Lung cancer is one of the most serious and common cancer types of today, with very uncomfortable and potentially cumbersome diagnostic techniques in x-ray, CT, CT-PET scans, bronchoscopies and biopsies. Completing all these steps can also take a long time and be time consuming for hospital staff. So finding a new safer and faster technique to diagnose cancer would be of great benefit. The objectives of this pilot study is to create an effective data storage system that can be scaled for larger data sets in a later study. The aim was also to see whether a E-nose can be used to find the differences in smell-prints from a healthy lung and a cancerous lung. As well as seeing if the E-nose can distinguish samples drawn from the lungs from exhaled air samples. Samples were taken on patients by the staff at ”Lung kliniken” at Link¨oping University Hospital during a bronchoscopy on patients with one-sided lung cancer. These samples were then analyzed by the E-nose which sensory response is later used to test the classification system that uses a mix of Principal Component Analysis (PCA) and K-Nearest Neighbour (KNN). Using a k = 7, the system was able to correctly classify 60 % of the samples when comparing cancerous and healthy lung samples. Comparing exhaled, healthy and cancerous samples the accuracy was calculated to 55.56 %. Comparing all lung samples against exhaled samples the accuracy was 86.67 %

No description available.

No description available.

No description available.

Food loss and waste represent a significant challenge to global sustainability. In a world where the number of people suffering from hunger has been rising, approximately 1.3 million tonnes of food are lost or wasted each year. When food is lost or wasted, all the resources used to produce it, including water, land, energy, labor, and capital, are also lost. In addition, it is estimated that the disposal of food in landfills generates 11% of all greenhouse gas emissions, thereby contributing to climate change. Food loss and waste can also have a negative impact on food security and prices. This dissertation introduces non-invasive and chemicals-free solutions for the shelf-life extension and quality monitoring of fresh foods. First, we propose the creation of a sterilized anaerobic storage environment using UV-C irradiation and vacuum sealing for increasing the shelf-life of perishables. The proposed combination was tested on fresh strawberries and quartered tomatoes and has successfully increased the shelf-life by 124.41% and 54.41%, respectively, while acceptable sensory characteristics were maintained throughout the storage period. Second, the proposed combination was tested on fresh beef, chicken and salmon fillets, where a shelf-life increase of 66% was achieved. The shelf-life of strawberries, tomatoes and meats were determined by monitoring the organoleptic qualities and counting the microbial populations of various bacteria, which includes aerobic bacteria, Lactic Acid Bacteria, Pseudomonas spp., yeast, mold, Salmonella and E-coli in addition to pH measurements. In the third part, we propose an IoT-enabled electronic nose system for rapid beef quality monitoring. The e-nose system includes carbon dioxide, ammonia, and ethylene sensors to measure the volatile organic compounds' (VOCs) concentrations. Microbial population quantifications of various bacteria were conducted to identify the concentrations of VOCs that are associated with raw beef spoilage. The production of VOCs was correlated with the proliferation of bacteria using linear regression, and it was discovered that aerobic bacteria and Pseudomonas spp. play a significant role in the production of VOCs in raw beef, as opposed to LAB. This system demonstrates how the IoT-enabled e-nose system can be an effective tool for monitoring the quality of perishables.

Lung cancer (LC) is often diagnosed at advanced stage and as a result, survival rates are low. Recent studies describe exhaled breath and exhaled breath condensate (EBC) as a potential non-invasive method of sampling the airways for assessing inflammation of the respiratory system, and possibly for the early detection of LC. It was hypothesised that higher concentrations of markers and protein will be present in the EBC of LC patients compared to those of normal controls and healthy smokers, and may aid in assessing lung status. Methods: The gaseous phase of breath was investigated for volatile organic compound (VOC) patterns using an electronic nose (eNose) system, in addition to off-line measurements of carbon monoxide (CO) and nitric oxide (NO) levels. The aqueous phase, EBC, was collected during tidal breathing through a glass collection device cooled to 4??C by ice. Nitrite/nitrate (NOx) and pH levels were determined by a fluorescent modification of the Griess method, and silicon chip sensor pH meter, respectively. Protein levels in EBC were examined with a bicinchoninic acid (BCA) assay, silver staining and PAGE techniques, while the levels of tumour markers, CYFRA 21-1 and CEA, were quantified by enzyme-linked immunosorbent assays (ELISA). Results: The eNose machine was not able to produce characteristic VOC profiles from exhaled breath unique to each study group, while no significant difference was observed for mean NOx concentrations in the LC group when compared to other subjects (p=0.8824). Higher protein levels were found in the EBC of LC patient compared to normal controls (p=0.0204), with subsequent measurements of elevated CEA levels observed in the LC group when compared to non-smokers and smokers (p=0.023). Conclusion: This study showed that protein can be detected in the exhaled breath condensate of patients, with a significantly elevated amount in the samples from newly diagnosed LC patients. The mechanism for these differences remains to be determined but may be related to inflammatory changes within the airway, such as vascular protein leakage and release of mediators. Future work may aim to identify the upregulated proteins, and focus on proteomics and tissue microarrays to explore candidate proteins.

Aroma is one of the most important quality attributes of bread or any food. It will determine whether the product will be tasted and eaten in the first instance and is a major factor in establishing acceptability and preference. The dominant preference by consumers of bread made from refined flour in contrast to whole wheat flour is at least in part due to the strong and different aroma of whole wheat bread. White wheats may have an advantage over red wheat in this regard according to some industry reports, but the science is extremely limited. The goal of this research was to add more science-based knowledge to this topic via the use of machine olfaction technology, specifically electronic (E) nose and gas chromatography combined with mass spectrometry (GC-MS). A state-of-the-art E-nose system (AlphaMOS FOX 3000) with metal oxide sensors (MOS) was used to capture aroma volatiles from crumb, crust and whole slices of breads made from sound Canadian Western Red Spring (CWRS) wheat as well as representative samples of two hard white wheats, viz. Snowbird, a cultivar belonging to the Canada Western Hard White Spring (CWHWS) class of wheat, and Platte, a U.S. Hard White Winter (HWW) wheat. The same CWRS wheat provided the base flour for all the breads. A commercial formula and size format was used to produce breads from four flours for the study, i.e. refined CWRS wheat, and three whole wheat flours comprising blends of 85% CWRS flour and 15% bran from CWRS wheat, Snowbird and Platte. As there was no established protocol in the literature to evaluate bread aroma by E-nose, one was developed. Five temperatures (35, 40, 45, 50 and 60°C) were tested along with two incubation times (5 and 10 min) and four sample sizes (0.05, 0.1, 0.25 and 0.50 g) of ground bread crumbs. Through optimization using E-nose software including principal component analysis, a procedure was adopted using 40 °C, 5 min incubation time and 0.05 g of sample to acquire MOS data from 12 sensors for crust, crumb and whole slices of refined and whole wheat breads. Multivariate analysis methods were used to evaluate the capabilities of the E-nose system to discriminate and correctly classify samples according to bread type. Data for analysis comprised approximately 24 samples each of crust, crumb and whole slices randomly selected from three loaves each of refined and the three whole wheat breads. Results varied according to the nature of the sample, i.e. crust, crumb or whole slices. For crusts, the greatest distinction in aroma was found between refined and whole wheat breads. Refined bread crust was correctly classified 67% of the time. When refined bread crust was misclassified, samples were confused with whole white wheat crust predominantly from Platte bread. For whole wheat bread crusts, the pattern of classification depended mainly on bran colour. Whole wheat bread crust samples had correct classification scores in the range 54-58%. When misclassified, whole wheat CWRS crust was equally confused with the aroma of crust of the white whole wheat breads, Platte and Snowbird. Whole wheat Platte crust tended to be misclassified with the counterpart white whole wheat Snowbird or refined bread crust. In contrast, Snowbird whole wheat crust tended to be misclassified as either its counterpart HW wheat Platte or whole CWRS wheat. Accordingly, Platte bread crust appeared to possess an aroma more in line with refined wheat bread as opposed to whole wheat bread. For bread crumb, the pattern of E-nose differentiation of samples was different. In this case, CWRS whole wheat bread aroma was clearly and perfectly distinguished from the crumb aroma of all the other breads, either whole white wheat or refined CWRS. The latter tended to cluster on its own, as might be expected, and had a correct classification score of 75%, with the balance of samples largely misclassified as Snowbird crumb. Whole wheat Platte and Snowbird bread crumb had identical correct classification scores of 42%, and were similarly confused with the other’s aroma (average 3 4% classified) or the aroma of refined wheat bread (average 21% classified). E-nose results for crumb indicated a clear distinction in aroma between the hard red and white wheats in this study. E-nose analysis of bread samples representing whole slices produced results that provided unsatisfactory discrimination among bread types likely due to the blending of the different aromas of constituent crust and crumb. For whole slices, discrimination between refined and whole wheat breads was substantially lower than that for either crust and crumb samples. Based on this result, analysis of samples that combine both crust and crumb is not recommended for sensory analysis of bread, whether by instruments or human sensory panel. Further understanding of the differences between different types of bread made from refined wheat flour and whole wheat, and how the inclusion of bran from red and white-grained wheats modifies the composition and content of volatile and non-volatile compounds in crust and crumb was determined by gas chromatography-mass spectrometry (GC-MS). In total, 50 compounds were found, the greater majority of which have been previously reported in bread. Major Maillard reaction compounds like furfural, 2-furanmethanol, pyranone, maltol and 5-hydroxymethyl- 2-furancarboxaldehyde were present in highest concentration in whole CWRS bread. Significantly fewer compounds were found in the crust and crumb of CWRS refined wheat bread compared to the other whole wheat breads. In contrast, whole CWRS bread crumb and crust had the highest number of compounds, and in considerably higher total concentration compared to the other two whole white wheat breads, Snowbird and Platte. The higher concentration and number of compounds in whole CWRS bread was attributed to the wheat bran fraction. White whole wheat breads, Snowbird and Platte, had a total number of compounds in crust and crumb approximately intermediate between refined and whole CWRS bread, although Platte whole wheat bread crust was closer to refined bread crust in compound numbers. In terms of total compound concentrations, crust and crumb samples of the whole white breads were clearly more similar to refined CWRS bread, and in the case of whole wheat Platte bread crust, compound concentrations were much lower. On the whole, these aggregate totals of compound numbers and concentrations by GC-MS mirrored the discrimination and classification results obtained by E-nose, and supported the contention that whole wheat bread made with white wheat bran was milder in aroma compared to bread formulated using red wheat bran. While the number of samples of red and white wheats were very few in this study, results support the contention that different wheat genotypes and specifically, the bran tissue of these genotypes, contain differences in compound composition and/or concentration which when processed by breadmaking, manifest volatiles characteristic of those genotypes even between genotypes possessing the same colour of bran. E-nose instrumentation appears to be very capable of accommodating these sorts of complex tasks on fresh bread. It would be highly beneficial in future research to carry out similar studies in parallel with a human sensory panel, and ideally with many more genotypes of red and white grained wheat with an aim to firmly establish the relative superiority of particular genotypes to produce whole wheat bread with aroma profiles more similar to those of white pan bread. The long term goal of such studies would be to foster increased consumption of whole wheat products and constituent bioactive compounds which confer favourable health benefits in the general population.

Aroma is one of the most important quality attributes of bread or any food. It will determine whether the product will be tasted and eaten in the first instance and is a major factor in establishing acceptability and preference. The dominant preference by consumers of bread made from refined flour in contrast to whole wheat flour is at least in part due to the strong and different aroma of whole wheat bread. White wheats may have an advantage over red wheat in this regard according to some industry reports, but the science is extremely limited. The goal of this research was to add more science-based knowledge to this topic via the use of machine olfaction technology, specifically electronic (E) nose and gas chromatography combined with mass spectrometry (GC-MS). A state-of-the-art E-nose system (AlphaMOS FOX 3000) with metal oxide sensors (MOS) was used to capture aroma volatiles from crumb, crust and whole slices of breads made from sound Canadian Western Red Spring (CWRS) wheat as well as representative samples of two hard white wheats, viz. Snowbird, a cultivar belonging to the Canada Western Hard White Spring (CWHWS) class of wheat, and Platte, a U.S. Hard White Winter (HWW) wheat. The same CWRS wheat provided the base flour for all the breads. A commercial formula and size format was used to produce breads from four flours for the study, i.e. refined CWRS wheat, and three whole wheat flours comprising blends of 85% CWRS flour and 15% bran from CWRS wheat, Snowbird and Platte. As there was no established protocol in the literature to evaluate bread aroma by E-nose, one was developed. Five temperatures (35, 40, 45, 50 and 60°C) were tested along with two incubation times (5 and 10 min) and four sample sizes (0.05, 0.1, 0.25 and 0.50 g) of ground bread crumbs. Through optimization using E-nose software including principal component analysis, a procedure was adopted using 40 °C, 5 min incubation time and 0.05 g of sample to acquire MOS data from 12 sensors for crust, crumb and whole slices of refined and whole wheat breads. Multivariate analysis methods were used to evaluate the capabilities of the E-nose system to discriminate and correctly classify samples according to bread type. Data for analysis comprised approximately 24 samples each of crust, crumb and whole slices randomly selected from three loaves each of refined and the three whole wheat breads. Results varied according to the nature of the sample, i.e. crust, crumb or whole slices. For crusts, the greatest distinction in aroma was found between refined and whole wheat breads. Refined bread crust was correctly classified 67% of the time. When refined bread crust was misclassified, samples were confused with whole white wheat crust predominantly from Platte bread. For whole wheat bread crusts, the pattern of classification depended mainly on bran colour. Whole wheat bread crust samples had correct classification scores in the range 54-58%. When misclassified, whole wheat CWRS crust was equally confused with the aroma of crust of the white whole wheat breads, Platte and Snowbird. Whole wheat Platte crust tended to be misclassified with the counterpart white whole wheat Snowbird or refined bread crust. In contrast, Snowbird whole wheat crust tended to be misclassified as either its counterpart HW wheat Platte or whole CWRS wheat. Accordingly, Platte bread crust appeared to possess an aroma more in line with refined wheat bread as opposed to whole wheat bread. For bread crumb, the pattern of E-nose differentiation of samples was different. In this case, CWRS whole wheat bread aroma was clearly and perfectly distinguished from the crumb aroma of all the other breads, either whole white wheat or refined CWRS. The latter tended to cluster on its own, as might be expected, and had a correct classification score of 75%, with the balance of samples largely misclassified as Snowbird crumb. Whole wheat Platte and Snowbird bread crumb had identical correct classification scores of 42%, and were similarly confused with the other’s aroma (average 3 4% classified) or the aroma of refined wheat bread (average 21% classified). E-nose results for crumb indicated a clear distinction in aroma between the hard red and white wheats in this study. E-nose analysis of bread samples representing whole slices produced results that provided unsatisfactory discrimination among bread types likely due to the blending of the different aromas of constituent crust and crumb. For whole slices, discrimination between refined and whole wheat breads was substantially lower than that for either crust and crumb samples. Based on this result, analysis of samples that combine both crust and crumb is not recommended for sensory analysis of bread, whether by instruments or human sensory panel. Further understanding of the differences between different types of bread made from refined wheat flour and whole wheat, and how the inclusion of bran from red and white-grained wheats modifies the composition and content of volatile and non-volatile compounds in crust and crumb was determined by gas chromatography-mass spectrometry (GC-MS). In total, 50 compounds were found, the greater majority of which have been previously reported in bread. Major Maillard reaction compounds like furfural, 2-furanmethanol, pyranone, maltol and 5-hydroxymethyl- 2-furancarboxaldehyde were present in highest concentration in whole CWRS bread. Significantly fewer compounds were found in the crust and crumb of CWRS refined wheat bread compared to the other whole wheat breads. In contrast, whole CWRS bread crumb and crust had the highest number of compounds, and in considerably higher total concentration compared to the other two whole white wheat breads, Snowbird and Platte. The higher concentration and number of compounds in whole CWRS bread was attributed to the wheat bran fraction. White whole wheat breads, Snowbird and Platte, had a total number of compounds in crust and crumb approximately intermediate between refined and whole CWRS bread, although Platte whole wheat bread crust was closer to refined bread crust in compound numbers. In terms of total compound concentrations, crust and crumb samples of the whole white breads were clearly more similar to refined CWRS bread, and in the case of whole wheat Platte bread crust, compound concentrations were much lower. On the whole, these aggregate totals of compound numbers and concentrations by GC-MS mirrored the discrimination and classification results obtained by E-nose, and supported the contention that whole wheat bread made with white wheat bran was milder in aroma compared to bread formulated using red wheat bran. While the number of samples of red and white wheats were very few in this study, results support the contention that different wheat genotypes and specifically, the bran tissue of these genotypes, contain differences in compound composition and/or concentration which when processed by breadmaking, manifest volatiles characteristic of those genotypes even between genotypes possessing the same colour of bran. E-nose instrumentation appears to be very capable of accommodating these sorts of complex tasks on fresh bread. It would be highly beneficial in future research to carry out similar studies in parallel with a human sensory panel, and ideally with many more genotypes of red and white grained wheat with an aim to firmly establish the relative superiority of particular genotypes to produce whole wheat bread with aroma profiles more similar to those of white pan bread. The long term goal of such studies would be to foster increased consumption of whole wheat products and constituent bioactive compounds which confer favourable health benefits in the general population.

Lung cancer (LC) is often diagnosed at advanced stage and as a result, survival rates are low. Recent studies describe exhaled breath and exhaled breath condensate (EBC) as a potential non-invasive method of sampling the airways for assessing inflammation of the respiratory system, and possibly for the early detection of LC. It was hypothesised that higher concentrations of markers and protein will be present in the EBC of LC patients compared to those of normal controls and healthy smokers, and may aid in assessing lung status. Methods: The gaseous phase of breath was investigated for volatile organic compound (VOC) patterns using an electronic nose (eNose) system, in addition to off-line measurements of carbon monoxide (CO) and nitric oxide (NO) levels. The aqueous phase, EBC, was collected during tidal breathing through a glass collection device cooled to 4??C by ice. Nitrite/nitrate (NOx) and pH levels were determined by a fluorescent modification of the Griess method, and silicon chip sensor pH meter, respectively. Protein levels in EBC were examined with a bicinchoninic acid (BCA) assay, silver staining and PAGE techniques, while the levels of tumour markers, CYFRA 21-1 and CEA, were quantified by enzyme-linked immunosorbent assays (ELISA). Results: The eNose machine was not able to produce characteristic VOC profiles from exhaled breath unique to each study group, while no significant difference was observed for mean NOx concentrations in the LC group when compared to other subjects (p=0.8824). Higher protein levels were found in the EBC of LC patient compared to normal controls (p=0.0204), with subsequent measurements of elevated CEA levels observed in the LC group when compared to non-smokers and smokers (p=0.023). Conclusion: This study showed that protein can be detected in the exhaled breath condensate of patients, with a significantly elevated amount in the samples from newly diagnosed LC patients. The mechanism for these differences remains to be determined but may be related to inflammatory changes within the airway, such as vascular protein leakage and release of mediators. Future work may aim to identify the upregulated proteins, and focus on proteomics and tissue microarrays to explore candidate proteins.

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 neumoniae. 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.