Optimization of spray drying microencapsulation of olive pomace polyphenols using Response Surface Methodology and Artificial Neural Network. (July 2018)
- Record Type:
- Journal Article
- Title:
- Optimization of spray drying microencapsulation of olive pomace polyphenols using Response Surface Methodology and Artificial Neural Network. (July 2018)
- Main Title:
- Optimization of spray drying microencapsulation of olive pomace polyphenols using Response Surface Methodology and Artificial Neural Network
- Authors:
- Aliakbarian, Bahar
Sampaio, Fábio Coelho
de Faria, Janaína Teles
Pitangui, Cristiano Grijó
Lovaglio, Francesca
Casazza, Alessandro Alberto
Converti, Attilio
Perego, Patrizia - Abstract:
- Abstract: This study was performed to determine the optimum conditions for spray drying microencapsulation of olive pomace extract, in order to stabilize its phenolic compounds using maltodextrin as carrier material. To this purpose, a comparison optimization study was performed using Response Surface Methodology or Artificial Neural Network, which revealed better prediction accuracy of the former. Maltodextrin concentrations (100–500 g/L), inlet-drying air temperatures (130–160 °C), feed flowrates (5.0–10.0 mL/min), and drying compressed air flowrates (20–32 m 3 h −1 ) were tested as the independent variables according to a Central Composite Face Centered design, and the results of microencapsulation yield, moisture content, water solubility, specific total polyphenol content, specific antioxidant activity and encapsulation efficiency were elaborated. Under optimal conditions, these responses varied in the ranges 65–82%, 9–14 g/100 g, 64–65%, 38–52 mgCAE gDM −1, 230–487 μgTrolox gDM −1 and 85–92%, respectively. The same optimization regions for operative parameters were obtained using Response Surface Methodology or Artificial Neural Network. The results demonstrated that maltodextrin-based microcapsules containing olive pomace extract can effectively be produced by spray drying with good stability under storage conditions, and suggest that their remarkable antioxidant activity may be exploited to improve the properties of functional foods or pharmaceutical products.Abstract: This study was performed to determine the optimum conditions for spray drying microencapsulation of olive pomace extract, in order to stabilize its phenolic compounds using maltodextrin as carrier material. To this purpose, a comparison optimization study was performed using Response Surface Methodology or Artificial Neural Network, which revealed better prediction accuracy of the former. Maltodextrin concentrations (100–500 g/L), inlet-drying air temperatures (130–160 °C), feed flowrates (5.0–10.0 mL/min), and drying compressed air flowrates (20–32 m 3 h −1 ) were tested as the independent variables according to a Central Composite Face Centered design, and the results of microencapsulation yield, moisture content, water solubility, specific total polyphenol content, specific antioxidant activity and encapsulation efficiency were elaborated. Under optimal conditions, these responses varied in the ranges 65–82%, 9–14 g/100 g, 64–65%, 38–52 mgCAE gDM −1, 230–487 μgTrolox gDM −1 and 85–92%, respectively. The same optimization regions for operative parameters were obtained using Response Surface Methodology or Artificial Neural Network. The results demonstrated that maltodextrin-based microcapsules containing olive pomace extract can effectively be produced by spray drying with good stability under storage conditions, and suggest that their remarkable antioxidant activity may be exploited to improve the properties of functional foods or pharmaceutical products. Highlights: Olive pomace phenolics were encapsulated by spray drying. RSM and ANN were used for optimization of encapsulation. Prediction accuracy of RSM was better than that of ANN. Stable microcapsules with remarkable antioxidant activity were obtained. … (more)
- Is Part Of:
- Lebensmittel-Wissenschaft + Technologie =. Volume 93(2018)
- Journal:
- Lebensmittel-Wissenschaft + Technologie =
- Issue:
- Volume 93(2018)
- Issue Display:
- Volume 93, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 93
- Issue:
- 2018
- Issue Sort Value:
- 2018-0093-2018-0000
- Page Start:
- 220
- Page End:
- 228
- Publication Date:
- 2018-07
- Subjects:
- Antioxidant activity -- Experimental design -- Statistic models -- Moisture content -- Water solubility
Food industry and trade -- Periodicals
Food -- Composition -- Periodicals
Microbiology -- Periodicals
Nutrition -- Periodicals
664.005 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00236438 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.lwt.2018.03.048 ↗
- Languages:
- English
- ISSNs:
- 0023-6438
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3983.070000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 6463.xml