Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4317632 | Food Quality and Preference | 2011 | 8 Pages |
We investigated chewing behaviour and particle size outcome in the oral processing of heterogeneous foods using peanuts embedded within two types of food matrices. Eight subjects, selected according to strict dental and mastication criteria, were served four different model foods. Each model food comprised one of two matrices of different physical properties (chocolate and gelatine gel) which were embedded with one of two physically different particles (peanuts with low moisture or high moisture content). A standard volume of each model food was chewed to the point of swallowing and expectorated and the number of chews and chewing time was recorded. The matrix of the expectorated bolus was washed away to isolate the peanut fragments, and the particle size distributions of the peanut fragments were determined using image analysis. A Rosin–Rammler function was fitted to the cumulative distribution data of each bolus to derive particle size parameters (d50 and broadness (b)).Results showed the properties of one food component (the matrix) can influence the breakdown of another food component (the peanuts) in a heterogeneous system. The properties of the matrix caused differences in mastication (measured in terms of the number of chews, chewing duration, and frequency) and broadness of the peanut particle size distribution, but did not influence the final d50 of the peanut particle size distribution. Conversely the physical properties of the embedded peanut influenced the d50 of the particle size distribution but had no effect on chewing behaviour. It is likely that properties of the matrix influenced the rate at which particles of various sizes were selected for chewing (known as the selection function), whereas the physical properties of the peanuts influenced extent of breakage when the teeth made contact with the particles (known as the breakage function).
Research highlights► One food component can influence the breakdown of another food component. ► Matrices influenced mastication and broadness of the particle size distribution. ► Peanuts influenced the d50 but not chewing behaviour.