scholarly journals Optimization of Osmotic Dehydration of Autumn Olive Berries Using Response Surface Methodology

Foods ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1075
Author(s):  
Mohamed Ghellam ◽  
Oscar Zannou ◽  
Hojjat Pashazadeh ◽  
Charis M. Galanakis ◽  
Turki M. S. Aldawoud ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Color Change ◽  
Osmotic Dehydration ◽  
Physicochemical Characteristics ◽  
Regression Equations ◽  
Affecting Factors ◽  
Autumn Olive ◽  
Total Color Change ◽  
Predicted Values

Autumn olive fruits are a rich source of nutrients and functional compounds, making them functional foods against many diseases and cancers. To increase the consumption, its processing, and its transformation into new products would help spread them to the consumer’s table. In this study, after giving an overview of the physicochemical characteristics and the antioxidant activity, the objective was to optimize the osmotic dehydration (OD) of the berries. Response surface methodology was used to investigate the effect of dehydration factors: syrup concentration (30–70%), temperature (20–70 °C), and fruit-to-syrup ratio (1:10–2:10) on the water loss (WL), sugar gain (SG), weight reduction (WR), density (ρ), water activity (aw), and total color change (ΔE) of fruits after 10 h of OD. Results obtained by employing Box–Behnken design (three variables, three levels), and significant terms of regression equations indicated that the syrup concentration and temperature variation are the most affecting factors on the previously mentioned independent variables (WL SG, WR, ρ, aw, and ΔE). Fruits to syrup ratio appeared to have a significant effect only on WL. Under the optimum conditions found (70%, 70 °C, 1.8:10), the predicted values were 59.21%. 19.21%, 32.34%, 1.22 g/cm3, 0.850, and 3.65 for WL, SG, WR, ρ, aw, and ΔE, respectively.

Optimization of Manufacturing Process of Traditional Algerian Jben Cheese Using Response Surface Methodology (RSM)

2018 ◽  
Vol 8 (1) ◽  
pp. 31-42
Author(s):  
M. Amimour ◽  
T. Idoui ◽  
A. Cheriguene
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Manufacturing Process ◽  
Milk Powder ◽  
Statistical Design ◽  
Polynomial Equation ◽  
Enzymatic Extract ◽  
Traditional Cheese ◽  
Order Polynomial ◽  
Predicted Values

The Aim of this study was to develop an optimized method for manufacturing process of traditional Algerian Jben cheese, using response surface methodology (RSM). In order to develop the objective method of making this traditional cheese, several factors have been studied and a Plackett-Burman statistical design was applied. The effects of the four screened factors (enrichment with milk powder, 10 - 20 g/l; pH of milk, 5.75 - 6.75, enzymatic extract dose, 0.5 - 1.5 ml and coagulation temperature 40 - 60 °C) on the response were investigated, using a Box-Behnken statistical design. Multiple regression analysis was used so that experimental data fits to a second-order polynomial equation. This multiple analysis showed that the model explains about 90.73% of the variation. Based on statistical results, it can be noticed that enrichment with milk powder and pH of milk (Ë‚0.0001***) were highly significant factor influincing cheese yield. The optimal production parame-ters that maximized cheese product (20 g/l enrichment with milk powder, 5.75 pH of milk, 1.29 ml enzymatic extract dose and 60°C coagulation temperature) and the maximal predicted cheese yield (52.68 % ) were found out through response surface methodology. Under these conditions, a verification experiment was carried out and cheese yield was found to be 49.46 %. The overall percentage of agreement for the experimental results (more than 93 % validity) with the predicted values indicates the validation of the statistical model and the success of the optimization process.

scholarly journals Optimization of Supercritical Carbon Dioxide Extraction of Quercus infectoria Oil

2015 ◽  
Vol 74 (7) ◽  
Author(s):  
Liza Md Salleh ◽  
Stashia ELeaness Rosland Abel ◽  
Gholamreza Zahedi ◽  
Russly Abd Rahman ◽  
Hasmida Mohd Nasir ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Goodness Of Fit ◽  
Maximum Yield ◽  
Extraction Yield ◽  
Extraction Time ◽  
Extraction Temperature ◽  
Predicted Values ◽  
Artificial Neural Network Ann ◽  
Quercus Infectoria

This current study focuses on the modelling and optimization of supercritical fluid extraction of Quercus infectoria galls oil. In this case, response surface methodology (RSM) and artificial neural network (ANN) were applied for the modelling and prediction of extraction yield of galls oil. A 17-run Box-Behnken Design (BBD) was employed to statistically optimize the process parameters of SC-CO2 extraction of Quercus infectoria galls at a condition as follows: pressure (5000, 6000, 7000 Psi), temperature (40, 50, 60°C) and extraction time (30, 45, 60 min). The maximum yield of the extracted oil is1.12 % and the optimum conditions are at an extraction pressure of 5574 Psi; extraction temperature of 75°C and extraction time of 54 min. Under the optimal conditions, the experimental results agree with the predicted values obtained through analysis of variance (ANOVA). This indicates a successful response surface methodology and highly satisfactory goodness of fit of the model used. The analysis of experimental design for process optimization results demonstrates that temperature and extraction time are the main parameters that influence the oil extraction of Quercus infectoria.

scholarly journals Optimizing Physiochemical and Sensory Properties of Infrared-Hot Air Roasted Sunflower Kernels Using Response Surface Methodology

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Mahdis Mosayebi ◽  
Mahdi Kashaninejad ◽  
Leila Najafian
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Color Change ◽  
Specific Energy Consumption ◽  
Chemical Properties ◽  
Sensory Properties ◽  
Quadratic Model ◽  
Total Phenolic ◽  
Phenolic Contents ◽  
Hot Air

Roasting sunflower kernels is a key process in production of nuts. In this study, the effect of roasting conditions, including hot air temperature (120–160°C), infrared (IR) power (400–600 W) and roasting time (3–10 min) on energy and specific energy consumption, color parameters (L∗, a∗, b∗, ΔE, BI, SI, WI, and h°), texture, moisture content, chemical properties (pH and total phenolic contents, peroxide value (PV), and sensory properties of sunflower kernel were investigated. In addition, the best models for the responses were obtained, and the proper roasting conditions were determined using response surface methodology (RSM). A quadratic model was proposed for color change (L∗, ΔE, SI, and WI), moisture and total phenol contents, linear relation for a∗, b∗, h°, and 2FI for BI, texture, PV, and pH. Roasting at 425.7 W IR power and 124.3°C for 3.7 min was found to be convenient or proper roasting conditions.

scholarly journals Optimization of osmotic dehydration of chestnut (Castanea sativa Mill.) slices using Response Surface Methodology

2018 ◽  
Vol 7 (1) ◽  
Author(s):  
Teresa Delgado ◽  
Bruna Paim ◽  
José Alberto Pereira ◽  
Susana Casal ◽  
Elsa Ramalhosa
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Water Loss ◽  
Osmotic Dehydration ◽  
Sucrose Concentration ◽  
Volume Ratio ◽  
Castanea Sativa ◽  
Color Variation ◽  
Process Conditions ◽  
Operational Conditions

Osmotic dehydration of chestnut slices in sucrose was optimized for the first time by Response Surface Methodology (RSM). Experiments were planned according to a three-factor central composite design (α=1.68), studying the influence of sucrose concentration, temperature and time, on the following parameters: volume ratio, water activity, color variation, weight reduction, solids gain, water loss and normalized moisture content, as well as total moisture, ash and fat contents. The experimental data was adequately fitted into second-order polynomial models with coefficients of determination (R2) from 0.716 to 0.976, adjusted-R2 values from 0.460 to 0.954, and non-significant lacks of fit. The optimal osmotic dehydration process conditions for maximum water loss and minimum solids gain and color variation were determined by the “Response Optimizer” option: 83% sucrose concentration, 20 °C and 9.2 hours. Thus, the best operational conditions corresponded to high sugar concentration and low temperature, improving energy saving and decreasing the process costs.

Optimization of a Whole-Stalk Operating System after Sugarcane Base Cutting

2019 ◽  
Vol 62 (1) ◽  
pp. 157-166
Author(s):  
Luxin Xie ◽  
Jun Wang ◽  
Shaoming Cheng ◽  
Jinbing Hu
Keyword(s):  
Operating System ◽  
Response Surface Methodology ◽  
Central Composite Design ◽  
Response Surface ◽  
Fracture Rate ◽  
Cleaning Performance ◽  
Abrasion Rate ◽  
Leaf Stripping ◽  
Predicted Values ◽  
Central Composite

Abstract. Leaf stripping and top breaking are the key procedures in whole-stalk sugarcane harvesting. In this study, a whole-stalk operating system after sugarcane base cutting was developed and tested to improve the leafy trash cleaning performance and adaptability of a whole-stalk harvester. A leaf shredding procedure was proposed before leaf stripping, and an anti-float top breaking device was developed for breaking cane tops. The rotational speeds of the leaf shredding (RL), leaf stripping (RS), and top breaking (RT) rollers were regarded as experimental factors, and the leafy trash content (including leaves, leaf sheaths, and tops in this study), top breaking rate, abrasion rate, and non-fracture rate of the middle or bottom parts were selected as indices. Central composite design combined with response surface methodology and comprehensive evaluation method were employed to conduct experiments and explore the interaction effects of factors on indices. The optimal operating parameters were nonlinearly optimized and determined to be RL of 512.9 rpm, RS of 418.8 rpm, and RT of 307.0 rpm. Under these conditions, the predicted values of leafy trash content, top breaking rate, abrasion rate, and non-fracture rate were 4.98%, 88.39%, 5.19%, and 96.21%, respectively. Verification experiments indicated that the observed values were in agreement with the predicted values. Results suggested that the leaf shredding device and anti-float top breaking device developed in this study were effective for improving the leafy trash cleaning performance and adaptability of the whole-stalk operating system, and there was a good potential for performance improvement of whole-stalk sugarcane harvesters. Keywords: Central composite design, Leaf shredding, Leaf stripping, Response surface methodology, Top breaking, Whole-stalk harvester.

Optimization of Osmotic Dehydration of Radish in Salt Solution Using Response Surface Methodology

2009 ◽  
Vol 5 (3) ◽  
Author(s):  
Manivannan Petchi ◽  
Rajasimman Manivasagan
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Salt Solution ◽  
Water Loss ◽  
Weight Reduction ◽  
Osmotic Dehydration ◽  
Dehydration Process ◽  
Initial Sample ◽  
Solid Gain ◽  
Sample Ratio

Response surface methodology was used to determine the optimum processing conditions that yield maximum water loss and weight reduction and minimum solid gain during osmotic dehydration of radish in salt solution. The experiments were conducted according to Central Composite Design (CCD). The independent process variables for osmotic dehydration process were temperature (25 – 45°C), processing time (30 -150 minutes), salt concentrations (5 - 25% w/w) and solution to sample ratio (5:1 – 25:1). The osmotic dehydration process was optimized for water loss, solid gain, and weight reduction. The optimum conditions were found to be: temperature – 36°C, immersion time - 95 min, salt concentration – 25% and solution to sample ratio 15:1. At this optimum point, water loss, solid gain and weight reduction were found to be 34.5 (g/100 g initial sample), 2.2 (g/100 g initial sample) and 32.1 (g/100 g initial sample), respectively.

Sign in / Sign up

Export Citation Format

Share Document