Characterization of bread breakdown during mastication by image texture analysis

► GLCM can be used successfully to investigate bolus formation during chewing. ► 60–73% of images were correctly classified in their respective chewing cycles. ► The contrast textural feature of images was the best marker of food breakdown. ► Kinetics of bolus formation varied between breads and subjects. The methods currently used to characterise food breakdown during mastication are not easily applicable to cohesive and heterogeneous products such as white bread (baguettes). During this study, we investigated the applicability of image texture analysis to characterising the kinetics of bread bolus formation during chewing. Food boluses were collected from five subjects chewing four different breads after 10, 20 and 30 chewing cycles or at swallowing. Images were acquired and analysed using the Grey level co-occurrence matrix (GLCM) method. Food boluses were successfully discriminated: 60–73% of the images were correctly classified into their respective chewing cycles. Incorrect classifications arose from overlapping between subsequent cycles. Among the texture features the contrast was identified as being the best marker of food degradation. Different kinetics of bolus formation were observed between breads. This method revealed specific patterns of food degradation between subjects, which could be explained by their mastication behaviour and chewing efficiency.