Almond extract has unique nutritional properties and it can be used as a nutritive beverage. One of the most important problems in the formulation of almond milk is the physical stability of the final product. In this study, the response surface methodology was used to optimize ultrasound (US) treatment and the amount of modified starch, lecithin and agar with respect to physical stability besides other physical properties such as particle size, viscosity, Brix and color attributes. Our results showed that the US treatment had a significant effect on physical responses (p < 0.05). In order to formulate the final product, stabilized almond milk was formulated using a D-Optimal mixture design by considering sensory evaluation. This study suggests using 8.05 sugar, 0.55 stevia and 6.38% rose water to obtain the best formulation. Rheological properties of the formulated milk showed pseudoplastic behavior, and the power law model had the best fitness to the experimental data.
PRACTICAL APPLICATIONSOne of the most important problems in formulation of the almond milk as a nutritive beverage is the physical stability of the final product. Ultrasonic treatment and addition of various stabilizers can be useful to improve the stabilization of almond milk. The ultrasound treatment and the amount of modified starch, lecithin and agar were optimized with respect to the physical properties using response surface methodology. The best values for the ultrasound time and the amount of lecithin, modified starch and agar were 4.9 min, 0.09, 1.31% and 0.15, respectively. A D-Optimal mixture design was used to optimize the industrial formulation of final beverage by considering sensory evaluation. This study suggests using 8.05 sugar, 0.55 stevia and 6.38% rose water to obtain the best formulation. Rheological properties of the formulated milk showed that pseudoplastic behavior and power law model had the best fitness to the experimental data.
In this study, the whole potato was fortified with iron by using vacuum impregnation (VI) with an ultrasound (US) pretreatment. The physicochemical properties of VI‐processed potatoes were evaluated after a cooking process. The optimization of US pretreatment parameters was performed with respect to area fraction parameter, color, and texture and components leakage. The use of US with a lower frequency and a higher power intensity caused a higher ink impregnation, leakage of sugar content, and phenolic components after VI processing. The parameters of US have not a significant effect on color and texture of VI‐processed potatoes. The obtained results indicated that VI and US–VI processes significantly enhanced the iron content about 137.5 and 210%, respectively. For fortified‐cooked potatoes, the relative bioavailability of SunActive Fe was lower than the ferrous sulfate, but it had no undesirable effect on sensory evaluation, color parameters, and texture of fortified potatoes.
Practical applications
Food fortification with iron is a suitable strategy to control the iron deficiency. The ultrasound (US) pretreatment prior to vacuum impregnation (VI) leads to a higher iron impregnation. The US pretreatment has not significant effects on the color and textural properties of whole potatoes fortified by VI. SunActive Fe can be also considered as a suitable iron source to fortification of potato due to no undesirable effect on sensory properties, color parameters, and oxidative stability.
Optimization of fluidized bed drying of sesame seeds was done by response surface methodology (RSM) and genetic algorithms (GA). Effect of drying parameters (drying temperature (40, 50, 60°C), drying time (60, 120, 180 min), air velocity (1, 1.5, 2 m/s) and bed depth of dryer (1-3 cm) was investigated based on the quality attributes of dried seeds. These factors were optimized with respect to the moisture ratio, color indices, and texture parameters (hardness and fracturability). The obtained models showed very well fitness with experimental data. The coefficients of resulting models with RSM were further optimized using GA. It was revealed that GA-optimized models have better fitness with the experimental results than RSM models. Our results suggest that sesame seed dried in 40-45°C for 115-120 min with 1 m/s air velocity had the lowest moisture content and color changes and the best texture.
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