Instrumental assessment of cooked rice texture characteristics: A method for breeders

Abstract

Sensory textural characteristics of cooked rice (61 samples) were predicted using a miniature extrusion cell and the novel data analysis method Spectral Stress Strain Analysis (SSSA). Thirteen sensory texture characteristics evaluated using a trained descriptive panel and stress values from an extrusion test were used in combination with partial least squares regression to evaluate predictive models for each of the sensory attributes studied. Among the textural attributes evaluated by the panel, four (stickiness, hardness, cohesiveness of mass, and uniformity of bite [relative ability of prediction values (RAP) > 0.6, n = 61]) could be satisfactorily predicted using an instrumental test and subsequent SSSA. The quality of the models determined varied for the two grain types evaluated. This instrumental method provides a valuable screening tool for rice breeders.