Modelling the role of oral processing on in vivo aroma release of white rice: Conceptual model and experimental validation
2021
Syahmeer How, Muhammad | Jones, Jim, R | Morgenstern, Marco, P | Gray-Stuart, Eli | Bronlund, John, E | Saint-Eve, Anne | Trelea, Ioan-Cristian | Souchon, Isabelle | Massey University | Universiti Putra Malaysia | Riddet Institute and Massey Institute of Food Science and Technology ; Massey University | The New Zealand Institute for Plant & Food Research Limited [Auckland] (Plant & Food Research) | Paris-Saclay Food and Bioproduct Engineering (SayFood) ; AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Sécurité et Qualité des Produits d'Origine Végétale (SQPOV) ; Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
International audience
Afficher plus [+] Moins [-]anglais. A conceptual model was developed to relate oral processing parameters and aroma release of cooked white rice. The conceptual model indicates that aroma release is dependent on the increase of particle surface area, the dilution effect of saliva and the diffusion of aroma from food residues that can be trapped in the buccal-pouches in the mouth. The model was validated against in vivo retro-nasal aroma release data during the consumption of rice flavoured with two aroma compounds (2-nonanone and ethyl propanoate) by five panellists. The oral processing behaviour of each subject was characterised at four different stages during oral processing by measuring bolus particle size, saliva content and the amount of residue particles that could be washed from the mouth after bolus expectoration. The results showed that aroma release for all subjects were dependent on the particle breakdown pathways used in oral processing. Subjects who reduced the rice to smaller particle sizes, higher pasted fraction and higher bolus residues had higher aroma release as expected from the conceptual model. Accounting for the physiological variables of subjects, the physicochemical parameters of aroma compounds and using a larger number of subjects in future studies will improve the model reliability.
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