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Prediction of Cooked Rice Texture Using Extrusion and Compression Tests in Conjunction with Spectral Stress Strain Analysis
Author(s) -
Sitakalin Chanintorn,
Meullenet JeanFrancois C.
Publication year - 2000
Publication title -
cereal chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.558
H-Index - 100
eISSN - 1943-3638
pISSN - 0009-0352
DOI - 10.1094/cchem.2000.77.4.501
Subject(s) - extrusion , partial least squares regression , texture (cosmology) , chemistry , compression (physics) , food science , statistics , mathematics , artificial intelligence , composite material , materials science , computer science , image (mathematics)
Sensory texture attributes of cooked rice from two cultivars (Bengal and Cypress) harvested in 1997 (56 samples) were predicted using extrusion and compression tests along with spectral stress strain analysis. Predictive models for each of nine sensory texture attributes studied were evaluated using force values from the instrumental tests in conjunction with partial least squares regression. All sensory attributes were well predicted using both the extrusion and compression tests (relative ability of prediction > 0.70). However, the extrusion test consistently provided more accurate and discriminative predicted models (root mean square error of prediction < 0.55, S tot /RMSEP > 2.0). Spectral stress strain analysis predictive models for adhesiveness to lips and hardness were explained.