Which variables should be controlled when measuring the granulometry of a chewed bolus? A systematic review. Issue 3 (23rd November 2018)

• Record Type: Journal Article
• Authors: Bonnet, Guillaume; Batisse, Cindy; Peyron, Marie‐Agnès; Nicolas, Emmanuel; Hennequin, Martine
• Is Part Of: Journal of texture studies. Volume 50:Issue 3(2019)
• Page Start: 194
• Page End: 216
• Publication Date: 2018-11-23
• Subjects: chewing -- food bolus granulometry -- image analysis -- mastication -- sieving -- swallowing; Food texture -- Periodicals; Food -- Composition -- Periodicals; 664.02
• DOI: 10.1111/jtxs.12376
• Languages: English
• ISSNs: 0022-4901

Abstract

Abstract: The distribution of food particles in a chewed bolus characterizes the food destruction after food oral processing (FOP). Previous reviews report that it could be affected by a lot of parameters as the number of chewing strokes, the dental status, but the conditions for producing reproducible data allowing inter‐studies comparison have not been clearly described yet. This systematic review aims to identify the variables that can affect bolus granulometry determination, and to calculate their relative weights in the median particle size (D50 ) variations. The systematic review focuses on granulometry expressed as D50 of the most used foods (peanuts, carrots, and almonds) and materials (Optosil and Optocal). Based on 58 studies, 5 variables among 60 being extracted could explain the D50 variations. Conceptual differences between the conditions for FOP should be considered. After Chewing‐test, the bolus is collected after a predefined number of strokes and its granulometry characterizes the effects of the dental and muscular apparatus on food destruction, while after Mastication‐test the bolus is collected at the swallowing threshold, and its granulometry reflects the outcome of the abilities of the subject to adapt his/her mastication behavior to food texture. Experimental conditions related either to physical sieving or image analysis used to analyze the collected boluses impact the D50 values. Finally, when type of test, sieving conditions, type of food or material, number of chewing strokes, and the oral status of the subjects are controlled, mean D50 values are reproducible and could be used for inter‐studies comparisons. Practical applications: This review provides tables that could be useful to control mean D50 variations in further research.