantes de seus atributos, em especial da natureza da matéria orgânica e do ambiente de deposição. Este estudo foi realizado com dados de 19 perfis de solos de diferentes regiões do Brasil. Foram adotados os procedimentos da SBCS para descrição e coleta dos perfis, e os métodos analíticos da Embrapa Solos para caracterização dos solos. A análise dos componentes principais foi utilizada para agrupar os perfis com o auxílio de atributos morfológicos, físicos, químicos e do ambiente de ocorrência e mostrou-se adequada no agrupamento dos solos estudados com base em seus atributos, comparando-se com a sua taxonomia. Neste artigo foram usados os métodos multicritério ordinais de Borda, Condorcet e Copeland para ordenar, segundo o risco de subsidência, os perfis de Organossolos estudados. Os resultados mostram correlação entre os métodos (exceto Condorcet, que não foi capaz de ordenar as alternativas) e o resíduo mínimo, parâmetro usual para avaliar subsidência. Isso indica eficácia para ordenar/classificar os perfis de solos estudados quanto ao risco de subsidência. Os métodos quantitativos utilizados neste trabalho mostraram-se promissores como ferramentas em estudos na Ciência do Solo.
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BACKGROUND: The model for end-stage liver disease (MELD) was developed to predict short-term mortality in patients with cirrhosis. There are few reports studying the correlation between MELD and long-term posttransplantation survival. AIM: To assess the value of pretransplant MELD in the prediction of posttransplant survival. METHODS: The adult patients (age >18 years) who underwent liver transplantation were examined in a retrospective longitudinal cohort of patients, through the prospective data base. We excluded acute liver failure, retransplantation and reduced or split-livers. The liver donors were evaluated according to: age, sex, weight, creatinine, bilirubin, sodium, aspartate aminotransferase, personal antecedents, brain death cause, steatosis, expanded criteria donor number and index donor risk. The recipients' data were: sex, age, weight, chronic hepatic disease, Child-Turcotte-Pugh points, pretransplant and initial MELD score, pretransplant creatinine clearance, sodium, cold and warm ischemia times, hospital length of stay, blood requirements, and alanine aminotransferase (ALT >1,000 UI/L = liver dysfunction). The Kaplan-Meier method with the log-rank test was used for the univariable analyses of posttransplant patient survival. For the multivariable analyses the Cox proportional hazard regression method with the stepwise procedure was used with stratifying sodium and MELD as variables. ROC curve was used to define area under the curve for MELD and Child-Turcotte-Pugh. RESULTS: A total of 232 patients with 10 years follow up were available. The MELD cutoff was 20 and Child-Turcotte-Pugh cutoff was 11.5. For MELD score > 20, the risk factors for death were: red cell requirements, liver dysfunction and donor's sodium. For the patients with hyponatremia the risk factors were: negative delta-MELD score, red cell requirements, liver dysfunction and donor's sodium. The regression univariated analyses came up with the following risk factors for death: score MELD > 25, blood requirements, recipient creatinine clearance pretransplant and age donor >50. After stepwise analyses, only red cell requirement was predictive. Patients with MELD score < 25 had a 68.86%, 50,44% and 41,50% chance for 1, 5 and 10-year survival and > 25 were 39.13%, 29.81% and 22.36% respectively. Patients without hyponatremia were 65.16%, 50.28% and 41,98% and with hyponatremia 44.44%, 34.28% and 28.57% respectively. Patients with IDR > 1.7 showed 53.7%, 27.71% and 13.85% and index donor risk <1.7 was 63.62%, 51.4% and 44.08%, respectively. Age donor > 50 years showed 38.4%, 26.21% and 13.1% and age donor <50 years showed 65.58%, 26.21% and 13.1%. Association with delta-MELD score did not show any significant difference. Expanded criteria donors were associated with primary non-function and severe liver dysfunction. Predictive factors for death were blood requirements, hyponatremia, liver dysfunction and donor's sodium. CONCLUSION: In conclusion MELD over 25, recipient's hyponatremia, blood requirements, donor's sodium were associated with poor survival.
Resumo:
Errors are always present in experimental measurements so, it is important to identify them and understand how they affect the results of experiments. Statistics suggest that the execution of experiments should follow random order, but unfortunately the complete randomization of experiments is not always viable for practical reasons. One possible simplification is blocked experiments within which the levels of certain factors are maintained fixed while the levels of others are randomized. However this has a cost. Although the experimental part is simplified, the statistical analysis becomes more complex.
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In this work, the artificial neural networks (ANN) and partial least squares (PLS) regression were applied to UV spectral data for quantitative determination of thiamin hydrochloride (VB1), riboflavin phosphate (VB2), pyridoxine hydrochloride (VB6) and nicotinamide (VPP) in pharmaceutical samples. For calibration purposes, commercial samples in 0.2 mol L-1 acetate buffer (pH 4.0) were employed as standards. The concentration ranges used in the calibration step were: 0.1 - 7.5 mg L-1 for VB1, 0.1 - 3.0 mg L-1 for VB2, 0.1 - 3.0 mg L-1 for VB6 and 0.4 - 30.0 mg L-1 for VPP. From the results it is possible to verify that both methods can be successfully applied for these determinations. The similar error values were obtained by using neural network or PLS methods. The proposed methodology is simple, rapid and can be easily used in quality control laboratories.
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Chromatography combined with several different detection systems is one of the more used and better performing analytical tools. Chromatography with tandem mass spectrometric detection gives highly selective and sensitive analyses and permits obtaining structural information about the analites and about their molar masses. Due to these characteristics, this analytical technique is very efficient when used to detect substances at trace levels in complex matrices. In this paper we review instrumental and technical aspects of chromatography-tandem mass spectrometry and the state of the art of the technique as it is applied to analysis of toxic substances in food.
Resumo:
The validation of an analytical procedure must be certified through the determination of parameters known as figures of merit. For first order data, the acuracy, precision, robustness and bias is similar to the methods of univariate calibration. Linearity, sensitivity, signal to noise ratio, adjustment, selectivity and confidence intervals need different approaches, specific for multivariate data. Selectivity and signal to noise ratio are more critical and they only can be estimated by means of the calculation of the net analyte signal. In second order calibration, some differentes approaches are necessary due to data structure.
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A method to quantify lycopene and β-carotene in freeze dried tomato pulp by high performance liquid chromatography (HLPC) was validated according to the criteria of selectivity, sensitivity, precision and accuracy, and uncertainty estimation of measurement was determined with data obtained in the validation. The validated method presented is selective in terms of analysis, and it had a good precision and accuracy. Detection limit for lycopene and β-carotene was 4.2 and 0.23 mg 100 g-1, respectively. The estimation of expanded uncertainty (K = 2) for lycopene was 104 ± 21 mg 100 g-1 and for β-carotene was 6.4 ± 1.5 mg 100 g-1.
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This manuscript aims to show the basic concepts and practical application of Principal Component Analysis (PCA) as a tutorial, using Matlab or Octave computing environment for beginners, undergraduate and graduate students. As a practical example it is shown the exploratory analysis of edible vegetable oils by mid infrared spectroscopy.
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The difficulty in adapting European dairy cows breeds in Brazil affect considerably the milk production sector. Brazilian climatic conditions are not totally favorable and the development of new tecnologies is needed for the animals express their genetic potential, as well as their best feed conversion. An economical analysis of the applied investment in the free-stall climatization equipment in dairy housing, for estimating studies related to profit, possibility of return investment as well as time for this return is necessary. The objective of this research was to evaluate the influence of climatization investment in the milk production process and analyze the economical aspect of this investment. There were used 470 high productive dairy cows with genetic and morphologic homogeneous characteristics, and analyzed in two similar periods. Investment calculations were done using Excell®. The results were satisfactory and the invested capital was proved to return to the producer in a short term, 57 days.
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The purpose of this work was to analyze the logistical distribution of Brazilian soybean by applying a quadratic programming to a spatial equilibrium model. The soybean transportation system is an important part of the soybean complex in Brazil, since the major part of the costs of this commodity derives from the transportation costs. Therefore, the optimization of this part of the process is essential to a better competitiveness of the Brazilian soybean in the international market. The Brazilian soybean complex have been increasing its agricultural share in the total of the exportation value in the last ten years, but due to other countries' investments the Brazilian exportations cannot be only focused on increasing its production but it still have to be more efficient. This way, a model was reached which can project new frames by switching the transportation costs and conduce the policy makers to new investments in the sector.
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Currently, owing to the occurrence of environmental problems, along with the need of environmental preservation, both the territory management of Hydrographic Basin and the conservation of natural resources have proven to have remarkable importance. Thus, the mean goal of the research is to raise and scrutinize social-economic and technologic data from the Mogi Guaçu River Hydrographic Basin (São Paulo, Brazil). The aim is to group municipalities with similar characteristics regarding the collected data, which may direct joint actions in the Hydrographic Basin Management. There were used both the methods of factorial analysis and automatic hierarchical classifications. Additionally, there is going to be applied a Geographical Information System to represent the outcomes of the methods aforementioned, through the evolvement of a geo-referenced database, which will allow the obtainment of information categorically distributed including theme maps of interest. The main characteristics adopted to group the municipalities were: agricultural area, sugar cane production, small farms, animal production, number of agriculture machinery and equipments and agricultural income. The methodology adopted in the Mogi Guaçu River Hydrographic Basin will be analyzed vis-à-vis its appropriateness on basin management, as well as the possibility of assisting the studies on behalf of the São Paulo Hydrographic Basin groups, to regional development.