Quality Properties Of Rice Research Articles

Evaluating the fluidized-bed drying of rice using response surface methodology and artificial neural network

In this work, the effect of fluidized bed dryer under different fluidization regimes and temperature on drying time and quality properties of rice has been investigated. To predict the outputs, a feed-forward multilayered perceptron and a central composite design were created. The chosen final artificial neural network (2-8-7-5) was compared to the response surface methodology for its modeling and predictive skills. Capturing the system's nonlinear behavior and simultaneous performance prediction demonstrate the superiority of a response surface methodology. The experiments proved that fluidized bed dryer with ventilation significantly increased the head rice yield (from 30 to 505%) and the whiteness index (from 2 to 17%) compared to fluidized bed dryer without ventilation. After that, we optimized the drying conditions by response surface methodology. The best optimum conditions are related to lowest drying time and the highest quality parameters. The optimal drying conditions are as follows: 52 °C inlet temperature, 3.1 m/s inlet fluidization velocity (bubble fluidization regime), and fluidized bed dryer with ventilation. At this optimum condition, the values of experimental test were found to be 218 min (drying time), 74% (head ice yield), 60.7 (whiteness index), 3.15 (water uptake ratio) and 1.84 (elongation ratio) with desirability factor of 0.695.

The acceptance of zinc biofortified rice in Latin America: A consumer sensory study and grain quality characterization.

Zinc deficiency is a major public health problem in vulnerable populations of Latin America and the Caribbean. Biofortification of rice (Oryza sativa L.) with zinc has the potential to alleviate zinc deficiencies. However, as plant breeding processes can alter grain culinary quality and favorable sensory attributes, grain quality and consumer acceptability need to be assessed prior to releasing a variety to the public. A grain quality characterization and a sensory acceptability analysis were carried out with two varieties of zinc biofortified rice and a local control both in Bolivia and Colombia. The aim of this study was to evaluate the physicochemical parameters that are significant in consumer acceptance and to determine the acceptability of zinc biofortified rice by consumers. Results of physicochemical parameters were analyzed using ANOVA. The sensory acceptability was evaluated in 243 adults utilizing a 7-point hedonic scale and a Wilcoxon’s signed rank test was used to determine the overall acceptability of the varieties. Biofortified rice variety T2-11 and MAC-18 -control 1- were equally accepted by consumers in Bolivia with no significant differences (p<0.05). The grain quality analysis reported that both presented long and slender rice grains (L>7.5 mm and L/B>3), an intermediate to high amylose content (>25%) and a similar level of chalkiness. In Colombia, the biofortified variety 035 presented a higher score in overall acceptance in comparison to biofortified variety 021 and the local variety CICA4 -control 2-. However, no significant differences were observed (p<0.05). Conversely to the other two varieties, the biofortified variety 035 presented the largest size grain (L/B = 2.97), a lower chalkiness and an amylose content above 25%. This study shows that the grain quality properties of rice have an influence on acceptability and that zinc biofortified rice varieties are accepted by consumers.

Identification of rice varieties and determination of their geographical origin in China using Raman spectroscopy

The processing and quality properties of rice are significantly influenced by its variety and region of origin. However, discriminating between varieties and geographic regions is an urgent but difficult and time-consuming endeavor in China. In this study, an effective and reliable identification method was established by combining Raman spectroscopy (RS) with multivariate data analysis methods. Numerous RS spectra were collected, and the sensitive fundamental vibrations of less polar groups and bonds in rice were analyzed. Principal component analysis (PCA) was used for preliminary identification. Subsequently, different modeling methods were compared and seemed to reliably identify rice types, varieties, and region of origin, with accuracies of between 80 and 100%. As a result, a soft independent modeling of class analogy (SIMCA) model was shown to be the superior model for rice identification. The SIMCA model can deliver high precision detection of adulterated rice (i.e., rice of high quality blended with rice of inferior quality), and this study lays the foundations for an advanced rice quality identification technology system.

Effects of cooking method on physical properties, color, and microstructural characteristics of scorched rice chips

Effects of cooking method on quality properties of rice and scorched rice chips were investigated. Raw rice and rice flour were treated using steaming, pressure-cooking, microwave-cooking, and extrusion to produce scorched rice chips. Extrusion-cooked rice grain differed from other grains in physical properties. Extruded rice grains exhibited a rough and porous surface. Scorched rice chips made using extruded rice showed the highest chroma value and absorbed more water in 1 min than other rice chip samples. Extrusion is a novel approach for improving quality properties of moisture content, texture, color, rehydration, and microstructure of scorched rice chips.

Amylose Content and Grain Length of New Rice Transgressive Variants Derived from a Cross Between O. rufipogon and Malaysian Rice Cultivar MR219

Amylose content is one of the important grain quality properties of rice. A total of 10 new rice genotypes (BC2F7 generation) derived from a cross between O. rufipogon Griff. accession IRGC105491 and O. sativa subspecies indica cv. MR219 with high yield were evaluated for amylose content in three environments in Peninsular Malaysia. One of the parents, a popular high yielding Malaysian rice cultivar MR219 was used as a check. Based on the average amylose content across the environments, the genotype G13 showed significantly (p < 0.05) different amylose content (23.88 %) in comparison to other genotypes. Two genotypes G13 (25.7%) and G15 (25.6%) were higher than MR219 (25.1%) in terms of amylose content in Sungai Besar environment. There was a positive (r2=0.018) but no significant correlation between amylose content and grain length.