One trend in the ‘omics’ sciences is the generation of increasing amounts of data, describing complex biological samples. To cope with this and facilitate progress towards reliable diagnostic tools, it is crucial to develop methods for extracting representative and predictive information. In global metabolite analysis (metabolomics and metabonomics) NMR, GC/MS and LC/MS are the main platforms for data generation. Multivariate projection methods (e.g. PCA, PLS and O-PLS) have been recognized as efficient tools for data analysis within subjects such as biology and chemistry due to their ability to provide interpretable models based on many, correlated variables. In global metabolite analysis, these methods have been successfully applied in areas such as toxicology, disease diagnosis and plant functional genomics. This thesis describes the development of processing methods for the unbiased extraction of representative and predictive information from metabolic GC/MS and LC/MS data characterizing biofluids, e.g. plant extracts, urine and blood plasma. In order to allow the multivariate projections to detect and highlight differences between samples, one requirement of the processing methods is that they must extract a common set of descriptors from all samples and still retain the metabolically relevant information in the data. In Papers I and II this was done by applying a hierarchical multivariate compression approach to both GC/MS and LC/MS data. In the study described in Paper III a hierarchical multivariate curve resolution strategy (H-MCR) was developed for simultaneously resolving multiple GC/MS samples into pure profiles. In Paper IV the H-MCR method was applied to a drug toxicity study in rats, where the method’s potential for biomarker detection and identification was exemplified. Finally, the H-MCR method was extended, as described in Paper V, allowing independent samples to be processed and predicted using a model based on an existing set of representative samples. The fact that these processing methods proved to be valid for predicting the properties of new independent samples indicates that it is now possible for global metabolite analysis to be extended beyond isolated studies. In addition, the results facilitate high through-put analysis, because predicting the nature of samples is rapid compared to the actual processing. In summary this research highlights the possibilities for using global metabolite analysis in diagnosis.

This research project sought to explore, compare and develop chemometric methods with the goal of resolving chromatographically overlapped peaks though the use of spectral information gained from the four-way data sets associated with comprehensive two-dimensional liquid chromatography with diode array detection (LC ´ LC-DAD). A chemometric method combining iterative key set factor analysis (IKSFA) and multivariate curve resolution-alternating least squares (MCR-ALS) was developed. In the section of urine data analyzed, over 50 peaks were found, with 18 visually observable and 32 additional compounds found only after application of the chemometric method. Upon successful chemometric resolution of chromatographically overlapped peaks, accurate and precise quantification was then necessary. Of the compared methods for quantification, the manual baseline method was determined to offer the best precisions. Of the 50 found peaks from the urine analysis, 34 were successfully quantified using the manual baseline method with percent relative standard deviations ranging from 0.09 to 16. The accuracy of quantification was then investigated by the analysis of wastewater treatment plant effluent (WWTPE) samples. The chemometrically determined concentration of the unknown phenytoin sample was found to not exhibit a significant difference from the result obtained by the LC-MS/MS reference method, and the precision of the IKSFA-ALS method was better than that of the precision of the LC-MS/MS analysis. Chromatographic factors (data complexity, large dynamic range, retention time shifting, chromatographic and spectral peak overlap and background removal, were all found to affect the quantification results. The last part of this work focused on rapid screening methods that were capable of locating peaks between samples that exhibited significant differences in concentration. The aim here was to reduce the amount of data required to be resolved and quantified to only those peaks that were of interest. This would then reduce the time required to analyze large, complex samples by eliminating the need to first quantify all peaks in a given sample for many different samples. Both the similarity index (SI) method and the Fisher ratio (FR) method were found to fulfill this requirement in a rapid means of screening fifteen wine samples.

El objetivo de esta tesis ha sido estudiar y desarrollar metodologias analíticasusando un sistema de inyección secuencial (SIA) con un espectrofotómetro de diodos enfila para obtener datos de segundo orden. Para tratar estos datos, las herramientasquimiométricas usadas han sido; resolución de curvas multivariante mediante mínimoscuadrados alternados (MCR-ALS) y otras técnicas relacionadas a ésta como el análisisde componentes principales (PCA) y SIMPLISMA. Además se han aplicado estrategiasde diseño de experimentos para obtener las condiciones experimentales óptimas. Estametodología se aplicó a la determinación de amoxicilina y ácido clavulánico enmedicamentos.El primer capítulo de la tesis contiene una descripción de la amoxicilina y del ácidoclavulánico, una explicación de los fundamentos teóricos tanto del sistema instrumentalcomo de las herramientas quimiométricas usadas y por último, se describen los diseñosde experimentos usados y la función de deseabilidad.En los dos siguientes capítulos, se muestran en forma de artículos científicos lostrabajos experimentales realizados. En un primer artículo, se realizó una clasificación delos medicamentos dependiendo si se tenían interferentes o no, para posteriormenteproponer el tipo de calibrado. Un paso previo a la diferenciación de los medicamentos,fue buscar una secuencia analítica que permitiera obtener un sistema en evolución. Estaetapa se llevó a cabo mediante un diseño de experimentos.En el segundo artículo, se determinó la cantidad de amoxicilina en losmedicamentos que tenían interferentes y además no tenían zonas selectivas. Para llevara cabo de forma correcta la etapa de calibración se realizó un estudio de una serie deparámetros asociados a MCR-ALS. En un tercer artículo se realizó la determinaciónsimultánea del ácido clavulánico y de la amoxicilina que poseían unas característicasácido-base y una sensibilidad espectral similar. Por tal de determinar simultáneamenteambos analitos se rediseñó todo el experimental. En el cuarto artículo se hizo unarevisión bibliográfica de ambas técnicas a partir del año 2004 y se discutió el potencial deusar un sistema de inyección secuencial para generar datos de segundo orden.Con la experimentación realizada se comprobó que el paso clave en estasmetodologias era obtener una buen sistema en evolución, es decir diseñar una buenasecuencia analítica. Por lo que se profundizó en estrategias basadas en diseños deexperimentos. En el quinto artículo, se estudiaron qué factores podían afectar a lasecuencia analítica. También se propusieron respuestas que representaran de una formacuantitativa una buena resolución. Se realizó un diseño Plackett-Burman con el objetivode eliminar los factores no relevantes, para posteriormente modelar una superficie derespuesta a partir de los factores relevantes que permite visualizar las condicionesóptimas de la secuencia analítica.El inconveniente de utilizar la metodología de superficie de respuesta es que enlos casos donde el número de factores relevantes sea superior a 3 o 4, el número deexperiencias aumenta considerablemente. En estos casos, una técnica alternativa essimplex que dio lugar a un sexto artículo.El último capítulo de la tesis contiene las conclusiones. Como una conclusióngeneral, se puede decir que la combinación de un sistema de inyección secuencial (SIA)y una herramienta quimiométrica como la resolución de curvas multivariante mediantemínimos cuadrados alternados (MCR-ALS) puede ser usado tanto para realizar unanálisis cualitativo y cuantitativo ya que proporciona información de los perfiles deconcentración y perfiles espectrales de las diferentes especies a estudio. / The objective of this thesis is to study and develop analytical methods to determineamoxicillin and clavulanic acid in pharmaceuticals using sequential injection analysis (SIA)with a diode-array spectrophotometric detector to obtain second-order data. To treat thesedata, the chemometric tool used was; multivariate curve resolution with alternating leastsquares (MCR-ALS) and the techniques involved in the resolution process are: principalanalysis components (PCA) and simple-to-use interactive self-modelling mixture analysis(SIMPLISMA).The first chapter contains a brief description of the theoretical backgrounds thathave been used during this thesis. We explain the characteristics and properties ofamoxicillin and clavulanic acid, we describes the instrumental and the chemometric toolsused and at the end, we introduce the experimental designs used and the desirabilityfunction.In the next two chapters contain the bulk of the work carried out for this thesis andincorporate papers published in journals. In the first paper, the pharmaceuticals wereclassified according to their selective zones in order to propose the type of calibration. In aprevious step, the experimental work was conducted to find an analytical sequence thatallows us to obtain an evolving system. This step was carried out using experimentaldesign. In the second paper, the quantity of amoxicillin in the pharmaceuticals withinterferents or without selective zones was determined. To carry out correctly thecalibration step, we studied different conditions related to the MCR-ALS process.In the third paper, we propose the simultaneous determination of amoxicillin andclavulanic acid which they have the acid-base characteristics and spectral profile similar.To determine both analytes, a new analytical sequence was redesigned. In the fourthpaper, we describe the state of the art of sequential injection analysis (SIA) andmultivariate curve resolution with alternating least squares (MCR-ALS) by reviewing thebibliography since 2004. We discuss the potential of SIA for generating second-orderdata.In previous papers, we found that the most critical step in the development ofanalytical methods based on SIA and MCR-ALS was to obtain an analytical sequence thatprovides an evolving system. To resolve so, we developed the method of experimentaldesign to obtain the optimal analytical sequence.In the forth paper, we studied all the factors and analysed how they affect to theanalytical sequence. We also proposed responses to quantitatively represent a goodresolution. Once these factors and responses were proposed, we used a Plackett-Burmandesign to remove the non-relevant factors and then modelled a response surface. In themaximum of response surface, the optimum conditions for the analytical sequence couldbe visualised. To transform several responses into a single response, we used the overalldesirability function. In the sixth paper, we applied an alternative optimisation methodknows as the simplex approach. We aimed to determine amoxicillin and clavulanic acidsimultaneously when the number of factors and responses was higher than in theprevious paper.The last chapter contains the conclusions of the thesis. In general, we concludethat a combined sequential injection analysis (SIA) with a multivariate detector (i.e. diodearray spectrophotometer) and multivariate curve resolution with alternating least squares(MCR-ALS) can be used for both qualitative and quantitative analyses since, it providesconcentration and spectra profiles for the different species of the sample.

No description available.

No description available.

In chemical analyses, it is crucial to distinguish between chemical species. This is often accomplished via chromatographic separations. These separations are often pushed to their limits in terms of the number of analytes that can be sufficiently resolved from one another, particularly when a quantitative analysis of these compounds is needed. Very often, complicated methods or new technology is required to provide adequate separation of samples arising from a variety of fields such as metabolomics, environmental science, food analysis, etc. An often overlooked means for improving analysis is the use of chemometric data analysis techniques. Particularly, the use of chemometric curve resolution techniques can mathematically resolve analyte signals that may be overlapped in the instrumental data. The use of chemometric techniques facilitates quantitation, pattern recognition, or any other desired analyses. Unfortunately, these methods have seen little use outside of traditionally chemometrics focused research groups. In this dissertation, we attempt to show the utility of one of these methods, multivariate curve resolution-alternating least squares (MCR-ALS), to liquid chromatography as well as its application to more advanced separation techniques. First, a general characterization of the performance of MCR-ALS for the analysis of liquid chromatography-diode array detection (LC-DAD) data is accomplished. It is shown that under a wide range of conditions (low chromatographic resolution, low signal-to-noise, and high similarity between analyte spectra), MCR-ALS is able to increase the number of quantitatively analyzable peaks. This increase is up to five-fold in many cases. Second, a novel methodology for MCR-ALS analysis of comprehensive two-dimensional liquid chromatography (LC x LC) is described. This method, called two dimensional assisted liquid chromatography (2DALC), aims to improve quantitation in LC x LC by combining the advantages of both one-dimensional and two dimensional chromatographic data. We show that 2DALC can provide superior quantitation to both LC x LC and one dimensional LC under certain conditions. Finally, we apply MCR-ALS to an LC x LC analysis of fourteen furanocoumarins in three apiaceous vegetables. The optimal implementation of MCR-ALS and subsequent integration was determined. For these data, simply performing MCR-ALS on the two dimensional chromatogram and manually integrating the results proved to be the superior method. These results demonstrate the usefulness of these curve resolution techniques as a compliment to advanced chromatographic techniques.

The interaction between the amino acid glutathione (GSH) and zinc (II) and cadmium (II) ions was investigated using data obtained by potentiometric and voltammetric measurements. Solutions with ionic strength 0.1 M KCl with different metal-ligand ratios were titrated with standard solution of KOH and the pH profiles obtained were used to propose models of chemical equilibrium between the species. The potentiometric data treatment was performed using the Hyperquad software, which enabled that the formation constants of the differents pecies could be refined. The program HySS,belonging to the Hyperquad computer package, was used to obtain the species distribution curves. The best fit models of equilibrium was reached suggesting the existence of species in which the metal ions were coordinated by one and two molecules of the ligand, and the highest values were found for log β complex type MH2L, MHL2 and ML2. For the voltammetric data, multivariate curve resolution with alternating least squares (MCR-ALS) was applied. Several voltammograms recorded at different metal-ligand ratios generated a series of overlapping peaks, from which it was possible to recover the pure voltammograms and their concentration profiles applying non-negativity, unimodality and "closure" as constraints. For both systems studied (GSH-Zn and GSH-Cd), voltammograms were resolved to three components, the free metal and two complexes. The potentiometric and voltammetric data treated with MCR-ALS were capable to complement one another, constituting a important tool in the investigation of chemical equilibria between metal ions and ligands. / A interação entre o aminoácido glutationa (GSH) e os íons zinco (II) e cádmio (II) foi investigada a partir de dados obtidos por medidas potenciométricas e voltamétricas. Soluções com força iônica 0,1 M de KCl de diferentes proporções metal-ligante foram tituladas com solução padrão de KOH e os perfis de pH assim obtidos foram usados para propor os modelos de equilíbrio químico entre as espécies. Para tratar os dados potenciométricos foi utilizado o programa Hyperquad, possibilitando que as constantes de formação das diferentes espécies pudessem ser refinadas. O programa HySS, pertencente ao pacote computacional do Hyperquad, foi utilizado para obtenção as curvas de distribuição das espécies. O melhor ajuste dos modelos de equilíbrio foi alcançado propondo a existência de espécies em que os íons metálicos foram coordenados por uma e duas moléculas do ligante, sendo que os maiores valores de log β foram encontrados para os complexos do tipo MH2L, MHL2 e ML2. Para os dados voltamétricos, foi aplicado o método de resolução multivariada de curvas com mínimos quadrados alternantes (MCR-ALS). Vários voltamogramas registrados a diferentes proporções metal-ligante geraram uma série de picos sobrepostos, a partir dos quais foi possível recuperar os voltamogramas puros e respectivos perfis de concentração aplicando não negatividade, unimodalidade e closure como restrições. Para ambos os sistemas estudados (GSH-Zn e GSH-Cd) os voltamogramas foram resolvidos para três componentes, o metal livre e dois complexos. A potenciometria e a voltametria submetida a MCR-ALS mostraram-se capazes de se complementarem, constituindo-se em grandes ferramentas na investigação de equilíbrios químicos entre íons metálicos e ligantes.

Orientador: Ronei Jesus Poppi / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Química / Made available in DSpace on 2018-08-26T16:15:02Z (GMT). No. of bitstreams: 1 Almeida_MarianaRamosde_D.pdf: 6686279 bytes, checksum: 1e1d5d53538fb99a153ff4425595e0ce (MD5) Previous issue date: 2015 / Resumo: A motivação para o desenvolvimento dessa tese foi a busca por métodos de análise não destrutivos, com nenhum ou mínimo preparo de amostra e que permitam a obtenção do máximo de informação com a realização de uma única análise na área de forense e paleontologia. Em forense, a espectroscopia Raman e o método de classificação supervisionado PLS-DA (Análise Discriminante por Mínimos Quadrados Parciais) foram empregados para construir modelos de classificação. O primeiro modelo foi construído para discriminar cédulas autênticas de cédulas falsas. A análise foi baseada na caracterização das tintas usadas na confecção das cédulas. O segundo modelo de classificação foi construído para diferenciar o óleo essencial extraído de diferentes partes (caule, folhas e galhos) da árvore amazônica Aniba Rosaeodora. A confiabilidade dos modelos foi avaliada pelo cálculo do intervalo de confiança, que foram calculados usando a técnica de reamostragem bootstrap. Os resultados obtidos mostraram que os modelos de classificação podem ser usados como método complementar à inspeção forense clássica e método de triagem. O desempenho dos modelos de classificação foi avaliado pelo cálculo de sensibilidade, especificidade, eficiência e coeficiente de Mathew. A espectroscopia Raman de imagem e o método de análise de componentes independentes (ICA) foram empregados para a identificação de explosivos em superfícies de cédulas. O método ICA foi avaliado como método de resolução de curvas para extrair os perfis espectrais e as imagens Raman dos constituintes presentes nas superfícies analisadas. Os resultados obtidos mostraram que o método ICA é adequado para resolução de curvas, uma vez que alcançou desempenho equivalente ao método clássico MCR-ALS (Resolução Multivariada de Curvas com Mínimos Quadrados Alternados). O limite de detecção da metodologia apresentada foi de 50 µg.cm-2 para o explosivo TNT. Por fim, a espectroscopia Raman de imagem foi empregada no estudo da composição química de fósseis de peixes, com o objetivo de obter informações sobre características biológicas. Os resultados mostraram informações sobre a composição química do fóssil estudado / Abstract: The motivation for the development of this thesis was to search for non-destructive testing methods, with none or minimal sample preparation and allowing them to obtain maximum information with the completion of a single analysis for forensic and paleontology. In the forensics, the Raman spectroscopy and the PLS-DA (discriminant analysis by Partial Least Squares) classification method were explored to build classification models. The first model was built to discriminate authentic and counterfeit banknotes. The analysis was based on the characterization of inks used in the confection of the banknotes. The second classification model was built to differentiate the essential oil extracted from different parts (wood, leaves and branches) of the Brazilian tree Aniba rosaeodora. The reliability of the models was evaluated by calculating the confidence interval, which was calculated using the bootstrap resampling technique. The results show that the classification models can be used as a complementary method to classical forensic inspection and a screening method. The performance of classification models was evaluated by calculating sensitivity, specificity, efficiency and Matthew coefficient. In a third application, Raman hyperspectral imaging and the independent component analysis (ICA) method were used for identification of explosives on the surfaces of banknotes. The ICA method was evaluated as curve resolution method to extract the Raman spectral profiles and the images of the constituents present in the analyzed surfaces. The results showed that the ICA method is appropriate for curves resolution, once achieved equivalent performance to the classical MCR-ALS (Multivariate Curve Resolution with Alternating Least Squares) method. The methodology presented limit of detection of 50 µg.cm-2 for the explosive TNT. Finally, the Raman hyperspectral imaging was applied in paleontology to study the chemical composition of fish fossil with the aim of obtaining information on biological characteristics. The results showed information about the chemical composition of fossil studied / Doutorado / Quimica Analitica / Doutora em Ciências

Flat panel displays (FPDs) are microfabricated devices that are often fabricated on specialized glass substrates known as display glass. The surface chemistry of the outer few nanometers of display glass can have an important influence on FPD performance and yield. Dsiplay glass surface characterization is difficult because (i) display glass surface composition varies significantly from its bulk composition; (ii) high-surface area forms of glass, such as fibers and powders, may not have the same surface composition as melt-formed planar surfaces, and (iii) the surface composition of display glass may be altered through exposure to chemical treatments commonly used during flat panel display production, including acids, bases, etchants, detergents, and plasmas. We have performed a detailed surface composition of Eagle XG®, a widely used commercial display glass substrate, using a range of surface analytical techniques including time-of-flight secondary ion mass spectrometry (ToF-SIMS), angle-resolved X-ray photoelectron spectroscopy (AR-XPS) and low energy ion scattering (LEIS). The information from these techniques has given us a detailed understanding of the elemental surface composition and surface hydroxylation of Eagle XG® at length scales ranging from ca. 10 nm from the surface to the outermost atomic layer. These analyses reveal that the surface composition of Eagle XG® varies significantly from its bulk composition, having generally lower concentrations of Al, B, Mg, Ca, and Sr, and higher concentrations of Si. Treatment with an industrial alkaline detergent results in significant recovery of aluminum concentration at the Eagle XG® surface, while treatment with hydrochloric and hydrofluoric acid result in further depletion of Al, B, Mg, Ca, and Sr at the sample surface.We used ToF-SIMS to quantify surface hydroxyls at the sample surface of this material. The SiOH+/Si+ peak area ratio was a useful metric of surface hydroxylation. We studied the effects of adventitious surface contamination on the measurements by analyzing samples dosed with perdeuterated triacontane, a model alkane, prior to analysis. Thick triacontane overlayers suppressed the SiOH+ signal, indicating that this approach gives inaccurately low estimates of surface hydroxylation for samples with high degrees of surface contamination, and accurate measurements are only possible for very-clean surfaces. The number of of hydroxyls on Eagle XG® surfaces varied as the surfaces were exposed to different chemical treatments. HF- and HCl- treated surfaces had the highest degree of hydroxylation, while detergent-treated surfaces had the lowest.

Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2016-09-02T13:38:23Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação_Rafaella de Figueiredo Sales.pdf: 2788155 bytes, checksum: 95e4d0c2ca7494069abdc945b186152e (MD5) / Made available in DSpace on 2016-09-02T13:38:23Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação_Rafaella de Figueiredo Sales.pdf: 2788155 bytes, checksum: 95e4d0c2ca7494069abdc945b186152e (MD5) Previous issue date: 2016-02-19 / PETROBRÁS / PRH - 28 / O biodiesel é considerado um potencial substituto para os combustíveis de origem fóssil. Geralmente, esse biocombustível é produzido através da transesterificação de óleos vegetais ou gordura animal utilizando um álcool de cadeia curta. A vasta aplicação industrial da transesterificação para produção de biodiesel requer um cuidadoso monitoramento do processo e modelagem dessa reação, orientados para um melhor entendimento e para a otimização do processo. Além disso, o controle do processo é de fundamental importância para garantir a qualidade do biodiesel de forma constante, uniforme e atendendo às especificações necessárias para a sua comercialização. Dentre as técnicas existentes para o monitoramento de reações, a espectroscopia no infravermelho próximo permite uma análise rápida e não destrutiva, podendo ser utilizada para o monitoramento in-line de processos. Nesse contexto, o presente trabalho descreve o monitoramento in-line da produção de biodiesel por transesterificação de óleo de soja com metanol utilizando a espectroscopia na região do infravermelho próximo. As reações foram conduzidas em batelada com controle de temperatura e velocidade de agitação. Dois estudos diferentes foram então realizados a partir dos dados espectroscópicos coletados ao longo das reações. A primeira abordagem consistiu na implementação de estratégias de controle estatístico multivariado e de qualidade, baseadas em métodos de projeção multivariada. Nesse estudo, modelos de referência baseados em dois métodos diferentes (tempo real e após o término da batelada) foram desenvolvidos usando bateladas sob condições normais de operação (concentração de catalisador NaOH de 0,75% em massa em relação à massa de óleo de soja, temperatura de 55°C e velocidade de agitação de 500 rpm). Foram avaliadas diferentes técnicas de pré-processamento espectral, bem como estratégias para desdobramento da matriz de dados espectrais. Posteriormente, bateladas submetidas a diferentes perturbações (relacionadas à adição de água e a mudanças na temperatura, na velocidade de agitação, na concentração de catalisador e na matéria prima utilizada) foram produzidas para avaliar o desempenho dos diferentes modelos em relação às suas capacidades de detectar falhas de operação. De um modo geral, as cartas de controle desenvolvidas foram capazes de detectar a maioria das falhas intencionalmente produzidas ao longo do processo. Apenas pequenas perturbações na velocidade de agitação não foram identificadas. A segunda abordagem baseou-se no estudo do comportamento cinético da metanólise do óleo de soja em diferentes condições de temperatura (20, 45 e 55°C) e de concentração de catalisador (0,75 e 1,0% m/m de NaOH). Nesse estudo, a modelagem cinética foi realizada a partir dos perfis de concentração do éster metílico estimados utilizando o método de Resolução multivariada de curvas com mínimos quadrados alternantes com restrição de correlação. Os perfis de concentração obtidos permitiram o desenvolvimento de um estudo cinético simplificado da reação, a qual foi considerada como seguindo uma cinética de pseudo-primeira ordem baseada na concentração do éster metílico para a reação global de transesterificação. O modelo cinético incluiu apenas o regime pseudo-homogêneo, em que é observada uma rápida taxa de reação e a cinética está controlada pela reação química. Para esse regime, obteve-se uma energia de ativação de 32,29 kJ.mol-1, com base na equação de Arrhenius. / Biodiesel is considered a potential substitute for fossil fuels. In general, this biofuel is produced by transesterification of vegetable oils or animal fats using a short-chained alcohol. The wide industrial application of transesterification for biodiesel production requires a thorough process monitoring and modeling of this reaction, oriented to a better understanding and optimization of the process. Moreover, process control is of utmost importance to ensure in a constant and uniform way the biodiesel quality in order to meet commercialization requirements. Among the existing techniques applied for reaction monitoring, near infrared spectroscopy allows a fast and non-destructive analysis, being able to be used for in-line process monitoring. In this context, the present work describes the in-line monitoring of biodiesel production by transesterification of soybean oil with methanol using near infrared spectroscopy. Reactions were carried out in batch reactors with temperature and agitation speed control. Two different studies were then carried out from spectroscopic data collected throughout the reactions. The first approach consisted of the implementation of multivariate statistic and quality control strategies, based on multivariate projection methods. In this study, reference models based on two different methods (real time and end of batch) were developed using batches under normal operating condition (0.75 w/w% of catalyst NaOH with respect to the amount of oil, temperature of 55ºC and stirring speed of 500 rpm). Different techniques for pre-processing and unfolding the spectral data were evaluated. Afterwards, batches subjected to different disturbances (related with water addition and changes in the temperature, agitation speed, catalyst content and raw material used) were manufactured to assess the performance of the different models in terms of their capability for fault detection. In general, the control charts developed were able to detect most of the failures intentionally produced during the batch runs. Only small variations in the stirring spend were not detected. The second approach was based on the study of the kinetic behavior of the soybean oil methanolysiscarried out with different temperatures (20, 44 and 55°C) and catalyst (NaOH) concentrations (0.75 and 1.0 w/w% based onoil weight). In this study, the kinetic modelling was developed from methyl ester concentration profiles estimated by Multivariate curve resolution alternating least squares with correlation constraint. The obtained concentration profiles allowed the development of a simplified kinetic model of the reaction, which was considered to follow a pseudo-first order overall kinetics based on methyl ester concentration for global transesterification reaction. The kinetic model included only the pseudo-homogeneous regime where the overall process kinetics is under chemical reaction control and a fast methanolysis rate is observed. For this regime, the activation energy was 32.29 kJ.mol-1, based on Arrhenius equation.