Modelling and Optimization of Process Parameters for Strawberry Osmotic Dehydration Using Central Composite Rotatable Design

Osmotic dehydration conditions for strawberry were optimized using central composite rotatable design. The optimal conditions included osmotic dehydration temperature of 59.5°C, osmotic dehydration time of 245.6 min, and sorbitol concentration of 66.8%. Water loss (WL) exhibited a response value of 52.5% and was mainly influenced by sorbitol concentration (p≤0.01), followed by osmotic dehydration temperature (p≤0.01) and time (p≤0.01). The optimal condition was validated and found to be fitted well with the experimental data. The osmotic dehydration of strawberry was significantly influenced by osmotic dehydration temperature and time and sorbitol concentration. Based on the parameters of ANOVA, the predicted model for WL rate established by response surface quadratic regression provided an adequate mathematical description of the osmotic dehydration of strawberry.

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Effect of osmotic dehydration with whole cane sugar on the convective drying of mango (Tommy Atkins) and on some physicochemical properties

DYNA ◽

10.15446/dyna.v86n210.77615 ◽

2019 ◽

Vol 86 (210) ◽

pp. 91-97

Author(s):

Carlos Akberto Bejarano Martinez ◽

Carolina Maria Sánchez-Sáenz ◽

Sebastián David Ariza Quiroga

Keyword(s):

Water Loss ◽

Color Index ◽

Osmotic Dehydration ◽

Effective Diffusivity ◽

Cane Sugar ◽

Convective Drying ◽

Central Composite Rotatable Design ◽

Optimal Conditions ◽

Maximum Value ◽

Central Composite

This research evaluates the effect of osmotic dehydration (OD) as a pretreatment of convective drying in mango pieces (Tommy Atkins) using whole cane sugar solutions in concentrations between 30 and 65 °Brix, and temperatures between 50 and 80 °C in a central composite rotatable design. The effect on effective diffusivity, water loss, sugar gain, color index (CIE-L*a*b*), water activity, sensory perception (color, texture and flavor), and consumption probability were measured. Effective diffusivity was influenced only by temperature of solution, presenting a maximum of 1.4E-4 cm2s-1. Water loss in OD registered a maximum of 40%. Color perception was affected by both variables. The consumption probability was influenced by the conditions evaluated with a maximum value of 80%. It was found the optimal conditions of OD in 65°Brix and 79 °C.

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Application of central composite rotatable design to modelling the effect of some operating variables on the performance of the three-product cyclone

International Journal of Mineral Processing ◽

10.1016/j.minpro.2005.01.002 ◽

2005 ◽

Vol 76 (3) ◽

pp. 181-192 ◽

Cited By ~ 94

Author(s):

D.P. Obeng ◽

S. Morrell ◽

T.J. Napier-Munn

Keyword(s):

Central Composite Rotatable Design ◽

Operating Variables ◽

Central Composite ◽

Rotatable Design

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Optimization of transesterification of castor oil with ethanol using a central composite rotatable design (CCRD)

Fuel ◽

10.1016/j.fuel.2009.10.029 ◽

2010 ◽

Vol 89 (5) ◽

pp. 1172-1176 ◽

Cited By ~ 53

Author(s):

Kiany S.B. Cavalcante ◽

Maria N.C. Penha ◽

Karlene K.M. Mendonça ◽

Hilton C. Louzeiro ◽

Antonio C.S. Vasconcelos ◽

...

Keyword(s):

Castor Oil ◽

Central Composite Rotatable Design ◽

Central Composite ◽

Rotatable Design

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Modeling and Optimizing of Mechanically Agitated Vessels by Central Composite Rotatable Design Method

International Journal of Chemical Reactor Engineering ◽

10.1515/1542-6580.2363 ◽

2011 ◽

Vol 9 (1) ◽

Author(s):

Ramin Zadghaffari ◽

Jafarsadegh Moghaddas ◽

F. Fakheri ◽

H. Razmi ◽

H. Heidari

Keyword(s):

Gas Flow ◽

Design Method ◽

Mixing Time ◽

Central Composite Rotatable Design ◽

Two Phase ◽

Injection Point ◽

Tracer Injection ◽

Operating Variables ◽

Central Composite ◽

Rotatable Design

A central composite rotatable design (CCRD) methodology was used to analyze the effect of some operating variables on gas-liquid two phase mixing time in an agitated tank driven by dual 6-blade Rushton turbines. The variables chosen were the impellers rotational speed (x1), gas flow rate (x2), probe location (x3) and tracer injection point (x4). The mathematical relationship of mixing time on the four significant independent variables can be approximated by a nonlinear polynomial model. Predicted values were found to be in good agreement with the experimental values (R-sq of 95.9 percent and R-Sq (Adj) of 95.7 percent for response Y). This study has shown that central composite design could efficiently be applied for the modeling of mixing time, and it is an economical way of obtaining the maximum amount of information with the fewest number of experiments.

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