Cheese is a fermented product in which bacteria contribute to different flavours and textures. In order to understand the microbial processes in cheese, it is necessary to not only look at the genomic information in bacteria. The metabolome consists of a complete collection of metabolites in a biological sample. These metabolites are small molecules with a Mr >1.5 kDa, including flavour compounds. During the ripening process of cheese, many microbiological and biochemical changes occur that give cheese a diversity of textures and flavours. Proteins that go through proteolysis and amino acid catabolism are of great importance in the development of flavour in cheese, regardless of variety. Even though techniques for measurements of metabolites have existed for a long time, there are some unique challenges by analysing of several metabolites in parallel in a biological sample that promotes different metabolic pathways. Metabolic fingerprinting is the most common approach used in metabolomics, which is based on statistical analysis that through algorithms presents differences between samples. The electronic nose is able to identify the sum of volatile metabolites in a food, which is unlike the gas chromatograph that identifies individual metabolites. The aim of this review is to evaluate the use of metabolomics of selected Enterobacteriaceae together with electronic nose technology in order to analyse possible patterns of volatile metabolites produced in soft cheese. By this we hope to evaluate potential application of this approach in food quality control and microbial contamination screening. The pilot study was done together with the center for AASS, Örebro University where bacteria were analysed using the electronic nose NST3320. The study showed that it is possible to discriminate between Enterobacteriaceae, Staphylococcus aureus and cheese-associated bacteria, but also between the Enterobacteriaceae species Escherichia coli, Hafnia alvei and Klebsiella pneumoniae. It is important to consider the gas sensors gradually lose their ability to detect substances after continual use, in which they need to be replaced with new gas sensors. Further, data processing requires special knowledge and can be hard to handle if the expertise is lacking. We believe that there is evidence that metabolomics together with the electronic nose have future prospects in terms of quality control and microbial contamination screening.

Athletes complete a balance of training loads and rest periods, risking overtraining when this balance favors excessive training. Diagnostic biomarkers have been suggested but a clear diagnostic method is not available. This preliminary study's objective was to use data standardization to improve an electronic nose's (enose) discrimination model for athletes' breathprints after cumulative and acute training loads. Collegiate long distance runners were observed throughout competitive training seasons. Prolonged training effects were observed through Profile of Mood States (POMS) surveys and blood and breath samples collected at the beginning (Pre-Study) and end of the training season (Post-Study). Immediate training effects were observed for one low (LI) and one high (HI) intensity acute training load. Subjects provided blood and breath samples before the LI (BSR) and HI (BLR), completed the training load, and provided blood and breath samples after each training load (ASR; ALR). Blood was analyzed for antioxidant enzymes (catalase, glutathione peroxidase, and glutathione reductase). Breath samples were analyzed with a Cyranose® 320 (C320) enose. Age, gender, and training loads affected oxidative states, with the HI having more effect than the LI. Mood profiles indicated healthy and successful athletes. Neither POMS nor blood parameters suggested overtrained athletes. The C320 successfully discriminated between breathprints of athletes correlating to the training loads. Direct data standardization through carbon dioxide as a baseline sensor purge correctly classified 100 percent of the data through linear discriminant analysis (LDA). Indirect data standardization by subtracting Pre-Study data from the subsequent data classes (e.g. BSR) correctly classified 96 percent of the data. An LDA on the combined blood parameters correctly classified 61.9 percent of the data. The blood analyses required invasive sample collections and involved procedures that took a long time (hours). In comparison, the best C320 model correctly classified 96 percent of the data and required less invasive sample collections, simple analysis, and short result times (minutes). Evidence suggested the C320 will provide a simple and noninvasive method for clinically diagnosing the onset of overtraining. The unit is small, handheld, rapid, and noninvasive so it could also be used on- site to provide immediate feedback for training optimization. / Ph. D.

Athletic performance is improved by increasing training loads but it is difficult to determine an athlete's response to a training load and the amount of stress incurred. This makes athletes susceptible to overtraining, leading to decreased performance levels, due to physical exhaustion and oxidative stress. Past studies have observed a myriad of biomarkers without conclusively identifying a clinically specific marker for overtraining due to oxidative stress. These methods require invasive testing and lengthy result times, making real-time adjustments of training programs to prevent overtraining difficult. The use of an electronic nose (enose) as a non-invasive evaluation tool will provide immediate feedback on training stress, allowing for real-time training adjustments for performance optimization. Two long distance runners (one male and one female) completed a pilot study. Both performed a short run and the female performed a long run. Blood samples were collected from each athlete before and after each run and analyzed for catalase and GPx activity. Breath samples were also collected before and after each run and analyzed by an enose. Multivariate analyses of combined blood data yielded better results than individual analyses. Although data was limited for this pilot study, canonical discriminant analyses (CDA) showed separation between before and after run and between short and long run breath samples. Cross validations also found up to a 77.8 percent prediction accuracy for the enose. Results indicate an enose is feasible for detecting changes in the breath occurring after physically demanding exercise perhaps due to oxidative stress incurred during the exercise. / Master of Science

Vineyard management practices are known to affect fruit composition and resultant wines, in part, by altering fruit volatiles. Methods currently used to evaluate the impact of vineyard practices on grape/wine composition include measuring physico-chemistry indices and performing wine sensory analyses. These activities are both time-consuming and destructive. Two electronic nose (ENose) systems: a hand-held conducting polymer-based and a portable surface acoustic wave-based systems were investigated as grape monitoring tools. Vineyard treatments included the effect of canopy side (East vs. West and North vs. South), cluster thinning (unthinned, 1 cluster/shoot, and 1 & 2 cluster/shoot) and ethanol spray (5% v/v) on Cabernet franc, Merlot and both varieties respectively. ENose data were obtained in the field (over two growing seasons for canopy side and in 2008 for cluster thinning and ethanol spray) and laboratory (2007 for canopy side), across different sampling dates and compared with nine-grape/eight-wine chemistry assays, GC/MS (cluster thinning) and wine aroma sensory evaluations (triangular difference testing). ENose results demonstrated 100% significant differences between all Cabernet franc and Merlot treatments. Grape/wine chemistry indices, for both Cabernet franc and Merlot, did not differ among treatments (except ethanol treatment) across sampling dates or growing seasons and vineyard management practices. Wine aroma sensory evaluations demonstrated only limited differences (3 out of 8 comparisons: East vs. West, 1 cluster/shoot vs. 1 & 2 clusters/shoot and 1 cluster/shoot and 1 & 2 clusters/shoot). The high level of discrimination by ENose systems may provide opportunities to enhance the understanding of vineyard management activities. / Master of Science in Life Sciences

Grape maturity is a critical attribute impacting potential wine quality. Maturity evaluation is difficult due to the many interrelated factors that impact physicochemical changes and limitations in the understanding of these factors. Current methods of assessing grape maturity are destructive, expensive, time consuming, subjective, and do not always strongly correlated to potential wine quality. This study evaluated the applicability of a conducting polymer-based electronic nose to monitor grape maturity by analyzing headspace volatiles. In the first part of the study, system and experimental parameters affecting the electronic nose operation were investigated to optimize detection of wine grape aroma. In the second part, the ability of an electronic nose to classify Cabernet Sauvignon (Vitis vinifera L.) grapes based on maturity was investigated. Maturity of samples collected at different weeks post-bloom was evaluated by measuring berry weight, pH, Brix, titratable acidity, total phenols, color intensity, hue, total anthocyanins, and total and phenol-free glycosides. Results were compared, using discriminant and canonical discriminant analysis, with analysis of headspace volatiles via the hand-held electronic nose. The electronic nose was able to determine the difference between the sample groups. Field measurements demonstrated the potential for the electronic nose as a rapid, non-destructive tool for evaluating grape maturity. / Master of Science

The apple growers and packaging houses are interested in methods that can evaluate the quality of apples non-destructively. Harvested fruits are a mixture of immature, mature, and over mature fruits, thereby posing a great problem in deciding their end use and storage time. It is expected that the technique developed from the present project could be effectively used to classify the harvested fruit into immature, mature and over mature apples, rapidly and non-destructively. It would also help the growers to predict the optimum dates to harvest the fruits. York and Gala were the varieties of apples that were used in this study and were obtained from Virginia Tech College of Agriculture and Life Sciences Kentland Farm. Apples were harvested at different times resulting in different maturity groups (immature, mature and ripe). Gala apples were harvested on three dates with an interval of 10 days, while York apples were harvested on four dates with an interval of 14 days. They were stored at 0oC until sampled. For each harvest date, the experiments were conducted in two sets (10 each) on two consecutive days. First the ethylene levels were measured, followed by gas chromatograph and electronic nose. Then the maturity indices were measured. Three maturity indices, starch index, firmness and soluble solids were used as the three variables for the statistical analysis to identify and categorize the fruits into three maturity categories referred as immature, mature and over mature fruits. Apples were also categorized into three maturity groups based on the emanation levels of the aroma compounds evolved from the fruits. Then electronic nose sensor responses were categorized into the above maturity categories, and their effectiveness was determined using a statistical procedure called Discriminant Analysis (DA). From the DA cross validation results the correct classification percentage for Gala and York apples into maturity groups was 95%. The Electronic nose sensor's effectiveness to categorize the same observations based on sensor responses in to the above classified maturity categories was 83% correct in case Gala apples and 69% for York apples. The EN sensors response data were analyzed by the EN system software and the correct classification percentage for Gala was 83% and for York was 81%. Aroma-based categorization for Gala apples was 100% correct, while the electronic nose for the same analysis was 80%. Based on the three physical parameters, an objective evaluation of maturity could be accomplished. Principal Component Analysis, Canonical Discriminant Analysis and DA results demonstrated that the electronic nose could be used to classify apples into three identified maturity-based groups. The EN sensors (Gala apples), could also classify the apples into aroma-based categories. Thus, it can be concluded that the EN system holds promise as non-destructive evaluation technique to determine the maturity of an apple. / Master of Science

Vineyard management practices are known to affect fruit composition and resultant wines, in part, by altering fruit volatiles. Methods currently used to evaluate the impact of vineyard practices on grape/wine composition include measuring physico-chemistry indices and performing wine sensory analyses. These activities are both time-consuming and destructive. Two electronic nose (ENose) systems: a hand-held conducting polymer-based and a portable surface acoustic wave-based systems were investigated as grape monitoring tools. Vineyard treatments included the effect of canopy side (East vs. West and North vs. South), cluster thinning (unthinned, 1 cluster/shoot, and 1 & 2 cluster/shoot) and ethanol spray (5% v/v) on Cabernet franc, Merlot and both varieties respectively. ENose data were obtained in the field (over two growing seasons for canopy side and in 2008 for cluster thinning and ethanol spray) and laboratory (2007 for canopy side), across different sampling dates and compared with nine-grape/eight-wine chemistry assays, GC/MS (cluster thinning) and wine aroma sensory evaluations (triangular difference testing). ENose results demonstrated 100% significant differences between all Cabernet franc and Merlot treatments. Grape/wine chemistry indices, for both Cabernet franc and Merlot, did not differ among treatments (except ethanol treatment) across sampling dates or growing seasons and vineyard management practices. Wine aroma sensory evaluations demonstrated only limited differences (3 out of 8 comparisons: East vs. West, 1 cluster/shoot vs. 1 & 2 clusters/shoot and 1 cluster/shoot and 1 & 2 clusters/shoot). The high level of discrimination by ENose systems may provide opportunities to enhance the understanding of vineyard management activities. / Master of Science

Prostate cancer is the most commonly diagnosed disease and second most commonly caused death among men in America. Although much controversy surrounds the current methods of detection, PSA test and biopsy, no new methods have been approved as an effective method of detection. Biomarkers and non-invasive means of detection are being investigated everyday in hopes of discovering new information that could be of use in the prostate cancer field. One such non-invasive technology is the use of an electronic nose. The electronic nose technology has been utilized in the agricultural, food, biomedical, and environmental. The objective of this current study is to determine the effectiveness of the electronic nose to discriminate between prostate cancer cells (DU-145 and PC-3) and non-tumor forming cells from the urinary tract (SVHUC). Specific factors that will be investigated are incubation period and cell population. For all three cell lines, two cell populations of 75,000 and 150,000 cells were cultured and tested after 2, 8, 12, and 24 hours using a conducting polymer based hand-held electronic nose. Multivariate analysis was performed on the data and determined that the greatest discrimination between incubation periods was between 2 hours of incubation and the remaining periods of 8, 12, and 24 hour periods. This presents the idea that by 8 hours, ample volatiles were produced to be detected by the electronic nose. Additionally, when compared to one another, all three cell lines showed distinct differences. The cell lines most closely related were PC-3 and DU-145, the prostate cancer cell lines. However some variation was seen between these cell lines, which may be attributed to the presence of PSA in PC-3 cells or other factors affecting prostate cancer patients. Finally, PCA plots clearly illustrated that after 2 hours of incubation, sufficient volatiles were produced to allow the electronic nose to clearly discriminate the three cell lines from one another, demonstrating the importance of incubation period on successful discrimination. Based on the findings that the electronic nose was effective at discriminating the three cell lines, testing was completed to determine if cell population or cell maturity had the greatest effect on discrimination. The cell lines were cultured and tested immediately using an initial cell population of the highest cell population observed after a 72 hour incubation period. The results concluded that when the cell lines were tested immediately after culturing, the Cyranose was able to detect the individual cell lines in culture while also determining a range of detection for each cell line. The range of detection for DU-145 was found to be 26,200 to 262,000 cells based on interclass m-distances of 6.829-9.170 for cell populations lower than 26,200. A range of detection of 51,400 to 514,000 cells was concluded for PC-3 cells based on interclass m-distances of 5.690-7.400 for cell populations lower than 51,400. Finally, the results showed a range of detection of 19,000 to 190,000 cells for SVHUC based on interclass m-distances of 5.520-9.076 for cell populations lower than 19,000. However, when attempting to discriminate the three cell lines against one another immediately after culture, the electronic nose was unable to make clear distinctions between the three cell lines. When testing cancerous and non-cancerous cells, incubation period of the cells should be the only factor considered. It is evident that the cells need time to metabolize and produce volatiles so that the electronic nose can clearly distinguish these cells from one another in culture. / Master of Science

The expanding role of electronic nose instrumentation, as a quality-monitoring tool for food-packaging materials, is examined and reviewed. The food industry is interested in determining the applicability of using an electronic nose for odor analysis of retained printing solvent levels in packaging. Three electronic nose systems were optimized for this application and their performance assessed. These include the FOX 3000, the Cyranose 320, and the QMB6. Response surface methodology was used to generate 2nd order models of sensor response as a function of system and experimental parameters for the three electronic nose systems. Forty-seven of 50 sensor models generated were found to be significant at an a-level of 0.05. Optimum settings, that allowed adequate signals to be obtained for the full range of examined retained solvents levels, were selected for the remaining work using these models. Performance analyses of these systems, which use three leading sensor technologies, showed that the conducting polymer sensor technology demonstrated the most discriminatory power. All three technologies proved able to discriminate among different levels of retained solvents. Each complete electronic nose system was also able to discriminate between assorted packaging having either conforming or non-conforming levels of retained solvents. Each system correctly identified 100% of unknown samples. Sensor technology had a greater effect on performance than the number of sensors used. Based on discriminatory power and practical features, the FOX 3000 and the Cyranose 320 were superior. The results indicate that electronic nose instrumentation can be used as a complimentary discriminatory tool in quality control. / Master of Science

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