New insights into cooked rice quality by measuring modulus, adhesion and cohesion at the level of an individual rice grain

The surface mechanics of cooked rice as influenced by gastric fluids measured using a micro texture analyzer

In this study, a micro texture analyzer (MTA) was employed to explore the texture characteristics of the surface of an individual steamed rice (SR) and fried rice (FR) grain exhibited in four simulated digestion environments in vitro. The elastic modulus, hardness and elastic index of the single cooked rice particle were measured using the MTA. The hardness of SR particles decreased by 66, 81, 89.1, and 95% after simulated digestion in distilled water, HCl, simulated gastric fluid (SGF), and simulated salivary and gastric fluid (SSF + SGF), respectively. This is in line with the most significant volume expansion and structure ruptures when digested in SSF + SGF. Similar mechanical and structural behaviors were shown for FR, but the hardness and elastic modulus decreased less than those of SR under the same digestion conditions. The different surface mechanics are consistent with the reduced expansion and more compact structure with smaller voids in FR during in vitro digestion. This could be attributed to the encapsulation by frying oil on the surface that would retard the diffusion of digestive fluids into the rice kernels. A weak negative correlation was found between the elastic modulus and the moisture content of the cooked rice. The present study has quantitatively assessed the surface mechanics of cooked rice as influenced by gastric fluids using the MTA. This is practically meaningful for gaining an in-depth understanding of the influence of textural modifications on disintegration of solid foods and release of nutrients during digestion.

Aroma, Quality, and Consumer Mindsets for Shelf-Stable Rice Thermally Processed by Reciprocal Agitation

Food engineering, food chemistry, and consumer segmentation were used to evaluate ready-to-eat rice. The aromatic Louisiana Clearfield Jazzman (CJ) and Thai Jasmine (TJ), and a non-aromatic parboiled (PB) rice were hydrated during the first 10 min of processing with reciprocal agitation followed by static retort processing. The aroma compound, 2-Acetyl-1-pyrroline (2-AP) was more heat-stable in CJ than TJ rice but decreased 15-fold compared to the rice cooker method. Pareto analysis indicated that rice type and agitation had the main effect on amylose and total starch and chroma and hue. Color differences of rice agitated during hydration and between rice cooker or static retort processed rice, indicated only slight differences for each rice variety. Hydration of dry rice during retort cooking and similar starch, color, and aroma quality were achieved with reciprocal compared to static or rice cooker methods. Survey responses categorized consumers into three, mindsets driven by rice consumption, convenience, or packaging.

Mathematical modeling for the prediction of some quality parameters of white rice based on the strength properties of samples using response surface methodology (RSM)

One of the major problems in predicting the quality properties of rice is that conducting experiments in the food industry can be highly expensive. The objective of this study was to predict some quality properties in varieties (Domsiah, Hashemi, Dorfak, and Kadus) via compression test at moisture levels 9 and 14% w.b. Based on historical data design, RSM was used to model and estimate of dependent variables (amylose (AC) and protein content (PC), gelatinization temperature, gel consistency GC), minimum (Min.V), final (FV), breakdown (BDV) and setback viscosity (SBV), peak time (PT) and pasting temperature (Pa.T)) through independent variables (the rate of force, deformation, rupture energy, tangent, and secant modulus). An ANOVA test showed that models were significant (p < 0.05). The most appropriate model for response variables prediction of AC and GC (Kadus 14%), PC (Domsiah 9%), Min.V, FV, and SBV (Dorfak 9%), BDV (Dorfak 14%), PT (Hashemi 14%), and Pa.T (Kadus 9%) was R pred 2 as 0.86, 0.85, 0.93, 0.955, 0.953, 0.94, 0.94, 0.86, and 0.91, respectively, with the most appropriate optimal values as 23.52%, 48, 10%, 164.95 RVU, 304.12 RVU, 162.66 RVU, 64.52 RVU, 6.09 min, and 92.45°C and desirability as 0.91, 0.95, 0.95, 0.80, 0.89, 0.83, 0.84, 0.89, and 0.96, respectively. The optimal values of the independent variables have a decreasing trend, and the optimal values of the response variables are proportional to the optimal conditions. The results indicated that the RSM could be quite useful in the optimization of the models developed for predicting the rice quality properties.