Дисертації з теми "Chemometric approaches"
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Folch, Fortuny Abel. "Chemometric Approaches for Systems Biology." Doctoral thesis, Universitat Politècnica de València, 2017. http://hdl.handle.net/10251/77148.
Повний текст джерелаEsta tesis doctoral se centra en el estudio, desarrollo y aplicación de técnicas quimiométricas en el emergente campo de la biología de sistemas. Procedimientos comúnmente utilizados y métodos nuevos se aplican para resolver preguntas de investigación en distintos equipos multidisciplinares, tanto del ámbito académico como del industrial. Las metodologías desarrolladas en este documento enriquecen la plétora de técnicas utilizadas en las ciencias ómicas para entender el funcionamiento de organismos biológicos y mejoran los procesos en la industria biotecnológica, integrando conocimiento biológico a diferentes niveles y explotando los paquetes de software derivados de esta tesis. Esta disertación se estructura en cuatro partes. El primer bloque describe el marco en el cual se articulan las contribuciones aquí presentadas. En él se esbozan los objetivos de los dos proyectos de investigación relacionados con esta tesis. Asimismo, se introducen los temas específicos desarrollados en este documento mediante presentaciones en conferencias y artículos de investigación. En esta parte figura una descripción exhaustiva de las ciencias ómicas y sus interrelaciones en el paradigma de la biología de sistemas, junto con una revisión de los métodos multivariantes más aplicados en quimiometría, que suponen las pilares sobre los que se asientan los nuevos procedimientos aquí propuestos. La segunda parte se centra en resolver problemas dentro de metabolómica, fluxómica, proteómica y genómica a partir del análisis de datos. Para ello se proponen varias alternativas para comprender a grandes rasgos los datos de flujos metabólicos en estado estacionario. Algunas de ellas están basadas en la aplicación de métodos multivariantes propuestos con anterioridad, mientras que otras son técnicas nuevas basadas en descomposiciones bilineales utilizando rutas metabólicas elementales. A partir de éstas se ha desarrollado software de libre acceso para la comunidad científica. A su vez, en esta tesis se propone un marco para analizar datos metabólicos en estado no estacionario. Para ello se adapta el enfoque tradicional para sistemas en estado estacionario, modelando las dinámicas de los experimentos empleando análisis de datos de dos y tres vías. En esta parte de la tesis también se establecen relaciones entre los distintos niveles ómicos, integrando diferentes fuentes de información en modelos de fusión de datos. Finalmente, se estudia la interacción entre organismos, como naranjas y hongos, mediante el análisis multivariante de imágenes, con futuras aplicaciones a la industria alimentaria. El tercer bloque de esta tesis representa un estudio a fondo de diferentes problemas relacionados con datos faltantes en quimiometría, biología de sistemas y en la industria de bioprocesos. En los capítulos más teóricos de esta parte, se proponen nuevos algoritmos para ajustar modelos multivariantes, tanto exploratorios como de regresión, en presencia de datos faltantes. Estos algoritmos sirven además como estrategias de preprocesado de los datos antes del uso de cualquier otro método. Respecto a las aplicaciones, en este bloque se explora la reconstrucción de redes en ciencias ómicas cuando aparecen valores faltantes o atípicos en las bases de datos. Una segunda aplicación de esta parte es la transferencia de modelos de calibración entre instrumentos de infrarrojo cercano, evitando así costosas re-calibraciones en bioindustrias y laboratorios de investigación. Finalmente, se propone un paquete software que incluye una interfaz amigable, disponible de forma gratuita para imputación de datos faltantes. En la última parte, se discuten los aspectos más relevantes de esta tesis para la investigación y la biotecnología, incluyendo líneas futuras de trabajo.
Aquesta tesi doctoral es centra en l'estudi, desenvolupament, i aplicació de tècniques quimiomètriques en l'emergent camp de la biologia de sistemes. Procediments comúnment utilizats i mètodes nous s'apliquen per a resoldre preguntes d'investigació en diferents equips multidisciplinars, tant en l'àmbit acadèmic com en l'industrial. Les metodologies desenvolupades en aquest document enriquixen la plétora de tècniques utilitzades en les ciències òmiques per a entendre el funcionament d'organismes biològics i milloren els processos en la indústria biotecnològica, integrant coneixement biològic a distints nivells i explotant els paquets de software derivats d'aquesta tesi. Aquesta dissertació s'estructura en quatre parts. El primer bloc descriu el marc en el qual s'articulen les contribucions ací presentades. En ell s'esbossen els objectius dels dos projectes d'investigació relacionats amb aquesta tesi. Així mateix, s'introduixen els temes específics desenvolupats en aquest document mitjançant presentacions en conferències i articles d'investigació. En aquesta part figura una descripació exhaustiva de les ciències òmiques i les seues interrelacions en el paradigma de la biologia de sistemes, junt amb una revisió dels mètodes multivariants més aplicats en quimiometria, que supossen els pilars sobre els quals s'assenten els nous procediments ací proposats. La segona part es centra en resoldre problemes dins de la metabolòmica, fluxòmica, proteòmica i genòmica a partir de l'anàlisi de dades. Per a això es proposen diverses alternatives per a compendre a grans trets les dades de fluxos metabòlics en estat estacionari. Algunes d'elles estàn basades en l'aplicació de mètodes multivariants propostos amb anterioritat, mentre que altres són tècniques noves basades en descomposicions bilineals utilizant rutes metabòliques elementals. A partir d'aquestes s'ha desenvolupat software de lliure accés per a la comunitat científica. Al seu torn, en aquesta tesi es proposa un marc per a analitzar dades metabòliques en estat no estacionari. Per a això s'adapta l'enfocament tradicional per a sistemes en estat estacionari, modelant les dinàmiques dels experiments utilizant anàlisi de dades de dues i tres vies. En aquesta part de la tesi també s'establixen relacions entre els distints nivells òmics, integrant diferents fonts d'informació en models de fusió de dades. Finalment, s'estudia la interacció entre organismes, com taronges i fongs, mitjançant l'anàlisi multivariant d'imatges, amb futures aplicacions a la indústria alimentària. El tercer bloc d'aquesta tesi representa un estudi a fons de diferents problemes relacionats amb dades faltants en quimiometria, biologia de sistemes i en la indústria de bioprocessos. En els capítols més teòrics d'aquesta part, es proposen nous algoritmes per a ajustar models multivariants, tant exploratoris com de regressió, en presencia de dades faltants. Aquests algoritmes servixen ademés com a estratègies de preprocessat de dades abans de l'ús de qualsevol altre mètode. Respecte a les aplicacions, en aquest bloc s'explora la reconstrucció de xarxes en ciències òmiques quan apareixen valors faltants o atípics en les bases de dades. Una segona aplicació d'aquesta part es la transferència de models de calibració entre instruments d'infrarroig proper, evitant així costoses re-calibracions en bioindústries i laboratoris d'investigació. Finalment, es proposa un paquet software que inclou una interfície amigable, disponible de forma gratuïta per a imputació de dades faltants. En l'última part, es discutixen els aspectes més rellevants d'aquesta tesi per a la investigació i la biotecnologia, incloent línies futures de treball.
Folch Fortuny, A. (2016). Chemometric Approaches for Systems Biology [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/77148
TESIS
Premiado
Guan, Pingping. "Class I HLA supertype and supermotif definition by chemometric approaches." Thesis, University College London (University of London), 2005. http://discovery.ucl.ac.uk/1445534/.
Повний текст джерелаStubbins, Frederick John. "Addressing the challenges of crude oil processing utilising chemometric approaches." Thesis, University of Newcastle upon Tyne, 2018. http://hdl.handle.net/10443/4047.
Повний текст джерелаTeague, Claire Rachel. "NMR spectroscopic and chemometric approaches to investigate metabolic variation in biofluids." Thesis, Imperial College London, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.414749.
Повний текст джерелаHerranz-Trillo, Fatima. "Disentangling structural complexity in proteins by decomposing SAXS data with chemometric approaches." Thesis, Montpellier, 2017. http://www.theses.fr/2017MONTT044/document.
Повний текст джерелаMany biological systems are inherently polydisperse, presenting multiple coexisting species differing in size, shape or conformation (i.e. oligomeric mixtures, weakly bound complexes, and species appearing along amyloidogenic processes). The study of such complex systems is challenging due to the instability of the species involved, their low and interdependent relative concentrations, and the difficulties to isolate the pure components. In this thesis, I have developed methodological approaches to apply Small-Angle X-ray Scattering (SAXS), a low-resolution structural biology technique, to the study of polydisperse systems. As an additive technique, the SAXS pattern measured for a polydisperse sample corresponds to the concentration-weighted sum of the contributions from each of the individual components. However, decomposition of SAXS data into species-specific spectra and relative concentrations is laborious and burdened by ambiguity. In this thesis, I present an approach to decompose SAXS datasets into the individual components. This approach adapts the chemometrics Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) method to the specificities of SAXS data. Our method enables the rigorous and robust decomposition of SAXS data by simultaneously introducing different representations of these data and, consequently, emphasizing molecular changes at different time and structural resolution ranges. We have applied this approach, which we name COSMiCS (Complex Objective Structural analysis of Multi-Component Systems), to study two polydisperse systems: amyloid fibrillation by analysing time-dependent SAXSdata, and conformational fluctuations through the analysis of data obtained using on-line size-exclusion chromatography coupled to SAXS (SEC-SAXS). The importance of studying fibrillation processes lies in their implication in amyloidogenic pathologies such as Parkinson’s or Alzheimer’s diseases. There exist strong indications that soluble oligomeric species, and not mature fibrils, are the main cause of cytotoxicity and neuronal damage emphasizing the importance of characterizing early stages of fibrillation. The first application of our COSMiCS approach has allowed the study of the amyloidogenic mechanisms of insulin and the familial mutant E46K of ↵-synuclein, a Parkinson’s disease related protein. The analysis enables the structural characterization of all the species present as well as their kinetic transformations. The second part of the thesis is dedicated to the use of COSMiCS to analyze on-line SEC-SAXS experiments. Using synthetic data, I demonstrate the capacity of chemometric approaches to decompose complex chromatographic profiles. Using this approach, I have studied the conformational fluctuations in prolyl oligopeptidase (POP), a protein related to synaptic functions and neuronal development. In summary, this thesis presents a novel chemometrics approach that can be generally applied to any macromolecular mixture with a tuneable equilibrium that is amenableto SAXS. Transient biomolecular complexes, folding processes, or ligand-dependent structural rearrangements can be probed structurally using COSMiCS
Vestner, Jochen. "New Chemometric Approaches to Non-targeted GCMS Fingerprinting Analysis of Wine Volatiles." Thesis, Bordeaux, 2016. http://www.theses.fr/2016BORD0141/document.
Повний текст джерелаIn contrast to targeted gas chromatography mass spectrometry (GC-MS) analysis of wine volatiles, non-targeted GC-MS approaches take information of known and unknown compounds into account, are faster, inherently more comprehensive and give a more holistic representation of the sample composition. Although several non-targeted approaches have been developed, there is still a great demand for automated data processing tools, especially for complex multi-way data such as chromatographic data obtained from multichannel detectors (e.g. GC-MS chromatograms of multiple samples). This work therefore aimed at the development of data processing procedures for non-targeted GC-MS analysis of volatile wine compounds. The two developed approaches use basic matrix manipulation of segmented GC-MS chromatograms and PCA or PARAFAC multi-way modelling. The approaches take retention time shifts between samples into account and avoid peak integration. A demonstration of the new fingerprinting approaches is presented using an artificial GC-MS data set and an experimental full-scan GC-MS data set obtained for a set of experimental wines. Results of the new approaches were also compared to a references method. Furthermore, the combination of one of the developed GC-MS fingerprinting approaches with the fast sensory screening technique projective mapping was exploited as a powerful approach to simultaneously study the volatile composition and the sensory characteristics of experimental wines. This methodology was used to study the impact of different malolactic fermentation scenarios on two different Pinotage wine styles and for a full factorial investigation of the impact of grape vine age, must turbidity and yeast strain on the aroma of Riesling experimental wines
BACCOLO, GIACOMO. "Chemometrics approaches for the automatic analysis of metabolomics GC-MS data." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2022. http://hdl.handle.net/10281/374731.
Повний текст джерелаMetabolomics, which consists of identifying all the metabolites present in the biological samples analysed, is an approach widely applied in various research fields such as biomarker identification, new drug development, food and environmental sciences. Metabolomics is closely linked to the ability of analytical techniques, one of the most widely applied being gas chromatography coupled to mass spectrometry. Modern analytical platforms can generate hundreds of thousands of spectra, detecting an impressive number of distinct molecules. Despite the technical progress achieved on the experimental side, the conversion of signals measured by instruments into useful information is not an obvious step in metabolomic studies. For each identified compound, the goal is to obtain the relative concentration among all analysed samples and the mass spectrum associated with the compound needed to identify the molecule itself. The software available for analysing experimental data has repeatedly been cited as a major source of uncertainty, severely limiting both the quantity and quality of the information extracted. The most applied tools are based on univariate data analysis, considering each sample separately from the others and requiring the operator to set several parameters, affecting the result of the analysis. In this thesis, a new approach, called AutoDise, for the analysis of GC-MS data is described. The processing of the experimental signals is based on PARAFAC2. PARAFAC2 is a model that decomposes multidimensional data, discriminating between different signals in the samples. Due to its properties, PARAFAC2 does not need the data to be pre-processed and does not require parameters to be set, whereas software used in this field requires several parameters to be defined and laborious pre-processing of the data, requiring the intervention of an expert user, and the reproducibility of the results is limited, depending on the parameters chosen by the user. However, fitting PARAFAC2 models involves several steps and an experienced analyst is needed to analyse and interpret the models. AutoDise is an expert system capable of handling all modelling steps and generating a peak table in which each compound is uniquely identified, with fully reproducible results. This is possible thanks to the combination of different diagnostic tools and the application of artificial intelligence models. The performance of the approach was tested on a complex dataset of olive oils obtained by GC-MS analysis. The data were analysed both manually, by experienced users, and automatically with the proposed AutoDise method and the resulting peak tables were compared. The results show that AutoDise outperforms manual analysis both in terms of the number of compounds identified and the quality of identification and quantification. In addition, a GUI was developed to make the algorithm more accessible to people not skilled in the programming language. The thesis includes a tutorial showing the main features and how to use the GUI. Another important part of the thesis was devoted to testing and developing new artificial neural networks to be implemented in the AutoDise software to detect which PARAFAC2 components are providing chemically useful information. To this end, more than 170,000 profiles were manually labelled in order to train, validate and test a convolutional neural network and a bilinear network with short-term memory and a k-nearest neighbour model. The results suggest that deep learning networks can be effectively applied for the automatic classification of chromatographic profiles.
Ryabchykov, Oleg [Verfasser], Jürgen [Gutachter] Popp, and Thomas Wilhelm [Gutachter] Bocklitz. "Investigations on chemometric approaches for diagnostic applications utilizing various combinations of spectral and image data types / Oleg Ryabchykov ; Gutachter: Jürgen Popp, Thomas Wilhelm Bocklitz." Jena : Friedrich-Schiller-Universität Jena, 2019. http://d-nb.info/1206604719/34.
Повний текст джерелаCeci, Adriana Teresa. "Measuring the nutritional quality of local plant-based EUREGIO foods." Doctoral thesis, Università degli studi di Trento, 2022. https://hdl.handle.net/11572/355331.
Повний текст джерелаMörén, Lina. "Metabolomics and proteomics studies of brain tumors : a chemometric bioinformatics approach." Doctoral thesis, Umeå universitet, Kemiska institutionen, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-111309.
Повний текст джерелаBain, Alison. "Property prediction with Raman spectroscopy in the pulp and paper industry : a chemometric approach." Thesis, University of British Columbia, 2016. http://hdl.handle.net/2429/58800.
Повний текст джерелаScience, Faculty of
Chemistry, Department of
Graduate
Malegori, C. "SPECTROSCOPY, IMAGE ANALYSIS AND HYPERSPECTRAL IMAGING FOR FOOD SAFETY AND QUALITY: A CHEMOMETRIC APPROACH." Doctoral thesis, Università degli Studi di Milano, 2015. http://hdl.handle.net/2434/346455.
Повний текст джерелаThis PhD project regards different applications of non-destructive optical techniques to evaluate quality and shelf life of agro-food product as well as the early detection of biofilm on food plants. Spectroscopy, image analysis and hyperspectral imaging could play an important role in the assessment of both quality and safety of foods due to their rapidity and sensitivity especially when using simplified portable devices. Due to the huge amount of collected data, chemometric, a multivariate statistical approach, is required, in order to extract information from the acquired signals, reducing dimensionality of the data while retaining the most useful spectral information. The thesis is organized in four chapters, one for each technique and a final chapter including the overall conclusion. Each chapter is divided in case studies according to the matrix analysed and the data acquisition and elaboration carried out. The first chapter is about spectroscopy. The aim of the first study - Testing of a Vis-NIR system for the monitoring of long-term apple storage - is to evaluate the applicability of visible and near-infrared (Vis-NIR) spectroscopy to monitor and manage apples during long-term storage in a cold room. The evolution of the apple classes, originally created, was analysed during 7 months of storage by monitoring TSS and firmness. Vis-NIR allows an accurate estimation of chemical-physical parameters of apples allowing a non-destructive classification of apples in homogeneous lots and a better storage management. The work reported in the second paragraph - Wavelength selection with a view to a simplified handheld optical system to estimate grape ripeness - is aimed to identify the three most significant wavelengths able to discriminate grapes ready to be harvested directly in the field. Wavelengths selection was carried out with a view to construct a simplified handheld and low-cost optical device. Standardized regression coefficients of the PLS model were used to select the relevant variables, representing the most useful information of the full spectral region. The same approach was followed to discriminate freshness levels during shelf-life of fresh-cut Valerianella leaves - Selection of optimal wavelengths for decay detection in fresh-cut Valerianella Locusta Laterr. (third paragraph). The aim of the work presented in the fourth paragraph of the first chapter - Comparison between FT-NIR and Micro-NIR in the evaluation of Acerola fruit quality, using PLS and SVM regression algorithms - is to estimate titratable acidity and ascorbic acid content in acerola fruit, using a MicroNIR, an ultra-compact and low-cost device working between 950 – 1650 nm. The spectral data were modelled using two different regression algorithms, PLS (partial least square) and SVM (support vector machine). The prediction ability of Micro-NIR appears to be suitable for on field monitoring using non-linear regression modelling (i.e. SVM). In the second chapter, image analysis was performed. The traditional RGB imaging for the evaluation of image texture, a specific surface characteristic, is presented. The texture of an image is given by differences in the spatial distribution, in the frequency and in the intensity of the values of the grey levels of each pixel of the image. This technique was applied for the early detection of biofilm in its early stages of development, when it is still difficult to observe it by the naked eye, was evaluated (Image texture analysis, a non-conventional technique for early detection of biofilm). In the third paragraph, image and spectroscopy were combined in hyperspectral imaging applications. Data analysis by chemometric was crucial in any stage of my PhD project. Chemometric is a multivariate statistical approach that is applied on chemical data to extract the useful information avoiding noise and redundant data. At the beginning of the third chapter - Hyperspectral image analysis: a tutorial - proposes an original approach, developed as a flow sheet for three-dimensional data elaboration. The method was applied, as an example, to the prediction of bread staling during storage. The first application about hyperspectral on acerola is focused on the vitamin C content - HIS for quality evaluation of vitamin C content in Acerola fruit. Ten different acerola fruits picked up according to two different stages of maturity, based on the colour of the peel (5 green and 5 red acerola), were analysed. The spectra of pure vitamin C powder was used as references for computing models with two different correlation techniques: spectral angle mapping and correlation coefficient allowing the construction of a qualitative distribution map of ascorbic acid inside the fruit. The aim of the last one work presented is to evaluate acerola post-harvest quality - Selection of NIR wavelengths from hyperspectral imaging data for the quality evaluation of Acerola fruit. Hyperspectral images of 20 acerolas were acquired for five consecutive days and an investigation of time trends was carried out to highlight the most important three wavelengths that characterized the ripeness/degradation process of the Acerola fruit. The false-colour RGB images, derived from the composition of the three interesting wavelengths selected, data enable early detection of the senescence process in a rapid and non-destructive manner. In conclusion, the three non-destructive optical techniques applied in this PhD project have proved to be one of the most efficient and advanced tools for safety and quality evaluation in food industry answering the need for accurate, fast and objective food inspection methods to ensure safe production throughout the entire production process.
MERCURIALI, Mattia. "Study of multicomponent chromatograms using a chemometric approach: characterization of the organic fraction of atmospheric aerosol." Doctoral thesis, Università degli studi di Ferrara, 2010. http://hdl.handle.net/11392/2389169.
Повний текст джерелаBai, Chuannan. "Noninvasive near infrared spectroscopy on living tissue with multivariate calibration approaches." Diss., University of Iowa, 2010. https://ir.uiowa.edu/etd/776.
Повний текст джерелаRiovanto, Roberto. "Near infrared spectroscopy in food analysis: qualitative and quantitative approaches." Doctoral thesis, Università degli studi di Padova, 2011. http://hdl.handle.net/11577/3427409.
Повний текст джерелаLa qualità degli alimenti è un concetto molto ampio e talvolta difficile da definire. Il cibo è un miscuglio di composti chimici e proprietà fisiche che insieme definiscono le caratteristiche dell’alimento stesso. Determinare la qualità di un sistema così complesso è spesso molto difficile, soprattutto considerate le tecniche analitiche disponibili, che generalmente riescono a valutare un costituente o una proprietà alla volta senza essere in grado di esprimere un giudizio generale sulla qualità del prodotto. Queste tecniche analitiche, inoltre, sono solitamente costose in quanto richiedono strumentazioni elaborate e personale addetto qualificato. La spettroscopia nel vicino infrarosso (NIRS) sembra essere in grado di risolvere buona parte di queste problematiche. Gli spettri ottenuti attraverso lo scansionamento dei campioni possono essere considerati una sorta di “impronta digitale” della sostanza organica e possono contenere molte informazioni riguardanti la composizione e le proprietà chimico-fisiche degli alimenti. Il vero vantaggio della tecnologia NIR resta comunque la sua velocità nel fornire i risultati. Questa caratteristica è estremamente importante nel settore alimentare, dove i prodotti sono altamente deperibili e devono essere commercializzati nel più breve tempo possibile. La spettroscopia NIR si adatta perfettamente alle moderne esigenze delle industrie alimentari dove le catene di produzione sono principalmente automatizzate e la qualità degli alimenti deve essere monitorata costantemente in modo tale da standardizzare la qualità del prodotto finito. Nonostante la spettroscopia NIR venga utilizzata da laboratori ed industrie alimentari da parecchi anni, c’è ancora spazio per ulteriore ricerca in questo campo. Attraverso la mia tesi di dottorato ho cercato di ampliare le possibili applicazioni della tecnologia NIR per risolvere delle problematiche concrete del settore “produzione e commercializzazione” degli alimenti. Il lavoro è stato suddiviso in 7 capitoli. Il primo riguarda alcuni aspetti generali della spettroscopia NIR e fornisce una breve descrizione dei fondamenti, delle attrezzature e degli strumenti necessari per l‘interpretazione degli spettri. La parte riguardante la chemiometria vuole essere una sorta di introduzione per coloro che si avvicinano per la prima volta a questa disciplina molto ampia. Il numero di formule inserito in questa tesi è stato mantenuto il più basso possibile, riportando solo quelle necessarie per ottenere delle buone calibrazioni e per poter poi testare le loro performance. Gli altri sei capitoli della tesi trattano i diversi contributi sperimentali che ho condotto durante i miei tre anni di dottorato di ricerca: - nel primo studio la spettroscopia NIR è stata utilizzata per valutare la qualità della carne di coniglio basando l’analisi sul prodotto fresco. È stata inoltre testata la capacità discriminante di questa tecnologia per classificare i campioni sulla base della loro linea genetica di appartenenza. È stato dimostrato che la tecnologia NIR potrebbe diventare una tecnica analitica di supporto nei piani di selezione genetica dei conigli per monitorare la qualità della loro carne soprattutto per quel che riguarda la predizione dei principali costituenti chimici e del profilo acidico di questo prodotto; - gli obiettivi del secondo contributo sperimentale sono stati la predizione della composizione centesimale del formaggio Pecorino Siciliano DOP e la classificazione di questo prodotto sulla base del suo grado di stagionatura. Per essere commercializzato con la denominazione DOP, questo formaggio deve rispettare alcuni prerequisiti minimi quali un contenuto di grasso pari al 40% sulla sostanza secca e un livello di stagionatura minima di 4 mesi. NIRS sembra una tecnica analitica molto utile per poter standardizzare la qualità e le tecniche di produzione dei prodotti tradizionali italiani che per essere commercializzati su mercati nazionali ed internazionali devono presentare caratteristiche ben definite; - l’obiettivo del terzo e quarto contributo sperimentale è stato il confronto di diverse regioni spettrali quali il NIR (vicino infrarosso) e il visibile-vicino infrarosso (Vis-NIR) per la discriminazione di pesce fresco da quello decongelato. I due contributi avevano come oggetto di studi due prodotti ittici di qualità quali i filetti di orata e i tranci di pesce spada. La vendita di prodotto decongelato spacciato per fresco è una comune frode commerciale da cui i consumatori e i commercianti devono essere protetti. La spettroscopia si è dimostrata una tecnica analitica utile per discriminare campioni che hanno subito trattamenti di conservazione diversi, in particolare per quei prodotti ittici che hanno perso la loro integrità anatomica (quali filetti e tranci); - il quinto studio ha trattato un argomento particolarmente importante nell’ambito della spettroscopia NIR: il trasferimento di calibrazioni tra diversi strumenti. Il nostro laboratorio aveva a disposizione una calibrazione ampia e robusta costruita sul grasso suino per la predizione del numero di iodio e del profilo acidico. Le equazioni erano state ottenute usando uno spettrofotometro FOSS NIRSystem 5000. Il nostro obiettivo era quello di trasferire questa calibrazione su altri due strumenti (Unity Scientific 2500x e un sensore Zeiss MMS1 portatile) per poter quindi mantenere e sfruttare l’informazione acquisita durante molti anni di analisi chimiche di laboratorio su questa matrice. Per evitare la ricalibrazione degli strumenti secondari, la chemiometria mette a disposizione diverse tecniche definite “modelli di standardizzazione” che nel nostro studio sono state poste a confronto; - l’obiettivo dell’ultimo contributo introdotto in questa tesi è stata la discriminazione di vino Shiraz prodotto in 5 diverse regioni australiane particolarmente vocate per il settore vitivinicolo (Barossa Valley, McLaren Vale, Clare Valley, Coonawarra, Western Australia). Diverse regioni spettrali sono state confrontate a tale scopo (Visibile, vicino infrarosso e medio infrarosso), sfruttando inoltre diverse tecniche di classificazione che la chemiometria mette a disposizione. Conoscere l’origine degli alimenti è di particolare importanza soprattutto per salvaguardare i prodotti tradizionali. Questi, infatti, rischiano di essere sostituiti con prodotti simili ma di qualità inferiore. La spettroscopia NIR, impiegando le informazioni contenute nello spettro di un alimento, si è rivelata in grado di discriminare i prodotti sulla base della loro origine. Sicuramente la spettroscopia NIR non è una “scatola magica” dove tutte le domande trovano risposta e i problemi vengono risolti, ma possiede una versatilità tale da consentirne l’impiego in molteplici realtà industriali e commerciali. Attraverso la mia tesi ho cercato di mettere in luce le potenzialità di questa tecnologia senza però nascondere i limiti che ho riscontrato nel corso del suo utilizzo.
Tang, Fenfen. "Metabolic profiling of complex mixtures using novel NMR-based approaches and chemometrics: Pomegranate juice as a case study." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1575485567931001.
Повний текст джерелаAbdullah, Sewa Faraj. "Proteomics approaches to polyketide synthases interfaces by mass spectrometry and NMR spectroscopy and the application of chemometrics to metabolomics." Thesis, University of Bristol, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.682232.
Повний текст джерелаLapins, Maris. "Development of Proteochemometrics—A New Approach for Analysis of Protein-Ligand Interactions." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Universitetsbiblioteket [distributör], 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-7211.
Повний текст джерелаLiu, Yuanli. "Development of Cross-reactive Sensors Array: Practical Approach for Ion Detection in Aqueous Media." Bowling Green State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1345428697.
Повний текст джерелаSTRANI, LORENZO. "PROCESS ANALYTICAL TECHNOLOGY APPROACHES FOR DAIRY INDUSTRY." Doctoral thesis, Università degli Studi di Milano, 2021. http://hdl.handle.net/2434/814055.
Повний текст джерелаThis thesis work wants to answer the need of dairy industry to increase productivity while satisfying the consumers request for higher quality products. In order to do that, dairy companies need innovative methods to improve the understanding and the monitoring of production processes. Process Analytical Technology (PAT) approaches are the perfect tool for this purpose, as they use green, fast, non-invasive and non-destructive sensors that allow to perform measurements in real time. The most used techniques in this field are Near- and Mid-Infrared (NIR and MIR, respectively) spectroscopy, whose probes can be directly installed in critical points of the process providing both physical and chemical information of the product. However, these techniques have the drawback of providing results (spectra) difficult to be interpreted without proper statistical tools. In this context, Chemometric methods and algorithms allow the extraction of relevant information from spectroscopic data, providing a better understanding of the studied system. The first part of the present work focused on the monitoring of the coagulation process, one of the most critical moments of cheesemaking. To this aim, an FT-NIR spectroscopy system was used, acquiring spectra along the rennet coagulation process. According to a Box-Behnken experimental design, several coagulation trials were carried out, changing crucial technological factors, such as temperature, fat content and pH. Through Multivariate Curve Resolution optimized by Alternating Least Squares (MCR-ALS) algorithm it was possible to both have a reliable description of the three different coagulation phases and, most importantly, to build Multivariate Statistical Process Control (MSPC) charts, able to detect failures from the first moment of the process. Moreover, ANOVA-Simultaneous Component Analysis (ASCA) method was applied on spectral data to obtain a better understanding of the process, highlighting in which way each physicochemical parameter affects the process. In the second part of the work, FT-NIR spectroscopy was tested as a possible tool to replace the golden standards of coagulation ability, i.e. Formagraph. Coagulation trials were carried out using different milk powder samples. The use of MCR-ALS algorithm permitted the assessment of the best powder in terms of coagulation attitude and, in addition, it highlighted the non-significant effect on coagulation occurrence of CaCl2 concentration and of heat treatment on reconstituted milk. Finally, experimental trials carried out with mixtures of skimmed milk and reconstituted milk showed a slower coagulation time when a higher reconstituted milk percentage was used. The last part of the work regarded the use of MIR spectroscopy to monitor Galactooligosaccharides (GOS) production from cheese whey, in order to avoid the waste of this compound and to optimize the studied process. To do so, Partial Least Square (PLS) regression was used to predict the specific compounds resultant from the different enzymatic reaction studied. In conclusion, the application of the proposed methods will implicate, with a modest environmental impact, an efficient control of the process, satisfying at the same time law requirements and consumers’ needs. Furthermore, reliability of PAT approaches could be strengthened by future industrial applications.
Ahmad, Muhammad Haseeb [Verfasser], and Bernd [Akademischer Betreuer] Hitzmann. "Fluorescence spectroscopy and chemometrics : an innovative approach for characterization of wheat flour and dough preparation / Muhammad Haseeb Ahmad. Betreuer: Bernd Hitzmann." Hohenheim : Kommunikations-, Informations- und Medienzentrum der Universität Hohenheim, 2016. http://d-nb.info/1111628491/34.
Повний текст джерелаAndersson, Karl. "Characterization of Biomolecular Interactions Using a Multivariate Approach." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-4322.
Повний текст джерелаQuasso, Fabio. "Elemental profiling as a chemical investigation approach: application to health studies and food authentication." Doctoral thesis, Università del Piemonte Orientale, 2018. http://hdl.handle.net/11579/97204.
Повний текст джерелаGrassi, S. "MICROBIAL FOOD FERMENTATIONS: INNOVATIVE APPROACH USING INFRARED SPECTROSCOPY." Doctoral thesis, Università degli Studi di Milano, 2014. http://hdl.handle.net/2434/232573.
Повний текст джерелаPanayiotou, Helen. "Vibrational spectroscopy of keratin fibres : A forensic approach." Thesis, Queensland University of Technology, 2004. https://eprints.qut.edu.au/15953/7/Helen_Panayiotou_Thesis_ePrint-15953.pdf.
Повний текст джерелаPanayiotou, Helen. "Vibrational spectroscopy of keratin fibres : A forensic approach." Queensland University of Technology, 2004. http://eprints.qut.edu.au/15953/.
Повний текст джерелаChorell, Elin. "Mapping the consequenses of physical exercise and nutrition on human health : A predictive metabolomics approach." Doctoral thesis, Umeå universitet, Kemiska institutionen, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-43844.
Повний текст джерелаEmbargo until 2012-06-01
Gentner, Janene Margaret. "Tissue analysis : multidisciplinary approach using FT-IR microspectroscopy and visual microscopy." Thesis, Queensland University of Technology, 2001.
Знайти повний текст джерелаEgloff, Coraline. "Synthèse et étude en milieux biologiques de motifs structuraux sensibles aux médiateurs chimiques." Thesis, Strasbourg, 2013. http://www.theses.fr/2013STRAF031.
Повний текст джерелаThe main topic of this work was the research and the use of new structural patterns sensitive to chemical mediators. A chimiometric approach was developped to obtain reactivity profiles which will be filed in a table with a color code in order to visually highlight the patterns having interessant potential. Then, the patterns of interest were integrated in FRET-based probes which were tested in cell experiments. This profiling led to a new type of biologically and chemically deactivatable quencher. Thus, even in the absence of the studied mediator, this quencher incorporated in a FRET probe will be activated by adding an exogenous chemical agent to reveal inactivated probes in the cell
Pomareda, Sesé Victor. "Signal Processing Approaches to the Detection and Localization of Gas Chemical Sources using Partially Selective Sensors." Doctoral thesis, Universitat de Barcelona, 2013. http://hdl.handle.net/10803/119727.
Повний текст джерелаDebido a los progresos recientes, la instrumentación química genera mayores volúmenes de datos los cuales requieren de un procesado automático con la finalidad de extraer la información relevante, ya que un análisis manual no suele ser viable debido a la elevada complejidad de los datos. La habilidad de detectar, identificar y cuantificar sustancias químicas en fase gas en operaciones de campo es requerida en un gran número de aplicaciones. Entre ellas, aplicaciones humanitarias y de seguridad. En estos casos, la monitorización continua de los entornos es extremadamente importante, ya que se debe estar alerta de eventos anormales. En los escenarios más críticos, debe realizarse una exploración del área porque la posición de la fuente de gas de interés es desconocida. Esta exploración puede realizarse usando múltiples robots. Diferentes tecnologías de sensores se han aplicado con éxito a la detección e identificación de diferentes sustancias químicas (gases o compuestos volátiles). Estos compuestos pueden ser tóxicos, peligrosos, o precursores de explosivos o drogas. De entre estas tecnologías, los analizadores basados en movilidad iónica (IMS) proporcionan rápidas respuestas con gran sensibilidad. Sin embargo, estos instrumentos no están exentos de problemas. Típicamente, proporcionan una moderada selectividad, apareciendo picos solapados en los espectros. Además, la presencia de humedad provoca que los picos se ensanchen, así empeorando la resolución. Además, la respuesta de IMS es no lineal al incrementar la concentración y es posible que más de un pico debido al mismo compuesto aparezca en el espectro. En la presente tesis se trata con estos problemas y se demuestra que las herramientas de análisis de datos multivariantes son más efectivas que las herramientas típicas univariantes al tratar con tecnologías de movilidad iónica (IMS y DMA), especialmente para el análisis cualitativo y cuantitativo de sus espectros. Además, se demuestra que las medidas cuantitativas pueden integrarse de manera efectiva en un algoritmo de localización de fuentes químicas. Los resultados obtenidos (simulaciones realistas y datos reales) muestran que el algoritmo desarrollado durante la tesis puede funcionar especialmente bien en situaciones en las que la potencia de emisión de la fuente a detectar sea débil.
Dib, Omar. "Implementation of a physio-chemical approach coupled with a data fingerprinting methodology for the characterization of the Lebanese extra-virgin olive oils." Thesis, université Paris-Saclay, 2021. http://www.theses.fr/2021UPASB004.
Повний текст джерелаOlive oil is a vital component of the Mediterranean diet, hence Lebanese, owed to its well-known economic and nutritional value. Several environmental, agricultural, and technological factors play an essential role in defining olive oil's quality. In Lebanon, preliminary studies on the quality of extra virgin olive oil have shown that certain quality criteria exceed the International Olive Council's (IOC) standards. However, the causes of such non-conformities have not been clearly identified. Accordingly, ninety-six olive oil samples have been harvested from two seasons, processed using different extraction methods, and collected from eight locations (Akkar, Chouf, Hasbaya, Koura, Tyr, Nabatiyeh, Zgharta, and Hermel). These locations are identified by the European Union to have potentials for Protected Geographical Indications (PGI). In this perspective, and to meet the European framework's requirements, the analyzed oil will be subjected to conventional chemical analysis as suggested by the IOC and to ultra-fast analysis using 3D-front face spectroscopy (3D-FFFS) and ultra-flash gas chromatography (Ultra-FGC).A correlation between the fatty acid profile and the pedoclimatic conditions of the main olive growing regions in Lebanon was noticed. Three main pedoclimatic conditions, altitude, temperature, and relative humidity, were the major influencers and the reason for the distinctive fatty acid profile of the Lebanese olive oil. Lebanese areas with high altitudes, low average temperature, and low relative humidity have high oleic acid content. As for areas with lower altitudes, higher average temperature, and higher relative humidity, the fatty acid profile was characterized by linoleic, linolenic, palmitoleic, and palmitic acids. In addition to the environmental factors, agricultural ones, particularly the harvest date, had affected the chemical constituents of olive oil. The results obtained showed that the harvest date strongly influenced acidity and total polyphenols. A change in the fatty acid profile characterized by a higher linoleic and lower oleic content, an increase in ∆^7-stigmastenol exceeding the limit set by the IOC standards, and a dominating off-flavor compound (ethanol) was noticed as a result of delaying the harvesting time. Besides, two technological factors, particularly improper fruit storage, and bad hygienic practices, significantly affected olive oil’s quality parameters and fatty acid content.3D-FFFS and Ultra-FGC were used in-line with conventional analysis, and they both showed an undeniable performance. 3D-FFFS coupled with chemometric tools, namely multiple linear regression (MLR) applied on parallel factor (PARAFAC) scores and partial least squares (PLS), was tested on inconsistent qualities of olive oil samples to predict quality parameters. Twenty-two MLR models were generated, the majority of which showed a good correlation coefficient (R>0.7). A second model using PLS on the unfolded emission-excitation matrices was also conducted to improve the regression and assess whether the variability can be handled successfully. However, similar results, with a slight improvement over the MLR model, were obtained. As for Ultra Flash GC, it made it possible to identify, in only a few minutes (< 2 min), ethanol, (E,E)-2,4-decadienal (organoleptic defect), and 1-hexanol (fruity, grassy) as the main volatiles characterizing the Soury variety.This study offers the potential to disseminate an analytical control plan that links environmental aspects in Lebanon and cultivation/harvesting techniques to olive oil's resulting physicochemical characteristics. Such a matrix incorporating rapid analysis techniques will facilitate governance over the end product's final quality and, subsequently, conformity to IOC standards. Furthermore, this work will set the ground through a detailed identification fiche for PGI
ANESI, Andrea. "Mass spectrometry techniques and chemometric approaches for the study of grape metabolome." Doctoral thesis, 2012. http://hdl.handle.net/11562/392731.
Повний текст джерелаGrape vine is one of the most important fruit crop in the world. Numerous grape varieties are grown worldwide for production of wine or food. Grape berries contain a large and diverse range of primary and secondary metabolites, that are important for wine quality and sensory attributes but also for their positive impact on human health. This thesis is dedicated to the study of grape metabolomes through LC-MS, GC-MS and advanced multivariate data analysis. This thesis is divided into three main chapters, covering different aspects of grape metabolomics. Chapter 1 is a review on grape metabolomics. The first part is dedicated to the importance of grape and its metabolites, with particular regards on the effect on wine sensory properties. The second part covers the different analytical platforms used in grape metabolomics and the importance of multivariate data analysis, particularly with newly developed OPLS/O2PLS. In the third part, some recent trends in grape metabolomics are described. Chapter 2 is dedicated to the development of new methodological approaches to study terroir, or the effect of environmental and viticultural features on grape and wine quality. Secondary non-volatile and volatile metabolites were extracted from berries of cv. Corvina harvested in three vintages (2006, 2007 and 2008) in eleven vineyards located in the area surrounding Verona. Two different approaches were proposed, based on multivariate data analysis. First, a preliminary unsupervised analysis allowed highlighting the strong effect of climate on cv. Corvina metabolome. The most correct approach resulted to be the analysis of the three vintages together. Several multivariate models were built using vineyard features and validated to avoid over fitting. Few models, beside the one of vintages, gave information in terms of metabolites. Particularly, two vineyards located in Lake Garda area and with by loam soils were characterized by high contents of benzene derivative volatiles compared to other vineyards. A second and completely unsupervised approach was used to reduce the variability in the metabolome that was due to climate, so that to study terroir as the set of metabolites that did not show a year-dependent variation. The analysis of LC-MS dataset revealed that each single vineyard was characterized by specific levels of secondary metabolites. When analysing the GC-MS matrix, two clusters of producers where obtained but no single feature of terroir considered in this survey could explain the grouping. Specific terroir features were suggested to affect the metabolome composition, but such features were mainly correlated to very subtle variation of large sets of metabolites rather than to sharp variation of few metabolites. Chapter 3 is dedicated to the study of the metabolic responses of six different grape varieties (Cabernet Sauvignon, Corvina, Merlot, Oseleta, Sangiovese and Shiraz) during postharvest withering process. A first approach was based on the analysis of raw data and allowed the discrimination of the six varieties by their metabolomes. The second approach was based on the analysis of data matrix normalized for the weight loss, to compensate the concentration effect due to water loss. Modulation of anthocyanin, flavonoid, flavan-3-ol and procyanidin, hydroxybenzoic and hydroxycinnamic acid classes were mainly due to concentration effect and degradation. Compounds belonging to class of stilbenes and viniferins were highly induced during postharvest withering in all the varieties but Cabernet Sauvignon and might act as defence mechanism during stress conditions. The last part of Chapter 3 is focused on the different modulation of volatile compounds in Corvina and Shiraz varieties. Sesquiterpenes, a class of terpene molecules, were highly induced in Corvina during withering and may have a role in stress response and signalling.
Jabeen, Rukhshinda. "Automated Baseline Estimation for Analytical Signals." 2013. http://hdl.handle.net/10222/37440.
Повний текст джерелаMunawar, Agus Arip. "Multivariate analysis and artificial neural network approaches of near infrared spectroscopic data for non-destructive quality attributes prediction of Mango (Mangifera indica L.)." Doctoral thesis, 2014. http://hdl.handle.net/11858/00-1735-0000-0022-5E52-8.
Повний текст джерела