Sensory Descriptive Texture Analyses of Cooked Rice and Its Correlation to Instrumental Parameters Using an Extrusion Cell

Abstract

J. Gross, B.P. Marks and M. Daniels. Cereal Chem. 75, 714-720 (1998).A trained texture profiling panel and an extrusion cell fitted into the TA.XT2 Texture Analyzer were used to quantify textural characteristics of three cooked rice cultivars exhibiting small differences in tlexture. Nine sensory and five instrumental parameters were used to establish predictive models for the sensory characteristics evaluated. Most effectively pred3icted were hardness (R2=@.62) and toothpack (R2=0.70). Partial least square regression techniques gave the following RAP (relative ability of prediction) values: hardness 0.52, cohesiveness of mass 0.60, toothpull 0.73, and toothpack 0.54. These values take into account the accuracy of the sensory methodology and provide a more accurate evaluation of the quality of the predictive models. Poor predictability was related to small textural differences between test samples, and need for better statistical methods applicable to such situations.A. S. Sz.

Comparison of a Double Compression Test for the Prediction of Sensory Texture Attributes of Cooked Rice to a Single Compression Test

“…An extrusion test may have a better performance in predicting cooked rice hardness than a SC test. This result is supported by previous research (Meullenet et al, 1998;Sitakalin and Meullenet, 2000) showing that a forward extrusion test had good potential to predict sensory attributes in cooked rice, especially hardness. The WRC for predicting hardness by a DC test showed that A1 (compression work for the first compression cycle) was the most important contributor (Table 4).…”

“…Satisfactory prediction models for the hardness of cooked rice were reported by some other studies. Meullenet et al (1998) reported the hardness (R 2 =0.62) and tootpack (R 2 =0.70) for cooked rice of different varieties were the attributes most effectively predicted by an extrusion test. Sitakalin and Meullenet (2000) also found that the hardness for cooked rice from two cultivars was well predicted (RAP=0.85, 0.74 for each test) using both an extrusion test and compression test.…”

Estimating sensory texture of cooked rice using full and optimized predictive regression models

“…Room temperature was not effective for measuring texture of cooked rice (Meullenet, et al, 1998;Meullenet, et al, 1999). In addition, room temperature could be different from the temperature of cooked rice for descriptive analysis.…”

“…One of the widely used instrumental texture measurement methods was Ottawa extrusion cell (Juliano, et al, 1984;Meullenet, et al, 1998). However, the dimensions of traditional Ottawa cell require a large amount of samples (approximately 100 g) for evaluation.…”

“…Traditionally PLSR was used for the estimation by using the entire results (Kwak et al, 2015a;Meullenet, et al, 1998). If there are noise results that distort the average results, these outliers would be negatively influence the validation of the estimation model.…”