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Three new quantitative Fourier transform infrared (FTIR) spectroscopic methods were developed for the analysis of edible oils: two procedures to measure free fatty acids (FFA) and one to measure moisture (H2O), the latter two methods ultimately being automated and implemented on an auto-sampler equipped FTIR spectrometer. The methods developed for FFA determination both convert FFAs to their carboxylate salts by means of acid/base reaction without causing oil saponification, one approach using 1-propanol, an oil-miscible solvent, and the other using methanol, an oil-immiscible solvent into which the FFA salts are extracted. The first method involves splitting oil samples into two halves, with one half treated with propanol containing base and the other half with propanol only. The spectra of each half is collected and a differential spectrum obtained, from which quantization is performed. The methanol procedure simply involves extracting FFA into methanol containing a weak base and quantitating the FFA salts produced. Both FFA methods determine the FFA content by measuring the v (COO-) absorbance at ∼1570 cm-1 relative to a reference wavelength of 1820 cm-1 from a differential spectrum relative to the solvent, the extraction procedure being superior in terms of both speed and sensitivity, being able to measure FFA levels down to ∼0.001%. The method developed for moisture determination involves extracting water in edible oils into dry acetonitrile and then quantitating it by measuring the absorbance of the OH stretching band (3629 cm-1) and/or the HOH bending band (1631 cm -1). All three methods were validated by standard addition experiments, evaluated for potential interferences, and, in the case of FFA determination, compared to the performance of AOCS official methods. The results indicated that the extraction-based procedures were superior to conventional wet chemical methods in both sensitivity and reproducibility. The FFA and H2O extraction procedures were subsequently automated by connecting an auto-sampler to the FTIR spectrometer and developing procedures and software algorithms to enable the analysis of up to 100 samples/h. The methods developed and implemented are a substantive improvement over conventional methods for the analysis of FFA and H2O in edible oils and provide a means by which QC and process laboratories can analyze large volumes of edible oils for these two important parameters.

We present the observations, reduction and preliminary analysis of a sample of 45 mid-to-high redshift galaxy clusters imaged with the Spitzer Space Telescope's MIPS camera at 24 ~m and selected from the Red Sequence Cluster Survey. The purpose of the data set is motivated by a broad review of studies into the evolutionary trends of galaxy clusters and their constituent galaxy populations, focusing specifically on recent results that indicate clusters are environmental drivers of dusty starburst and active galactic nuclei activity. To accommodate the large amount of data in hand, we have constructed an extensive data reduction pipeline for the MIPS data and describe its development and output in detail. Using the resulting catalogues for introductory analysis, we find strong evidence for an excess luminous infrared galaxy population in galaxy clusters at high redshift and discuss the implications of this discovery in terms of cluster evolution and motivate future work.

A mid-infrared chalcogenide fiber optic probe was employed to develop a Fourier transform infrared spectroscopy-based partial-least-squares (PLS) calibration model for the quantitative analysis of sucrose, glucose, fructose, maltose, total sugar and water content in chocolate syrup. Based on the comparison of the pure component and correlation spectra extracted from chocolate syrup and aqueous sugar solutions based models, it was determined that the tightness of the concentration ranges and the ratios of the sugars in the chocolate syrup samples did not allow to draw adequate information to build a robust PLS calibration model. PLS regression models developed using infrared spectra of chocolate syrup calibration standards prepared by addition of sugar solutions to increase the concentration range did not yield conclusive results. A different approach used for standard preparation consisted of diluting chocolate syrup samples to different degrees. This new method provided an increased concentration range for the sugars but maintained an almost constant sugar to sugar ratios. The PLS models based on these new calibration standards yielded high calibration correlation coefficients and low errors on the external validation. Accuracy, repeatability, long-term stability and ruggedness were tested and the results demonstrated that the calibration models were robust and had a better repeatability than the reference high-performance liquid chromatography method. The fact that the calibration model was developed using standards having very similar sugar profiles precluded its use for the analysis of chocolate syrup samples of different formulations. The resulting formulation-specific PLS regression model required a preclassification step to ensure that the model is applied to the appropriate sample type. A probabilistic neural network (PNN) model was developed to fulfill the preclassification requirement. PNN yielded excellent classification results. The modeling uncovered

The application of visible/near-infrared hyper-spectral analysis to monitor the quality of frying oil and fried breaded chicken nuggets was investigated. / Partial least squares (PLS) calibration models were developed to predict the acid value, total polar components and viscosity of heated oils with different ratios of hydrogenation. Coefficient of determination (R2) and root mean square error (RMSE) were calculated to assess the performance of each model. Results of the study demonstrated good prediction ability of the calibration models for the quality parameters with R2 values of over 0.92. / The second study was based on developing calibration models for prediction of moisture and fat contents of fried breaded chicken nuggets with different levels of moisture and fat contents. Performing the same procedure for evaluation of the PLS calibration models, results of the study demonstrated that moisture and fat contents of fried breaded chicken nuggets could be predicted with R2 values of 0.92.

The application of infrared imaging employing focal plane array Fourier transform infrared (FPA-FTIR) instrumentation for the identification of bacteria was investigated. FPA-FTIR spectroscopy was shown to provide new opportunities for bacteria identification with unprecedented reliability and throughput by allowing 102--103 FTIR spectra to be acquired simultaneously from surface areas of 90 x 90 to 200 x 200 mum with a spatial resolution of ∼6 mum. The combination of data redundancy and spatial resolution afforded by infrared imaging made it possible to acquire highly reproducible spectra from bacterial films. A protocol for enhancing the reliability of bacteria identification by transmission-mode FPA-FTIR spectroscopy was developed by optimizing spectral acquisition parameters, spectral processing and data analysis; using the differentiation of two Campylobacter species as a test case. The results for this test case were compared with those obtained from three alternate FTIR spectral acquisition modes. The optimized protocol was employed for the generation of a spectral database of foodborne bacteria, containing over 1,000,000 spectra acquired by infrared imaging of 36 species from 19 genera. The development of a modular hierarchical clustering (MHC) model, in combination with the use of a region selection algorithm, allowed all species in the database to be differentiated from each other down to the species level based on differences in their infrared absorption profiles. A validation study involving the identification of well-characterized isolates by comparison of their spectra to those in the database demonstrated the robustness of the MHC model. In a further study employing 44 strains of Clostridium botulinum, the discriminatory power of FPA-FTIR spectroscopy was compared with that of pulsed-field gel electrophoresis, and the region selection algorithm was applied to identify growth medium-independent spectral regions that allowed for the differentiation of Group I and Group II C. botulinum strains in two blind validation studies. The research carried out also demonstrated the high-throughput potential of bacteria identification by infrared imaging when combined with the use of a microarray system for sample deposition. Overall, the novel FPA-FTIR spectroscopy-based bacteria identification protocol developed in this work provides a rapid-response and reagent-free technique suitable for routine use in both food and clinical microbiology laboratories.

Globular proteins are important ingredients in many food formulations because of their nutritional value and their various functional properties such as gel formation. Proteins form gels by polymerization into a three-dimensional matrix. The rheological properties of the resulting viscoelastic solids can be obtained by Instron measurements. In the present work, gels were obtained by heating solutions of bovine serum albumin (BSA) in D$ sb2$O and egg albumin in H$ sb2$O under different conditions (i.e., pH, salt concentration, protein concentration, time of heating and temperature), and their gel strengths were measured by a compression test (Universal Testing Machine LRX). The Fourier transform infrared (FTIR) spectra of the same gel samples were recorded in order to investigate the changes in protein structure at the molecular level accompanying gel formation. Intermolecular $ beta$-sheet formation was found to increase as gel formation progresses at the expense of intramolecular $ beta$-sheet and $ alpha$-helix structures. For BSA, maximum gel strength was obtained around pH 7. The addition of salt had little effect on the gel strength while increase in protein concentration, time of heating and temperature increased the gel strength. The rate of denaturation of BSA and ovalbumin and of mixtures of these proteins in the ratios 9:1, 1:1, and 1:9 was also investigated by measuring the peak height of an aggregation band at 1618 cm$ sp{-1}$; some inhibitory effects of BSA on ovalbumin aggregation were observed. Correlations between the measured gel strengths and the amide I band profile in the FTIR spectra were examined using partial-least-squares (PLS) regression. These studies reveal that gel strengths of a particular protein gel could be adequately predicted from their infrared spectra without the need to carry out the rheological compression measurements.

This work describes an investigation of the development of a Fourier Transform Infrared (FTIR) spectroscopic method for the determination of Solid Fat Index (SFI) of fats as a possible replacement of the traditional dilatometric procedure. The initial approach considered was the use of an existing FTIR analytical package which was designed to measure iodine value (IV), saponification number (SN), and cis and trans content. It was hypothesized that these measures could be related to SFI using multiple linear regression (MLR), thereby allowing the existing analytical package to simultaneously make SFI measures. It was found that there was a strong relationship between SN/cis/trans measurements and SFI, especially in sequentially hydrogenated oils. The MLR relationships, however, did not reproduce the dilatometric SFI values with sufficient accuracy in the general case, and this approach had to be abandoned. Subsequently, a partial least squares (PLS) calibration approach was investigated, relating the dilatometric SFI data directly to the spectral characteristics of the melted fats. It was found that suitable PLS calibrations could be developed for soybean and Canola oils. Based on these results, an FTIR system was programmed to determine SFI and the performance of the system validated using pre-analyzed "unknowns". It was shown that the SFI of either soybean or Canola oils could be determined to within $ pm$ 1.0 SFI. As configured, the FTIR system is capable of determining the SFI of a neat and clear, melted fat sample at 80$ sp circ$C in less than two minutes, providing four SFI values, representing the solids content at 50, 70, 80 and 92$ sp circ$F. In contrast to the standard dilatometric method, which takes over two hours to carry out, the FTIR approach provides a rapid means of determining SFI, the technique being suitable for routine quality control applications in the fats and oils industry.

Staphylococci strains are among the most widespread multidrug-resistant nosocomial pathogens in Canada. Rapid and accurate identification and epidemiological typing of methicillin-resistant S. aureus (MRSA) and its discrimination from coagulase-negative staphylococci (CNS) and glycopeptide-intermediate S. aureus (GISA) are crucial for appropriate therapy and for monitoring and limiting intra- and inter-hospital spread of epidemic MRSA strains. Although pulsed-field gel electrophoresis and polymerase chain reaction methods for the identification of MRSA are reliable, they are technically demanding, time-consuming and inappropriate for routine clinical diagnosis. Moreover, no reliable method exists for discrimination of epidemic MRSA from sporadic MRSA and from GISA strains. The objective of the research described in this thesis was to investigate whether Fourier transform infrared (FTIR) spectroscopy could be used to distinguish MRSA from methicillin-susceptible S. aureus, borderline oxacillin-resistant S. aureus (BORSA), CNS, including methicillin-resistant CNS, and GISA. The application of FTIR spectroscopy for epidemiological typing of Canadian epidemic MRSA (CMRSA) strains as well as their discrimination from sporadic MRSA was also assessed. FTIR spectra were recorded from intact stationary-phase cells grown on Universal Medium (UM™) and deposited and dried on a ZnSe optical window, normalized, and converted to first-derivative spectra. Various chemometric approaches were employed to cluster the different phenotypes of staphylococci species and to subtype five CMRSA strains based on the similarity of their infrared spectral fingerprints in narrow spectral regions selected by visual inspection and by employing a singularvalue decomposition (SVD) algorithm. Pairwise separation of MRSA from MSSA, BORSA, CNS, MRCNS, and GISA was accomplished by using principal component analysis (PCA), self-organizing maps (SOM), and the K-nearest neighbors (KNN) algorithm. These chemometric techniques were also successfully employed for epidemiological typing of the five CMRSA strains and their discrimination from sporadic MRSA strains using a combination of different optimal spectral regions selected by SVD. These results demonstrate that FTIR spectroscopy has considerable potential as a rapid method for the identification of different phenotypes of staphylococci and epidemiological typing of MRSA.

Variable-temperature Fourier transform infrared spectroscopy can be employed to monitor the denaturation and aggregation of proteins during heat treatment. Information on the changes that occur in protein secondary structure upon heating is provided by detailed examination of the amide I band, as different protein conformations have characteristic amide I frequencies. The objectives of the present study were: (i) to study the changes in protein structure that occur during gelation of whey protein isolate (WPI) and (ii) to correlate the changes in protein structure observed under different physico-chemical conditions to rheological properties of WPI gels prepared under the same conditions. / The FTIR spectra of D2O solutions of WPI at different pHs, ranging from 3 to 10, were recorded as the temperature of the solution was increased from room temperature to 95°C in 5°C increments. In all the solutions studied, the formation of two new bands at 1618--1623 cm -1 and 1678--1684 cm-1 was observed upon heating; these bands are characteristic of aggregate formation and have been previously assigned to antiparallel beta-sheet structure. As the pH increased from 3 to 10, the aggregation temperature of WPI decreased from 85°C to 65°C. / The rheological properties of WPI gels were studied by employing an Instron Universal Testing Machine. The Instron measurements demonstrated that protein concentration, heating temperature, and heating and cooling time are directly related to gel strength. The changes in gel strength as a function of cooling time (for gels prepared by heating at 75°C for 45 min) were correlated to FTIR spectral data for WPI solutions subjected to the same treatment.