Effect of Aging on the Quality of Glutinous Rice Crackers

The experiment was conducted to study the effects of aging on the physicochemical properties of two Thai cultivars of milled glutinous rice (RD6 and RD8). The amylose and protein content of rice samples did not change when stored from 0 to 4 months. Amylograph curves from samples of milled rice stored from 0 to 8 months were analyzed. Both cultivars gave constant gelatinization temperature during aging. The values for peak viscosity, final viscosity on cooking at 94°C, viscosity on cooling to 50°C and breakdown decreased significantly for RD6 cultivar, whereas the setback value and consistency were not changed significantly. For RD8 cultivar, no significant difference was observed for viscosity on cooling to 50°C and consistency during aging up to 8 months. Peak viscosity and breakdown value were reduced during storage, whereas the final viscosity on cooking at 94°C and setback value increased with time. Raw milled rice of both RD6 and RD8 cultivars have similar water uptake rates. Stored rice tended to have a lower water uptake rate which increased proportionately with soaking time. Samples from both rice cultivars were used to make rice crackers to study the effects of aging on quality. Volume expansion of rice crackers made from RD6 and RD8 cultivars tended to decrease during storage which resulted in an increase in the hardness of the crackers.     

Rapid Variety Identification of Pure Rough Rice by Fourier‐Transform Near‐Infrared Spectroscopy

Rice variety is considered as an important factor influencing cooking and processing quality because of variations in size, shape, and constitution. Difficulty in management of rough rice with lower varietal purity becomes a significant problem in rice production and can result in the reduction of rice quality. Fourier‐transform near‐infrared (FT‐NIR) spectroscopy was used to identify the variety of rough rice through whole‐grain techniques. Moist rough rice samples (n = 259) comprising five varieties (Khao Dawk Mali 105 [KDML105], Pathum Thani 1, Suphan Buri 60, Chainat 1, and Pitsanulok 2) were gathered from different locations around Thailand and scanned in the NIR region of 9088–4000 cm^–1 in reflectance mode. Soft independent modeling of class analogies (SIMCA) and partial least squares discriminant analysis (PLSDA) methods were used for identification by utilizing preprocessed spectra. The highest identification accuracy achieved was 74.42% by the SIMCA model and 99.22% by the PLSDA model. The best PLSDA model demonstrated approximately 97% correct identification for KDML105 samples and 100% for the others. This study raises the possibility of applying FT‐NIR spectroscopy as a nondestructive technique for rapidly identifying moist rough rice varieties in routine quality assurance testing.     

Modeling Selected Properties of Extruded Rice Flour and Rice Starch by Neural Networks and Statistics

Rice flour and rice starch were single‐screw extruded and selected product properties were determined. Neural network (NN) models were developed for prediction of individual product properties, which performed better than the regression models. Multiple input and multiple output (MIMO) models were developed to simultaneously predict five product properties or three product properties from three input parameters; they were extremely efficient in predictions with values of R² > 0.95. All models were feedforward backpropagation NN with three‐layered networks with logistic activation function for the hidden layer and the output layers. Also, model parameters were very similar except for the number of neurons in the hidden layer. MIMO models for predicting product properties from three input parameters had the same architecture and parameters for both rice starch and rice flour.     

Effect of Physicochemical Properties of High‐Amylose Thai Rice Flours on Vermicelli Quality

Certain physicochemical properties, including chemical composition, pasting, thermal parameters, and the gel texture of flour prepared from six cultivars of Thai rice with similar high‐amylose content were determined. These properties were correlated with the quality of vermicelli prepared from these flours for cooking and textural properties. Flour prepared from a Thai rice cultivar currently used for commercial production of vermicelli served as reference for these comparisons. Many similarities, but some significant differences, in the physicochemical properties were observed between the test rice flours and to the reference cultivar. Vermicelli prepared from all of the test rice flours were within an acceptable range for cooking quality but showed greater variation in textural quality. Among the physicochemical properties, gel hardness was well correlated with cooking and textural quality of vermicelli, and was useful for predicting overall vermicelli quality.