An alternate mechanism for the astringent sensation of acids

Siebert, Karl J.; Chassy, Alexander W.

doi:10.1016/s0950-3293(02)00221-5

Cited by 30 publications

(31 citation statements)

References 32 publications

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“…However, the positive effect of pH and O 2 on T max was confirmed, which means that astringency seems to appear faster at pH 3.0 than at pH 5.0 ( p ¼ 0.25) and at low O 2 than at high O 2 ( p ¼ 0.16) ( Table II). The astringency intensification observed with decreasing pH is consistent with the fact that at pH 4.4 interactions between polyphenols and proline-rich proteins are strengthened [14]. When beers at pH 3.0 are mixed with saliva, their pH shifts to around 4.4.…”

Section: Classical Approachsupporting

confidence: 78%

Inferential non‐centred principal curve analysis of time‐intensity curves in sensory analysis: the methodology and its application to beer astringency evaluation

François

Govaerts

Guyot-Declerck³

2007

Journal of Chemometrics

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Improving technologies and better understanding of sensory phenomena have lead sensory analysts to develop statistical methods to assess sensations that endure over time (e.g. the bitterness or astringency of a beer) dynamically. The data produced by this type of experiment is classically a time-intensity (TI) curve, and their analysis remains an active research topic. The classical approach, widely used in this context, starts by extracting some significant parameters from the initial curves (maximum intensity, area under the curve (AUC), etc.). Descriptive data analysis or statistical modelling is then applied to get information from these summary parameters. This paper presents a different method, called inferential non-centred principal curve analysis (INCPCA), for the analysis of TI curves. It combines multivariate analysis (to visualise the curves in a space of smaller dimensions) with statistical modelling (aimed at enhancing the significance of factor effects). Non-centred principal curves (NCPCs) are first extracted from the curves matrix. They decompose the TI curves into different interpretable components. Score plots are used to represent the projection of the initial curves in the space of the first principal curves and allow factors and judge effects to be visualised. Mixed modelling is then applied to test the significance of these effects using PCA scores as model responses. The classical and INCPCA methods are illustrated on a TI experiment exploring the relation between beer astringency and three factors of interest: pH, O 2 content and aging. Eight beers arranged in a 2 3 factorial design were tested in triplicate by eight trained judges.

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Section: Classical Approachsupporting

confidence: 78%

Inferential non‐centred principal curve analysis of time‐intensity curves in sensory analysis: the methodology and its application to beer astringency evaluation

François

Govaerts

Guyot-Declerck³

2007

Journal of Chemometrics

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“…Flavorants such as alum and tannic acid are known for their astringent or drying/puckering mouth feel and after feel. For tannic acid, this has been explained by complex formation and possibly co-precipitation with especially the basic prolinerich proteins present in saliva [86][87][88]. The remaining saliva is less viscous and has lost some of its lubricating ability.…”

Section: Precipitation Of Saliva Proteinsmentioning

confidence: 99%

Food colloids under oral conditions

Aken

Vingerhoeds

Hoog

2007

Current Opinion in Colloid & Interface Science

111

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“…The intraoral salivary coating interacts with dietary components, which consequently influence both taste and tactile perception, i.e., mouth-feel [26][27][28][29][30][31][32][33]. This is particularly apparent following the drinking of certain teas or wines that give a dry, puckering mouth-feel referred to as astringency.…”

Section: Introductionmentioning

confidence: 99%

The Lubricating Properties of Human Whole Saliva

2007

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We demonstrate the efficient boundary lubricating properties of human whole saliva (HWS) in a soft hydrophobic rubbing contact, consisting of a poly(dimethylsiloxane) (PDMS) ball and a PDMS disk. The influence of applied load, entrainment speed and surface roughness was investigated for mechanically stimulated HWS. Lubrication by HWS results in a boundary friction coefficient of l % 0.02, two orders of magnitude lower than that obtained for water. Dried saliva on the other hand results in l % 2-3, illustrating the importance of hydration for efficient salivary lubrication. Increasing the surface roughness increases the friction coefficient for HWS, while it decreases that for water. The boundary lubricating properties of HWS are less sensitive to saliva treatment than are its bulk viscoelastic properties. Centrifugation and ageing of HWS almost completely removes the shear thinning and elastic nature observed for fresh HWS. In contrast, the boundary friction coefficients are hardly affected, which indicates that the high-M w (supra-)molecular structures in saliva, which are expected to be responsible for its rheology, are not responsible for its boundary lubricating properties. The saliva-coated PDMS surfaces form an ideal model system for ex-vivo investigations into oral lubrication and how the lubricating properties of saliva are influenced by other components like food, beverages, oral care products and pharmaceuticals.

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An alternate mechanism for the astringent sensation of acids

Cited by 30 publications

References 32 publications

Inferential non‐centred principal curve analysis of time‐intensity curves in sensory analysis: the methodology and its application to beer astringency evaluation

Inferential non‐centred principal curve analysis of time‐intensity curves in sensory analysis: the methodology and its application to beer astringency evaluation

Food colloids under oral conditions

The Lubricating Properties of Human Whole Saliva

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