Understanding aroma release from model cheeses by a statistical multiblock approach on oral processing

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Abstract

For human beings, the mouth is the first organ to perceive food and the different signalling events associated to food breakdown. These events are very complex and as such, their description necessitates combining different data sets. This study proposed an integrated approach to understand the relative contribution of main food oral processing events involved in aroma release during cheese consumption. In vivo aroma release was monitored on forty eight subjects who were asked to eat four different model cheeses varying in fat content and firmness and flavoured with ethyl propanoate and nonan-2-one. A multiblock partial least square regression was performed to explain aroma release from the different physiological data sets (masticatory behaviour, bolus rheology, saliva composition and flux, mouth coating and bolus moistening). This statistical approach was relevant to point out that aroma release was mostly explained by masticatory behaviour whatever the cheese and the aroma, with a specific influence of mean amplitude on aroma release after swallowing. Aroma release from the firmer cheeses was explained mainly by bolus rheology. The persistence of hydrophobic compounds in the breath was mainly explained by bolus spreadability, in close relation with bolus moistening. Resting saliva poorly contributed to the analysis whereas the composition of stimulated saliva was negatively correlated with aroma release and mostly for soft cheeses, when significant. © 2014 Feron et al.

Figures

  • Table 1. Overview of the experimental design of the study and the corresponding code for the cheese products.
  • Table 2. Oral physiological characteristics of the 48 subjects included in the study: Descriptive statistics.
  • Figure 1. Typical aroma release curve profile. The release profile was separated in two release phases: before (phase 1) and after (phase 2) first swallowing. The quantity of aroma released (A1 & A2), the maximum intensity (Imax1 & Imax2), the time to reach maximum intensity (Tmax1 & Tmax2) and the release rate (Imax1/Tmax1 & Imax2/Tmax2) were extracted from the curve for each release phase. doi:10.1371/journal.pone.0093113.g001
  • Table 3. Presentation of the different blocks of variables used in the MB-PLS analyses.
  • Table 4. Percentage of inertia on the first three dimensions.
  • Figure 2. Bar charts representing the importance of the different blocks of variables (X1–X5) for the different dimensions obtained by means of MB-PLS analysis performed on ethyl propanoate release data set and for the four cheeses products. Green chart: rheology, Orange chart: coating, oral volume and % moistening, Red chart: EMG data, Grey chart: resting saliva composition, Violet chart: stimulated saliva composition. doi:10.1371/journal.pone.0093113.g002
  • Figure 3. Bar charts representing the importance of the different blocks of variables (X1–X5) for the different dimensions obtained by means of MB-PLS analysis performed on nonan-2-one release data set and for the 4 cheeses products. Green chart: rheology, Orange chart: coating, oral volume and % moistening, Red chart: EMG data, Grey chart: resting saliva composition, Violet chart: stimulated saliva composition. doi:10.1371/journal.pone.0093113.g003
  • Figure 4. MB-PLS results on dim1/dim2 and dim1/dim3: relationships between the X-blocks of explanatory variables (Green arrows: rheology, Orange arrows: coating, oral volume and % moistening, Red arrows: EMG data, Violet arrows: stimulated saliva composition) and the Y-block of variables to be explained (Blue arrows: aroma release) for ethyl propanoate and low fat cheeses.

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CITATION STYLE

APA

Feron, G., Ayed, C., Qannari, E. M., Courcoux, P., Laboure, H., & Guichard, E. (2014). Understanding aroma release from model cheeses by a statistical multiblock approach on oral processing. PLoS ONE, 9(4). https://doi.org/10.1371/journal.pone.0093113

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