Automatic pretreatment and multiblock analysis of flavor release and sensory temporal data simultaneously collected in vivo
Proton transfer reaction‐time‐of‐flight‐mass spectrometry (PTR‐ToF‐MS or PTR‐MS) is an analytical chemistry technique that can be used for measuring the concentration of volatile organic compounds directly in the subjects' noses (nosespace, in vivo analysis) during a tasting and over time. It c...
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Published in | Journal of chemometrics Vol. 38; no. 5 |
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Abstract | Proton transfer reaction‐time‐of‐flight‐mass spectrometry (PTR‐ToF‐MS or PTR‐MS) is an analytical chemistry technique that can be used for measuring the concentration of volatile organic compounds directly in the subjects' noses (nosespace, in vivo analysis) during a tasting and over time. It can be combined with temporal sensory methods such as temporal dominance of sensations (TDS) or temporal check all that apply (TCATA) in order to obtain simultaneous sensory and physico‐chemical signals. This paper aims to provide a methodology to analyze in vivo PTR‐MS and temporal sensory data and illustrate it on a real dataset. First, relevant pretreatments of PTR‐MS data were established, including breathing correction, blank periods removal, and standardization. Then, a statistical multiblock analysis was presented: the regularized generalized canonical correlation analysis (RGCCA). The versality of the approach was demonstrated, as it can be used to answer most of problematics (exploratory or supervised). Finally, this methodology is illustrated on a dataset of PTR‐MS and TDS or TCATA data collected simultaneously. In this study, 16 semitrained subjects evaluated three chocolates in TDS and TCATA on six flavor attributes (Spicy, Cocoa, Woody, Fruity, Roasty, and Dry Fruits) with two replicates for each sensory method. Results showed that TCATA and TDS gave similar results, but TDS was shown to slightly better preserve the PTR‐MS observed product configuration than TCATA. All computing tools developed in this work are freely available. |
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AbstractList | Proton transfer reaction‐time‐of‐flight‐mass spectrometry (PTR‐ToF‐MS or PTR‐MS) is an analytical chemistry technique that can be used for measuring the concentration of volatile organic compounds directly in the subjects' noses (nosespace, in vivo analysis) during a tasting and over time. It can be combined with temporal sensory methods such as temporal dominance of sensations (TDS) or temporal check all that apply (TCATA) in order to obtain simultaneous sensory and physico‐chemical signals. This paper aims to provide a methodology to analyze in vivo PTR‐MS and temporal sensory data and illustrate it on a real dataset. First, relevant pretreatments of PTR‐MS data were established, including breathing correction, blank periods removal, and standardization. Then, a statistical multiblock analysis was presented: the regularized generalized canonical correlation analysis (RGCCA). The versality of the approach was demonstrated, as it can be used to answer most of problematics (exploratory or supervised). Finally, this methodology is illustrated on a dataset of PTR‐MS and TDS or TCATA data collected simultaneously. In this study, 16 semitrained subjects evaluated three chocolates in TDS and TCATA on six flavor attributes (Spicy, Cocoa, Woody, Fruity, Roasty, and Dry Fruits) with two replicates for each sensory method. Results showed that TCATA and TDS gave similar results, but TDS was shown to slightly better preserve the PTR‐MS observed product configuration than TCATA. All computing tools developed in this work are freely available. Proton transfer reaction‐time‐of‐flight‐mass spectrometry (PTR‐ToF‐MS or PTR‐MS) is an analytical chemistry technique that can be used for measuring the concentration of volatile organic compounds directly in the subjects' noses (nosespace, in vivo analysis) during a tasting and over time. It can be combined with temporal sensory methods such as temporal dominance of sensations (TDS) or temporal check all that apply (TCATA) in order to obtain simultaneous sensory and physico‐chemical signals. This paper aims to provide a methodology to analyze in vivo PTR‐MS and temporal sensory data and illustrate it on a real dataset. First, relevant pretreatments of PTR‐MS data were established, including breathing correction, blank periods removal, and standardization. Then, a statistical multiblock analysis was presented: the regularized generalized canonical correlation analysis (RGCCA). The versality of the approach was demonstrated, as it can be used to answer most of problematics (exploratory or supervised). Finally, this methodology is illustrated on a dataset of PTR‐MS and TDS or TCATA data collected simultaneously. In this study, 16 semitrained subjects evaluated three chocolates in TDS and TCATA on six flavor attributes ( Spicy, Cocoa, Woody, Fruity, Roasty , and Dry Fruits ) with two replicates for each sensory method. Results showed that TCATA and TDS gave similar results, but TDS was shown to slightly better preserve the PTR‐MS observed product configuration than TCATA. All computing tools developed in this work are freely available. |
Author | Hélard, Cantin Peltier, Caroline Andriot, Isabelle Le Quéré, Jean‐Luc Cordelle, Sylvie Schlich, Pascal Visalli, Michel Labouré, Hélène |
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SubjectTerms | Analytical chemistry Correlation analysis Datasets flavor release Flavors In vivo methods and tests Mass spectrometry Organic compounds Pretreatment PTR‐MS RGCCA Software TCATA TDS VOCs Volatile organic compounds |
Title | Automatic pretreatment and multiblock analysis of flavor release and sensory temporal data simultaneously collected in vivo |
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