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Prediction Of Rice Sensory Texture Attributes Using Spectral Stress Strain Analysis And Jack-Knife Model Optimization, Marura Lenjo, Jean-Francois Meullenet
Prediction Of Rice Sensory Texture Attributes Using Spectral Stress Strain Analysis And Jack-Knife Model Optimization, Marura Lenjo, Jean-Francois Meullenet
Discovery, The Student Journal of Dale Bumpers College of Agricultural, Food and Life Sciences
Sensory texture characteristics of cooked rice were predicted using an extrusion test and a novel multivariate analysis method. Eleven sensory texture characteristics were evaluated via a trained descriptive panel and predicted for force/deformation spectra with partial least squares regression. Only four sensory attributes—adhesion to lips (Rcal = 0.83), cohesion of bolus (Rcal = 0.78), cohesiveness (Rcal = 0.69), and hardness (Rcal = 0.72)—were successfully predicted from instrumental measurements.