Optimization of ultrasound-assisted extraction of phenolic compounds from grapefruit (Citrus paradisi Macf.) leaves via D-optimal design and artificial neural network design with categorical and quantitative variables

Cigeroglu Z., ARAS Ö., Pinto C. A., Bayramoglu M., Kirbaslar S., Lorenzo J. M., ...Daha Fazla

JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE, cilt.98, sa.12, ss.4584-4596, 2018 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 98 Sayı: 12
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1002/jsfa.8987
  • Dergi Adı: JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.4584-4596
  • İstanbul Üniversitesi Adresli: Evet

Özet

BACKGROUND: The extraction of phenolic compounds from grapefruit leaves assisted by ultrasound-assisted extraction (UAE) was optimized using response surface methodology (RSM) by means of D-optimal experimental design and artificial neural network (ANN). For this purpose, five numerical factors were selected: ethanol concentration (0-50%), extraction time (15-60 min), extraction temperature (25-50 degrees C), solid:liquid ratio (50 - 100 gL(-1)) and calorimetric energy density of ultrasound (0.25-0.50 kW L-1), whereas ultrasound probe horn diameter (13 or 19 mm) was chosen as categorical factor.