Prediction of cooked rice texture using an extrusion test in combination with partial least squares regression and artificial neural networks

Spectral stress strain analysis was used in combination with partial least squares (PLS) regression and artificial neural networks (ANN) to predict ni ne sensory texture attributes of cooked rice. The models calculated with AN N were significantly more accurate in predicting most of the sensory textur e characteristics evaluated than the PLS models. Furthermore, ANN models we re more robust and discriminative than PLS models.