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Peter Schieberle - One of the best experts on this subject based on the ideXlab platform.
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characterization of key Aroma compounds in a commercial rum and an australian red wine by means of a new sensomics based expert system sebes an approach to use artificial intelligence in determining Food odor codes
Journal of Agricultural and Food Chemistry, 2019Co-Authors: Luca Nicolotti, Veronika Mall, Peter SchieberleAbstract:Although to date more than 10 000 volatile compounds have been characterized in Foods, a literature survey has previously shown that only 226 Aroma compounds, assigned as key Food odorants (KFOs), have been identified to actively contribute to the overall Aromas of about 200 Foods, such as beverages, meat products, cheeses, or baked goods. Currently, a multistep analytical procedure involving the human olfactory system, assigned as Sensomics, represents a reference approach to identify and quantitate key odorants, as well as to define their sensory impact in the overall Food Aroma profile by so-called Aroma recombinates. Despite its proven effectiveness, the Sensomics approach is time-consuming because repeated sensory analyses, for example, by GC/olfactometry, are essential to assess the odor quality and potency of each single constituent in a given Food distillate. Therefore, the aim of the present study was to develop a fast, but Sensomics-based expert system (SEBES) that is able to reliably predict th...
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Characterization of Key Aroma Compounds in a Commercial Rum and an Australian Red Wine by Means of a New Sensomics-Based Expert System (SEBES)An Approach To Use Artificial Intelligence in Determining Food Odor Codes
2019Co-Authors: Luca Nicolotti, Veronika Mall, Peter SchieberleAbstract:Although to date more than 10 000 volatile compounds have been characterized in Foods, a literature survey has previously shown that only 226 Aroma compounds, assigned as key Food odorants (KFOs), have been identified to actively contribute to the overall Aromas of about 200 Foods, such as beverages, meat products, cheeses, or baked goods. Currently, a multistep analytical procedure involving the human olfactory system, assigned as Sensomics, represents a reference approach to identify and quantitate key odorants, as well as to define their sensory impact in the overall Food Aroma profile by so-called Aroma recombinates. Despite its proven effectiveness, the Sensomics approach is time-consuming because repeated sensory analyses, for example, by GC/olfactometry, are essential to assess the odor quality and potency of each single constituent in a given Food distillate. Therefore, the aim of the present study was to develop a fast, but Sensomics-based expert system (SEBES) that is able to reliably predict the key Aroma compounds of a given Food in a limited number of runs without using the human olfactory system. First, a successful method for the quantitation of nearly 100 (out of the 226 known KFOs) components was developed in combination with a software allowing the direct use of the identification and quantitation data for the calculation of odor activity values (OAV; ratio of concentration to odor threshold). Using a rum and a wine as examples, the quantitative results obtained by the new SEBES method were compared to data obtained by applying an Aroma extract dilution analysis and stable isotope dilution assays required in the classical Sensomics approach. A good agreement of the results was found with differences below 20% for most of the compounds considered. By implementing the GC × GC data analysis software with the in-house odor threshold database, odor activity values (ratio of concentration to odor threshold) were directly displayed in the software pane. The OAVs calculated by the software were in very good agreement with data manually calculated on the basis of the data obtained by SIDA. Thus, it was successfully shown that it is possible to characterize key Food odorants with one single analytical platform and without using the human olfactory system, that is, by “artificial intelligence smelling”
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re investigation on odour thresholds of key Food Aroma compounds and development of an Aroma language based on odour qualities of defined aqueous odorant solutions
European Food Research and Technology, 2008Co-Authors: Michael Czerny, Martin Christlbauer, Anja Fischer, Michael Granvogl, Michaela Hammer, Cornelia Hartl, Noelia Moran Hernandez, Peter SchieberleAbstract:Literature data on odour thresholds of volatile Food constituents, and, in particular on their odour quality, may differ significantly. In order to obtain more reliable sensory data, the odour thresholds of eighty-four compounds previously characterised as key Food odorants were re-evaluated and compared to literature results. In addition, the odour thresholds of ten odorants are reported here for the first time. On the basis of a distinct protocol, also the Aroma attributes of the odorants were evaluated in order to define an Aroma language, which can be used for specific purposes, e.g., training of panellists for GC-Olfactometry.
Luca Nicolotti - One of the best experts on this subject based on the ideXlab platform.
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characterization of key Aroma compounds in a commercial rum and an australian red wine by means of a new sensomics based expert system sebes an approach to use artificial intelligence in determining Food odor codes
Journal of Agricultural and Food Chemistry, 2019Co-Authors: Luca Nicolotti, Veronika Mall, Peter SchieberleAbstract:Although to date more than 10 000 volatile compounds have been characterized in Foods, a literature survey has previously shown that only 226 Aroma compounds, assigned as key Food odorants (KFOs), have been identified to actively contribute to the overall Aromas of about 200 Foods, such as beverages, meat products, cheeses, or baked goods. Currently, a multistep analytical procedure involving the human olfactory system, assigned as Sensomics, represents a reference approach to identify and quantitate key odorants, as well as to define their sensory impact in the overall Food Aroma profile by so-called Aroma recombinates. Despite its proven effectiveness, the Sensomics approach is time-consuming because repeated sensory analyses, for example, by GC/olfactometry, are essential to assess the odor quality and potency of each single constituent in a given Food distillate. Therefore, the aim of the present study was to develop a fast, but Sensomics-based expert system (SEBES) that is able to reliably predict th...
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Characterization of Key Aroma Compounds in a Commercial Rum and an Australian Red Wine by Means of a New Sensomics-Based Expert System (SEBES)An Approach To Use Artificial Intelligence in Determining Food Odor Codes
2019Co-Authors: Luca Nicolotti, Veronika Mall, Peter SchieberleAbstract:Although to date more than 10 000 volatile compounds have been characterized in Foods, a literature survey has previously shown that only 226 Aroma compounds, assigned as key Food odorants (KFOs), have been identified to actively contribute to the overall Aromas of about 200 Foods, such as beverages, meat products, cheeses, or baked goods. Currently, a multistep analytical procedure involving the human olfactory system, assigned as Sensomics, represents a reference approach to identify and quantitate key odorants, as well as to define their sensory impact in the overall Food Aroma profile by so-called Aroma recombinates. Despite its proven effectiveness, the Sensomics approach is time-consuming because repeated sensory analyses, for example, by GC/olfactometry, are essential to assess the odor quality and potency of each single constituent in a given Food distillate. Therefore, the aim of the present study was to develop a fast, but Sensomics-based expert system (SEBES) that is able to reliably predict the key Aroma compounds of a given Food in a limited number of runs without using the human olfactory system. First, a successful method for the quantitation of nearly 100 (out of the 226 known KFOs) components was developed in combination with a software allowing the direct use of the identification and quantitation data for the calculation of odor activity values (OAV; ratio of concentration to odor threshold). Using a rum and a wine as examples, the quantitative results obtained by the new SEBES method were compared to data obtained by applying an Aroma extract dilution analysis and stable isotope dilution assays required in the classical Sensomics approach. A good agreement of the results was found with differences below 20% for most of the compounds considered. By implementing the GC × GC data analysis software with the in-house odor threshold database, odor activity values (ratio of concentration to odor threshold) were directly displayed in the software pane. The OAVs calculated by the software were in very good agreement with data manually calculated on the basis of the data obtained by SIDA. Thus, it was successfully shown that it is possible to characterize key Food odorants with one single analytical platform and without using the human olfactory system, that is, by “artificial intelligence smelling”
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high concentration capacity sample preparation techniques to improve the informative potential of two dimensional comprehensive gas chromatography mass spectrometry application to sensomics
Journal of Chromatography A, 2013Co-Authors: Chiara Cordero, Luca Nicolotti, Cecilia Cagliero, Erica Liberto, Patrizia Rubiolo, Barbara Sgorbini, Carlo BicchiAbstract:Abstract This study reports and critically discusses the results of a systematic investigation on the effectiveness of different and complementary sampling approaches, based on either sorption and adsorption, treated as a further dimension of a two-dimensional comprehensive gas chromatography–mass spectrometry analytical platform for sensomics. The focus is on the potentials of a group of high concentration capacity (HCC) sample preparation (Solid Phase Microextraction, SPME, Stir Bar Sorptive Extraction, SBSE and Headspace Sorptive Extraction, HSSE) and Dynamic Headspace (D-HS) techniques investigated to provide information useful for fingerprinting and profiling studies of Food Aroma. Volatiles and semi-volatiles contributing to define whole and nonfat dry milk Aroma have been successfully characterized thanks to the combination of effective and selective sampling by HCC and D-HS techniques, high separation and detection power of GC × GC–MS and suitable data elaboration (i.e., Comprehensive Template Matching Fingerprinting – CTMF). Out of the sample preparation techniques investigated, HSSE and SBSE have shown to be really effective for sensomics studies because of their high concentration factors, providing highly representative profiles as well as analyte recovery suitable for GC-Olfactometry even with high odor threshold (OT) markers or potent odorants in sub-trace amounts.
Veronika Mall - One of the best experts on this subject based on the ideXlab platform.
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characterization of key Aroma compounds in a commercial rum and an australian red wine by means of a new sensomics based expert system sebes an approach to use artificial intelligence in determining Food odor codes
Journal of Agricultural and Food Chemistry, 2019Co-Authors: Luca Nicolotti, Veronika Mall, Peter SchieberleAbstract:Although to date more than 10 000 volatile compounds have been characterized in Foods, a literature survey has previously shown that only 226 Aroma compounds, assigned as key Food odorants (KFOs), have been identified to actively contribute to the overall Aromas of about 200 Foods, such as beverages, meat products, cheeses, or baked goods. Currently, a multistep analytical procedure involving the human olfactory system, assigned as Sensomics, represents a reference approach to identify and quantitate key odorants, as well as to define their sensory impact in the overall Food Aroma profile by so-called Aroma recombinates. Despite its proven effectiveness, the Sensomics approach is time-consuming because repeated sensory analyses, for example, by GC/olfactometry, are essential to assess the odor quality and potency of each single constituent in a given Food distillate. Therefore, the aim of the present study was to develop a fast, but Sensomics-based expert system (SEBES) that is able to reliably predict th...
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Characterization of Key Aroma Compounds in a Commercial Rum and an Australian Red Wine by Means of a New Sensomics-Based Expert System (SEBES)An Approach To Use Artificial Intelligence in Determining Food Odor Codes
2019Co-Authors: Luca Nicolotti, Veronika Mall, Peter SchieberleAbstract:Although to date more than 10 000 volatile compounds have been characterized in Foods, a literature survey has previously shown that only 226 Aroma compounds, assigned as key Food odorants (KFOs), have been identified to actively contribute to the overall Aromas of about 200 Foods, such as beverages, meat products, cheeses, or baked goods. Currently, a multistep analytical procedure involving the human olfactory system, assigned as Sensomics, represents a reference approach to identify and quantitate key odorants, as well as to define their sensory impact in the overall Food Aroma profile by so-called Aroma recombinates. Despite its proven effectiveness, the Sensomics approach is time-consuming because repeated sensory analyses, for example, by GC/olfactometry, are essential to assess the odor quality and potency of each single constituent in a given Food distillate. Therefore, the aim of the present study was to develop a fast, but Sensomics-based expert system (SEBES) that is able to reliably predict the key Aroma compounds of a given Food in a limited number of runs without using the human olfactory system. First, a successful method for the quantitation of nearly 100 (out of the 226 known KFOs) components was developed in combination with a software allowing the direct use of the identification and quantitation data for the calculation of odor activity values (OAV; ratio of concentration to odor threshold). Using a rum and a wine as examples, the quantitative results obtained by the new SEBES method were compared to data obtained by applying an Aroma extract dilution analysis and stable isotope dilution assays required in the classical Sensomics approach. A good agreement of the results was found with differences below 20% for most of the compounds considered. By implementing the GC × GC data analysis software with the in-house odor threshold database, odor activity values (ratio of concentration to odor threshold) were directly displayed in the software pane. The OAVs calculated by the software were in very good agreement with data manually calculated on the basis of the data obtained by SIDA. Thus, it was successfully shown that it is possible to characterize key Food odorants with one single analytical platform and without using the human olfactory system, that is, by “artificial intelligence smelling”
Pilar Hernandezmunoz - One of the best experts on this subject based on the ideXlab platform.
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Food Aroma mass transport properties in renewable hydrophilic polymers
Food Chemistry, 2012Co-Authors: Pau M Balaguer, Rafael Gavara, Pilar HernandezmunozAbstract:The sorption and transport properties of gliadin and chitosan films with respect to four representative Food Aroma components (ethyl caproate, 1-hexanol, 2-nonanone and α-pinene) have been studied under dry and wet environmental conditions. The partition coefficients (K) of the selected volatiles were also obtained using isooctane and soybean oil as fatty Food simulants. The results showed that gliadin and chitosan films have very low capacities for the sorption of volatile compounds, and these capacities are influenced by the nature of the sorbate, the environmental relative humidity and the presence of glycerol as a plasticizer in the polymeric matrix. The volatile compounds also present a low partitioning in the biopolymer film/Food stimulant system. Given the low levels of interaction observed with the volatiles, gliadin and chitosan films are of potential interest for the packaging of Foods in which Aroma is one of the most important quality attributes.
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immobilization of β cyclodextrin in ethylene vinyl alcohol copolymer for active Food packaging applications
Journal of Membrane Science, 2010Co-Authors: Carol Lopezdedicastillo, Rafael Gavara, Miriam Gallur, Ramon Catala, Pilar HernandezmunozAbstract:Abstract Current developments in active Food packaging are focusing on incorporating agents into the polymeric package walls that will release or retain substances to improve the quality, safety and shelf-life of the Food. Because cyclodextrins are able to form inclusion complexes with various compounds, they are of potential interest as agents to retain or scavenge substances in active packaging applications. In this study, β-cyclodextrin (βCD) was successfully immobilized in an ethylene-vinyl alcohol copolymer with a 44% molar percentage of ethylene (EVOH44) by using regular extrusion with glycerol as an adjuvant. Films with 10%, 20% and 30% of βCD were flexible and transparent. The presence of the agent slightly increased the glass-transition temperature and the crystallinity percentage of the polymer, that is to say, it induced some fragility and a nucleating effect. The water vapor, oxygen and carbon dioxide barrier properties of the materials containing βCD were determined and compared with those of the pure polymeric material. Permeability to these three permeants increased with the addition of βCD due to the presence of discontinuities in the matrix and to the internal cavity of the oligosaccharide. Also the CO 2 /O 2 permselectivity increased with the addition of βCD. Finally, the potential effect of the composites in the Food Aroma was analyzed. The materials with βCD preferentially sorbed apolar compounds such as terpenes. This characteristic could be useful in active packaging applications for preferentially retaining undesired apolar Food components like hexanal or cholesterol.
Carlo Bicchi - One of the best experts on this subject based on the ideXlab platform.
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high concentration capacity sample preparation techniques to improve the informative potential of two dimensional comprehensive gas chromatography mass spectrometry application to sensomics
Journal of Chromatography A, 2013Co-Authors: Chiara Cordero, Luca Nicolotti, Cecilia Cagliero, Erica Liberto, Patrizia Rubiolo, Barbara Sgorbini, Carlo BicchiAbstract:Abstract This study reports and critically discusses the results of a systematic investigation on the effectiveness of different and complementary sampling approaches, based on either sorption and adsorption, treated as a further dimension of a two-dimensional comprehensive gas chromatography–mass spectrometry analytical platform for sensomics. The focus is on the potentials of a group of high concentration capacity (HCC) sample preparation (Solid Phase Microextraction, SPME, Stir Bar Sorptive Extraction, SBSE and Headspace Sorptive Extraction, HSSE) and Dynamic Headspace (D-HS) techniques investigated to provide information useful for fingerprinting and profiling studies of Food Aroma. Volatiles and semi-volatiles contributing to define whole and nonfat dry milk Aroma have been successfully characterized thanks to the combination of effective and selective sampling by HCC and D-HS techniques, high separation and detection power of GC × GC–MS and suitable data elaboration (i.e., Comprehensive Template Matching Fingerprinting – CTMF). Out of the sample preparation techniques investigated, HSSE and SBSE have shown to be really effective for sensomics studies because of their high concentration factors, providing highly representative profiles as well as analyte recovery suitable for GC-Olfactometry even with high odor threshold (OT) markers or potent odorants in sub-trace amounts.