The extraction of bitumen from the cretaceous oil sands ore within the Athabasca Oil Sands Region (AOSR) in Northern Alberta has generated over 1.18 trillion liters of by product in the form of Fluid Fine Tailings (FFT) and Oil Sands Process Water (OSPW)3. A reclamation strategy being investigated is water capped tailings technology (WCTT), that involves the development of Pit Lakes (PLs) by sequestering FFT below a water cap composed of both OSPW and fresh water to steadily densify these tailings over time4. A challenge that may impede this reclamation strategy is that as FFT densifies porewater containing oxygen consuming constituents (OCC) derived from anaerobic microbial degradation of labile petroleum hydrocarbons, such as gases (e.g. H2S, CH4), dissolved organic carbon (DOC) and dissolved ions (e.g. NH4+, HS-, and Fe2+), have the potential to be mobilized into to the overlying water cap. This dissertation is focused on developing an optimized comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC/TOFMS) methodology for analyzing the spatial distribution for a subset of identifiable solvent extractable PHCs species from FFT within Base Mine Lake (BML) the first full-scale demonstration of PL technology. The chemical “fingerprint” constructed from the concentration of each identified PHC isomer at a given depth and cosine theta (cos-Ɵ) similarity metric suggested the contribution of a singular source of PHCs within BML. Although a similar source fingerprint persisted throughout the study site, the spatial distribution for the isomers identified suggested differences in PHC input contributions across the FFT sampling platforms with the largest variation in concentration being attributed to the labile low molecular weight n-alkanes (C11 – C13) and postulated biomarker, drimane. These low molecular weight compounds, with the exception of drimane, are suspected components of residual naphtha, and the large variabilities in concentration are suggestive that these species may be linked with fluctuating inputs and/or sorption of naphtha to the organic phase of the FFT. Equally possible, the pronounced variability in the low molecular weight n-alkanes concentrations / Thesis / Master of Science (MSc)

Simplex algorithms have been used to optimize for size, number and morphology of lysozyme and apoferritin crystals. This approach requires fewer experiments than the single-factor-at-a-time method or factorial designs and will be useful in conserving materials on the International Space Station. The simplex method has the possible advantage that it conserves on materials by reducing the number of experiments required to optimize a crystallization system. The process is iterative and exploratory and should allow optimum microgravity conditions to be determined which might very well be different from the optimum conditions on Earth. Because the simplex method uses simple mathematical operations to calculate the next set of crystallization conditions it will be easier for crystal growers to implement than factorial designs. Factorial experiments are based on varying all factors simultaneously at a limited number of factor levels. This results in a model that is used to determine the influence of each factor and their interactions. Factorial design experiments are especially useful at the beginning of an experimental study and as a screening tool to investigate a large number of factors. The simplex method is an optimization method which is model-independent and requires no fitting of models to data. Also, when applied to protein crystal growth the simplex method does not rely on an absolute quality score. Instead, with each iteration a comparison is made to the last experiment and the results are assigned as being "better or worse". In this study, commercially obtained apoferritin was purified from 65% monomeric apoferritin to 92% monomeric apoferritin by size exclusion chromatography. Simplex optimization found the best apoferritin crystals were obtained at 15 mg/ml apoferritin, 2.0% CdSO4, 25°C using the hanging drop vapor diffusion method of crystallization and at 24 mg/ml apoferritin, 1.5% CdSO4, 25°C using the containerless crystallization method. For lysozyme, the simplex method found the best crystals at 19 mg/ml lysozyme, 7.0% (w/v) NaCl, pH 4.0, 25°C using the hanging drop vapor diffusion method of crystallization. For both proteins, the optimum conditions were found with less than ten experiments using very little protein. Finally, we report that the factors to be considered in the successful application of this method to crystallization are the number of variables to be studied, the initial conditions, step size and analysis of crystal quality.

Polycyclic aromatic hydrocarbons (PAH) are important environmental pollutants generally formed during incomplete combustion of organic matter containing carbon and hydrogen. Introduced into the human body by adsorption through the skin, ingestion or inhalation, the biotransformation processes of PAH lead to the formation of multiple metabolites. Due to the short elimination lifetime from the body, the quantitative determination of monohydroxy-PAH (OH-PAH) in urine samples provides accurate information on recent exposure to environmental PAH. Urine analysis of OH-PAH with established methodology relies on sample clean-up and pre-concentration followed by chromatographic separation and quantification. Although chromatographic techniques provide reliable results in the analysis of OH-PAH, their experimental procedures are time consuming and expensive. Additional problems arise when laboratory procedures are scaled up to handle thousands of samples under mass screening conditions. Under the prospective of a sustainable environment, the large usage of organic solvents is one of the main limitations of current chromatographic methodology. It is within this context that new analytical approaches based on easy-to-use and cost-effective methodology become extremely relevant. This dissertation focuses on the development of screening methodology for the routine analysis of PAH metabolites in numerous samples. It explores the room-temperature fluorescence properties of six metabolites originating from parent PAH included in the Environmental Protection Agency priority pollutants list. 1- hydroxyfluorene, 1-hydroxypyrene, 6-hydroxychrysene, 9-hydroxyphenanthrene, 3- hydroxybenzo[a]pyrene and 4-hydroxybenzo[a]pyrene are used as model biomarkers to investigate the analytical potential of new methods based on solid-phase extraction (SPE) and iii room-temperature fluorescence (RTF) spectroscopy. Quantitative determination of metabolites is carried out either in the eluent extract[1, 2] or on the surface of extraction membranes[3, 4] . The direct determination – i.e., no chromatographic separation - of the six metabolites is based on the collection of excitation-emission matrices and synchronous fluorescence spectra.

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Tesis por compendio / La industria alimentaria, concretamente el sector poscosecha, necesita innovar en sus procesos productivos, optimizando los mismos para rentabilizar sus actividades, garantizando productos de calidad capaces de satisfacer las necesidades de los consumidores. La presente tesis doctoral se centra en evaluar el potencial de la espectroscopia VIS-NIR para la caracterización e inspección de la calidad de la fruta tanto fuera de línea como a tiempo real en procesos automatizados. En un primer lugar, la viabilidad de la técnica se estudió a nivel de laboratorio en estado estático (off-line), con el fin de conocer y optimizar las condiciones de medición. Posteriormente, se evaluó la calidad interna y externa de diferentes tipos de frutas como son caqui, nectarina y mango. En una segunda etapa, se llevó a cabo una automatización de los procesos de inspección mediante el desarrollo de nuevos prototipos in-line. Para este propósito, y con el objetivo de completar y corroborar los resultados obtenidos de manera estática, se estudió la integración de dos sondas VIS-NIR en una garra robótica capaz de manipular mangos. Finalmente, se estudió la integración de una sonda VIS-NIR a una cinta transportadora. Los resultados obtenidos a nivel estático han demostrado que la espectroscopia VIS-NIR es un método no destructivo muy prometedor para predecir la astringencia en caqui. Así mismo, ha demostrado ser una adecuada herramienta para clasificar al 100% entre variedades de nectarinas como "Big Top" y "Diamond Ray" con una apariencia externa e interna muy similar, pero con diferentes propiedades organolépticas. De manera similar, fue posible clasificar al 100% variedades como "Big Top" y "Magique" de apariencia externa y composición similar pero distinto color de pulpa., y además se desarrolló un índice de calidad interna (IQI) para evaluar la calidad de las nectarinas. Por lo que respecta a los trabajos off-line realizados con mangos de la variedad "Osteen", fue posible predecir su calidad interna mediante los índices de madurez (RPI) y de calidad (IQI) con un gran rendimiento. A su vez, los ensayos experimentales efectuados con estos mismos mangos bajo la manipulación no destructiva de una garra robótica, demostraron que los mejores modelos eran capaces de predecir tanto la firmeza mecánica, el contenido en sólidos solubles, la luminosidad de la pulpa, así como el índice RPI de las muestras en base a la información obtenida por los acelerómetros instalados en los dedos de la garra robótica. En cuanto a los ensayos realizados de manera in-line, el primer prototipo desarrollado se basó en la integración de dos sondas VIS-NIR en una garra robótica dispuesta con dos acelerómetros. El sistema desarrollado permitió alcanzar una buena estimación de la calidad del mango a través del índice RPI fusionando la información tanto de los espectros VIS-NIR como del impacto no destructivo de los acelerómetros. De este modo quedó demostrado que era posible obtener una predicción similar trabajando de forma in-line como trabajando de manera off-line para la predicción del mismo índice de calidad en mangos. El segundo prototipo in-line desarrollado se basa en la integración de una sonda VIS-NIR en una cinta transportadora para la identificación de distintas variedades y orígenes de manzanas. El prototipo desarrollado permitió registrar resultados de clasificación tan buenos como los efectuados de manera off-line con, por ejemplo, nectarina. De este modo, se puede concluir que la espectroscopia VIS-NIR permite monitorear la calidad y clasificar fruta poscosecha tanto en modo off-line como in-line. Los nuevos prototipos desarrollados aportan claras ventajas respecto a los procesos tradicionales realizados a mano, como son la reducción del tiempo de inspección, la disminución de la cantidad de residuos generados y la posibilidad de inspeccionar toda la producción, obteniendo así un análisis más estandariz / The food industry, concretely the post-harvest sector, needs to innovate in their production processes, optimizing them to make their activities profitable, guaranteeing quality products capable of satisfying the needs of consumers. The present doctoral thesis focuses on evaluating the potential of visible and near infrared spectroscopy (VIS-NIR) for the characterization and inspection of fruit quality both off-line and in real time in automated processes. Firstly, the viability of the technique was studied at the laboratory level in a static mode (off-line), in order to know and optimise the measurement conditions. Subsequently, the internal and external quality of different types of fruits such as persimmon, nectarine and mango were evaluated. Secondly, an automation of the inspection processes was carried out through the development of new in-line prototypes. For this purpose, and with the aim of completing and corroborating the results obtained in a static mode, the integration of two VIS-NIR probes in a robotic gripper capable of manipulating mangoes was studied. Finally, the integration of a VIS-NIR probe to a conveyor belt was studied as an in-line monitoring tool on the inspection process of different apple varieties. The results obtained in static mode have shown that VIS-NIR spectroscopy is a very promising non-destructive method to predict the astringency in persimmon. Likewise, it has demonstrated to be an adequate tool to classify 100% between nectarine varieties such as 'Big Top' and 'Diamond Ray' with very similar external and internal appearance, but with different organoleptic properties. Similarly, it was possible to classify 100% varieties such as 'Big Top' and 'Magique' with external appearance and similar composition but different pulp colour. An internal quality index (IQI) was developed to evaluate the quality of nectarines, which can be predicted through VIS-NIR spectroscopy. Regarding the off-line work carried out with mangoes of 'Osteen' variety, it was possible to predict its internal quality through the indexes of maturity (RPI) and quality (IQI) with a high performance. Moreover, the experimental tests carried out with these same mangoes under the non-destructive manipulation of a robotic gripper, showed that the best models were able to predict both the mechanical firmness, the soluble solids content, the brightness of the pulp, as well as the RPI index of the samples based on the information obtained by the accelerometers installed on the fingers of the robotic gripper. Regarding the tests carried out in an in-line mode, the first developed prototype was based on the integration of two VIS-NIR probes in a robotic gripper fitted with two accelerometers. The developed system allowed reaching a good estimation of mango quality through the RPI index. In this way, it was demonstrated that it was possible to obtain a similar prediction working in-line as off-line mode for the prediction of the same quality index in mangoes. The second developed in-line prototype is based on the integration of a VIS-NIR probe in a conveyor belt for the identification of different varieties and origins of apples, achieving a success rate of 98% with the system. The developed prototype allowed to register classification results as good as those carried out off-line with, for example, nectarine. In this way, it can be concluded that VIS-NIR spectroscopy allows monitoring the quality and classifying post-harvest fruit in both off-line and in-line mode, being a tool that allows improving and guaranteeing the correct quality and food safety. The new developed prototypes provide clear advantages over the traditional processes performed by hand, such as the reduction of inspection time, the reduction of the amount of waste generated by destructive quality analysis and the possibility of inspecting full production, obtaining a more standardised analysis of the quality of the products. / La indústria alimentària, concretament el sector postcollita, necessita innovar en els seus processos productius, optimitzant els mateixos per a rendibilitzar les seues activitats, garantint productes de qualitat capaços de satisfer les necessitats dels consumidors. La present tesi doctoral es centra en avaluar el potencial de l'espectroscòpia visible i infraroig pròxim (VIS-NIR) per a la caracterització i la inspecció de la qualitat de la fruita tant fora de línia com a temps real en processos automatitzats. En un primer lloc, la viabilitat de la tècnica es va estudiar a nivell de laboratori en estat estàtic (off-line), a fi de conéixer i optimitzar les condicions de mesurament. Posteriorment, es va avaluar la qualitat interna i externa de diferents tipus de fruites com són caqui, nectarina i mango. En una segona etapa, es va dur a terme una automatització dels processos d'inspecció per mitjà del desenvolupament de nous prototips in-line. Per aquest propòsit, i amb l'objectiu de completar i corroborar els resultats obtinguts de manera estàtica, es va estudiar la integració de dos sondes VIS-NIR en una garra robòtica capaç de manipular. Finalment, es va estudiar la integració d'una sonda VIS-NIR a una cinta transportadora. Els resultats obtinguts a nivell estàtic han demostrat que l'espectroscòpia VIS-NIR és un mètode no destructiu molt prometedor per a predir l'astringència en caqui. Així mateix, ha demostrat ser una adequada ferramenta per a classificar al 100% entre varietats de nectarines com "Big Top" i "Diamond Ray" amb una aparença externa i interna molt semblant, però amb diferents propietats organolèptiques. De manera semblant, va ser possible classificar al 100% varietats com "Big Top" i "Magique" d'aparença externa i composició semblant però distint color de polpa. Es va desenvolupar un índex de qualitat interna (IQI) per avaluar la qualitat de les nectarines. Pel que fa als treballs off-line realitzats amb mangos de la varietat "Osteen" va ser possible predir la seua qualitat interna mitjançant els índexs de maduresa (RPI) i de qualitat (IQI) amb un gran rendiment. Al mateix temps, els assajos experimentals efectuats amb estos mateixos mangos baix la manipulació no destructiva d'una garra robòtica, van demostrar que els millors models eren capaços de predir tant la fermesa mecánica, el contingut en sòlids solubles, la lluminositat de la polpa, així com l'índex RPI de les mostres basant-se en l'informació obtinguda pels acceleròmetres instal¿lats en els dits de la garra robòtica. En quant als assajos realitzats de manera in-line, el primer prototip desenvolupat es va basar en la integració de dos sondes VIS-NIR en una garra robòtica disposada amb dos acceleròmetres. El sistema desenvolupat va permetre aconseguir una bona estimació de la qualitat del mango a través de l'índex RPI fusionant l'informació tant dels espectres VIS-NIR com de l'impacte no destructiu dels acceleròmetres. D'esta manera va quedar demostrat que era possible obtindre una predicció semblant treballant de forma in-line com off-line per a la predicció del mateix índex de qualitat en mangos. El segon prototip in-line desenvolupat es va basar en la integració d'una sonda VIS-NIR en una cinta transportadora per a l'identificació de distintes varietats i orígens de pomes. El prototip desenvolupat va permetre registrar resultats de classificació tan bons com els efectuats de manera off-line. D'aquesta manera, es pot concloure que l'espectroscòpia VIS-NIR permet monitorar la qualitat i classificar fruita postcollita tant en mode off-line com in-line. Els nous prototips desenvolupats aporten clars avantatges respecte als processos tradicionals realitzats a mà, com són la reducció del temps d'inspecció, la disminució de la quantitat de residus generats pels anàlisis destructives de qualitat i la possibilitat d'inspeccionar tota la producció, obtenint així un anàlisi més estandarditz / Cortés López, V. (2018). Innovations in non-destructive techniques for fruit quality control applied to manipulation and inspection lines [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/110969 / Compendio

The Anthropocene epoch in which we are currently living, also known as the Holocene, has brought about unprecedented losses in planet Earth’s biodiversity. Numerous extirpations of floral and faunal species have been influenced by human encroachment and more specifically, the exploitation of such species and the respective habitats in which they reside. It is this notion that has propelled many scientists to take up intellectual arms in an effort to protect these invaluable resources. The purpose of this research was to develop technologies to measure and evaluate various variables that influence animal physiology, specifically in amphibians who represent the most threatened class of all animal taxa. Species-specific knowledge including life history and an understanding of evolutionary traits are often needed to effectively guide the management decisions surrounding any given animal population. Specific objectives of this project were to develop non-invasive methods, such as hormone monitoring, machine learning-aided ultrasonography, and near-infrared spectroscopy (NIRS), to assess vital physiological traits, such as biological sex, reproductive status, and chytrid fungus pathogen detection in threatened amphibian species. The novel technologies developed and applied in amphibians here may provide insights for addressing conservation related questions in other animal as well as plant species. Additionally, automation of physiological monitoring techniques through the use of machine learning methods reduces barrier to entry and enables these technologies to be operated by a larger practitioner base. This research also serves to advance methods surrounding chemometric analyses as it pertains to the discipline of wildlife spectroscopy, where large multivariate datasets require data manipulation strategies to produce robust prediction models for the physiological trait of interest for qualitative or quantitative assessment. To that end, a multi-model framework is provided for optimizing predictive outcomes to address questions relating to wildlife management and conservation initiatives.

Raman spectroscopy records the inelastic scattering of photons originating from striking a sample with monochromatic light. Inelastic, or Raman, scattered photons shift in wavelength due to excitation of the vibrational modes of molecules struck by the incident light. The Raman scattered photons are representative of all of the covalent bonds contained within a sample. Raman spectra taken of biological systems such as proteins, bacterial colonies, and liquid waste, are difficult to interpret due to the complexity of their covalent bond landscape and mixtures of molecules in highly variable concentrations. Rather than deconstructing Raman spectra to attempt assignment of specific bonds and functional groups to wavenumber peaks, here we have developed a chemometric analysis pipeline for quantifying the similarities and differences among a set of Raman spectra. This quantification aids in both classification of samples, and in measuring how samples change over time. The chemometric approach for interpretation of Raman spectra was made freely available in a user-friendly format via a MATLAB add-on called the Raman Data Analysis (RDA) Toolbox. Demonstrations of the RDA Toolbox functionalities on Raman spectra taken of various common biological systems are included, such as determination of protein concentration and monitoring bacterial culture growth. The RDA Toolbox and Raman spectroscopy are also used to initiate research in novel areas. Fast and accurate evaluation of enzyme specific activity is required for engineering enzymes, and results of Raman assays, evaluated in the RDA Toolbox, are successfully correlated to absorbance activity assays of an enzyme WT and mutant library. Further development of this research could alleviate the bottleneck of screening mutant libraries in enzyme engineering projects. The Toolbox is then used in a distinctly different application for evaluating urine and spent dialysate samples from patients with end stage renal disease. Categorization between samples from healthy volunteers and patients is accomplished with close to 100% accuracy, and evidence indicating that Raman spectroscopy can serve as an early diagnostic tool for infections of the peritoneal membrane is presented. / PHD / Raman spectroscopy, unlike other forms of spectroscopy, provides a complete picture of the chemical make-up of a sample. However, Raman spectra of biological samples are very difficult to interpret due to the complex mixture of molecules in living systems. Rather than trying to discern what specific molecules are in a sample, we have developed a method for measuring the similarities and differences among a set of Raman spectra. These measurements help us classify samples and monitor how samples change over time. We made a MATLAB add-on called the Raman Data Analysis (RDA) Toolbox to automate our method for interpreting Raman spectra, and made it available online for anyone to download and use. Raman spectroscopy and the RDA Toolbox are used to measure enzyme reaction speed, and the results compare favorably with a traditional method for measuring enzyme reaction speed. The final part of this dissertation focuses on using Raman spectroscopy and the RDA Toolbox to evaluate the health of patients with end stage renal disease (ESRD) by scanning urine and spent dialysate samples to detect failing kidney function or the onset of infection.

No / The impregnation of items of clothing with drugs of abuse that are then smuggled through airports and ports of entry is a growing problem for law enforcement. This work describes the application of portable Raman spectroscopic techniques for the analysis of a range of natural and artificial fibre items of clothing impregnated with drugs of abuse. Textile pieces were soaked with the solutions of the drugs then left overnight to dry prior to spectroscopic examination. The feasibility of detection of the characteristic Raman spectral bands in the presence of background matrix signals is demonstrated, even for dyed clothing. Definitive evidence for contamination of the items of clothing concerned can be acquired within 20-25 s, without any form of sample pre-treatment or extraction being necessary. The feasibility of automatic spectral recognition of such illicit materials by Raman spectroscopy has been investigated by searching a database stored on the spectrometer computer and the use of principal component analysis. Copyright (c) 2014 John Wiley & Sons, Ltd.