scholarly journals Optimization of an Ultrasound-Assisted Extraction Condition for Flavonoid Compounds from Cocoa Shells (Theobroma cacao) Using Response Surface Methodology

Molecules ◽  
2019 ◽  
Vol 24 (4) ◽  
pp. 711 ◽  
Author(s):  
Arief Md Yusof ◽  
Siti Abd Gani ◽  
Uswatun Zaidan ◽  
Mohd Halmi ◽  
Badrul Zainudin
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Ethanol Concentration ◽  
Irradiation Time ◽  
Ultrasound Irradiation ◽  
Coefficient Of Determination ◽  
Ultrasound Assisted Extraction ◽  
Assisted Extraction ◽  
Ultrasound Assisted ◽  
Experimental Values

This study investigates the ultrasound-assisted extraction of flavonoids from Malaysian cocoa shell extracts, and optimization using response surface methodology. There are three variables involved in this study, namely: ethanol concentration (70–90 v/v %), temperature (45–65 °C), and ultrasound irradiation time (30–60 min). All of the data were collected and analyzed for variance (ANOVA). The coefficient of determination (R2) and the model was significant in interaction between all variables (98% and p < 0.0001, respectively). In addition, the lack of fit test for the model was not of significance, with p > 0.0684. The ethanol concentration, temperature, and ultrasound irradiation time that yielded the maximum value of the total flavonoid content (TFC; 7.47 mg RE/g dried weight (DW)) was 80%, 55 °C, and 45 min, respectively. The optimum value from the validation of the experimental TFC was 7.23 ± 0.15 mg of rutin, equivalent per gram of extract with ethanol concentration, temperature, and ultrasound irradiation time values of 74.20%, 49.99 °C, and 42.82 min, respectively. While the modelled equation fits the data, the T-test is not significant, suggesting that the experimental values agree with those predicted by the response surface methodology models.

scholarly journals Ultrasound-Assisted Extraction of Carotenoids from Carrot Pomace and Their Optimization through Response Surface Methodology

Molecules ◽  
2021 ◽  
Vol 26 (22) ◽  
pp. 6763
Author(s):  
Muhammad Umair ◽  
Saqib Jabbar ◽  
Mustapha M. Nasiru ◽  
Zhaoxin Lu ◽  
Jianhao Zhang ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Ethanol Concentration ◽  
Extraction Time ◽  
Ultrasound Assisted Extraction ◽  
Total Carotenoids ◽  
Independent Variables ◽  
Assisted Extraction ◽  
Productive Process ◽  
Ultrasound Assisted

Ultrasound-assisted extraction (UAE) was used to extract carotenoids from the carrot pomace. To investigate the effect of independent variables on the UAE, the response surface methodology (RSM) with central-composite design (CCD) was employed. The study was conducted with three independent variables including extraction time (min), temperature (°C), and ethanol concentration (%). The results showed that the optimal conditions for UAE were achieved with an extraction time of 17 min, temperature of 32 °C, and ethanol concentration of 51% of total carotenoids (31.82 ± 0.55); extraction time of 16 min, temperature of 29 °C, and ethanol concentration of 59% for a combination of β-carotene (14.89 ± 0.40), lutein (5.77 ± 0.19), and lycopene (2.65 ± 0.12). The non-significant (p > 0.05) correlation under optimal extraction conditions between predicted and experimental values suggested that UAE is the more productive process than conventional techniques for the extraction of carotenoids from the carrot pomace.

scholarly journals UPLC-ESI-MS/MS Analysis and Evaluation of Antioxidant Activity of Total Flavonoid Extract from Paeonia lactiflora Seed Peel and Optimization by Response Surface Methodology (RSM)

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Guiqin Shi ◽  
Jiaxin Shen ◽  
Tao Wei ◽  
Fei Ren ◽  
Famou Guo ◽  
...  
Keyword(s):  
Antioxidant Activity ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Ethanol Concentration ◽  
Paeonia Lactiflora ◽  
Ultrasound Assisted Extraction ◽  
Solid Ratio ◽  
Assisted Extraction ◽  
Ultrasonic Time ◽  
Ultrasound Assisted

In this study, the ultrasound-assisted extraction (UAE) of flavonoid from Paeonia lactiflora seed peel was optimized by response surface methodology (RSM). Single-factor experiments and a three-factor three-level Box-Behnken design (BBD) were performed to explore the effects of the following parameters on flavonoid extraction: ethanol concentration ( X 1 ), liquid-solid ratio ( X 2 ), and ultrasonic time ( X 3 ). The results showed that the optimal flavonoid yield (10.9045 mg RE/g) was as follows: ethanol concentration 62.93%, ultrasonic time 64.56 min, and liquid-solid ratio 24.86 mL/g. The optimized extract of P. lactiflora seed shell was further analyzed by UPLC-ESI-MS/MS, and 20 main flavonoids were identified and quantified, among which protocatechuic acid, vanillic acid, 4-hydroxybenzoic acid, and 3,4-dihydroxybenzaldehyde had the highest content. Furthermore, the results of the antioxidant test showed that the P. lactiflora seed peel extract obtained under optimized UAE conditions exhibited good antioxidant activity. The experimental results showed that ultrasound-assisted extraction was a fast, efficient, and simple method for extracting active ingredients from P. lactiflora seed peel, thereby making this byproduct a promising source of compounds in food and healthcare sectors.

scholarly journals Optimization of Ultrasound-Assisted Extraction of Phenolics from Sideritis raeseri Using Response Surface Methodology

Molecules ◽  
2021 ◽  
Vol 26 (13) ◽  
pp. 3949
Author(s):  
Katarina Šavikin ◽  
Jelena Živković ◽  
Teodora Janković ◽  
Nada Ćujić-Nikolić ◽  
Gordana Zdunić ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Ethanol Concentration ◽  
Extraction Time ◽  
Total Phenolic ◽  
Solvent Ratio ◽  
Extraction Temperature ◽  
Ultrasound Assisted Extraction ◽  
Assisted Extraction ◽  
Ultrasound Assisted

In this study we define the optimal conditions for ultrasound-assisted extraction of bioactive polyphenols from S. raeseri aerial parts using response surface methodology. The influence of ethanol concentration (10–90%), extraction temperature (20–80 °C), extraction time (10–60 min), and solid-to-solvent ratio (1:10–1:50) on total phenolic content as well as on content of individual flavonoids, and hypolaetin and isoscutellarein derivatives was studied. For the experimental design, a central composite design was chosen. In the obtained extracts, the following ranges of targeted compounds were detected: total phenol from 19.32 to 47.23 mg GAE/g dw, HYP from 1.05 to 11.46 mg/g dw, ISC 1 from 0.68 to 10.68 mg/g dw, and ISC 2 from 0.74 to 15.56 mg/g dw. The optimal extraction conditions were set as: ethanol concentration of 65%, extraction time of 50 min, extraction temperature of 63 °C, and solid-to-solvent ratio of 1:40. Contents of TP, HYP, ISC 1, and ISC 2 in optimal extracts were 47.11 mg GAE/g dw, 11.73 mg/g dw, 9.54 mg/g dw, and 15.40 mg/g dw, respectively. Experimentally set values were in good agreement with those predicted by the response surface methodology model, indicating suitability of the used model, as well as the success of response surface methodology in optimizing the conditions of the extraction.

scholarly journals Comparison of Artificial Neural Networks and Response Surface Methodology towards an Efficient Ultrasound-Assisted Extraction of Chlorogenic Acid from Lonicera japonica

Molecules ◽  
2019 ◽  
Vol 24 (12) ◽  
pp. 2304 ◽  
Author(s):  
Hui-Chuan Yu ◽  
Shang-Ming Huang ◽  
Wei-Min Lin ◽  
Chia-Hung Kuo ◽  
Chwen-Jen Shieh
Keyword(s):  
Response Surface Methodology ◽  
Chlorogenic Acid ◽  
Response Surface ◽  
Ethanol Concentration ◽  
Lonicera Japonica ◽  
Ultrasound Assisted Extraction ◽  
Assisted Extraction ◽  
Ultrasound Assisted ◽  
Artificial Neural ◽  
Ultrasound Power

Chlorogenic acid (CGA), a bioactive compound commonly found in plants, has been demonstrated possessing nutraceutical potential in recent years. However, the more critical issue concerning how to improve production efficacy of CGA is still limited. It is a challenge to harvest a large amount of CGA without prolonging extraction time. In this study, the feasibility of using ultrasound for CGA extraction from Lonicera japonica was investigated. A central composite design (CCD) was employed to evaluate the effects of the operation parameters, including temperature, ethanol concentration, liquid to solid ratio, and ultrasound power on CGA yields. Meanwhile, the process of ultrasound-assisted extraction was optimized through modeling response surface methodology (RSM) and artificial neural network (ANN). The data indicated that CGA was efficiently extracted from the flower of Lonicera japonica by ultrasound assistance. The optimal conditions for the maximum extraction of CGA were as follows: The temperature at 33.56 °C, ethanol concentration at 65.88%, L/S ratio at 46:1 mL/g and ultrasound power at 150 W. ANN possessed greater optimization capacity than RSM for fitting experimental data and predicting the extraction process to obtain a maximum CGA yield. In conclusion, the process of ultrasound-assisted extraction can be well established by a methodological approach using either RSM or ANN, but it is worth mentioning that the ANN model used here showed the superiority over RSM for predicting and optimizing.

scholarly journals Skin-Whitening and Anti-Wrinkle Effects of Bioactive Compounds Isolated from Peanut Shell Using Ultrasound-Assisted Extraction

Molecules ◽  
2021 ◽  
Vol 26 (5) ◽  
pp. 1231
Author(s):  
Da Hye Gam ◽  
Ji Woo Hong ◽  
Jun Hee Kim ◽  
Jin Woo Kim
Keyword(s):  
Ethanol Concentration ◽  
Extraction Time ◽  
Extraction Temperature ◽  
Peanut Shell ◽  
Ultrasound Assisted Extraction ◽  
Skin Whitening ◽  
Activity Inhibition ◽  
Assisted Extraction ◽  
Ultrasound Assisted ◽  
Experimental Values

Response surface methodology was employed to optimize the ultrasound-assisted extraction (UAE) conditions for simultaneous optimization of dependent variables, including DPPH radical scavenging activity (RSA), tyrosinase activity inhibition (TAI), and collagenase activity inhibition (CAI) of peanut shell extracts. The effects of the main variables including extraction time (5.0~55.0 min, X1), extraction temperature (26.0~94.0 °C, X2), and ethanol concentration (0.0%~99.5%, X3) were optimized. Based on experimental values from each condition, quadratic regression models were derived for the prediction of optimum conditions. The coefficient of determination (R2) of the independent variable was in the range of 0.89~0.96, which demonstrates that the regression model is suitable for the prediction. In predicting optimal UAE conditions based on the superimposing method, extraction time of 31.2 min, extraction temperature of 36.6 °C, and ethanol concentration of 93.2% were identified. Under these conditions, RSA of 74.9%, TAI of 50.6%, and CAI of 86.8% were predicted, showing good agreement with the experimental values. A reverse transcription polymerase chain reaction showed that peanut shell extract decreased mRNA levels of tyrosinase-related protein-1 and matrix metalloproteinase-3 genes in B16-F0 cell. Therefore, we identified the skin-whitening and anti-wrinkle effects of peanut shell extracts at protein as well as gene expression levels, and the results show that peanut shell is an effective cosmetic material for skin-whitening and anti-wrinkle effects. Based on this study, peanut shell, which was considered a byproduct, can be used for the development of healthy foods, medicines, and cosmetics.

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