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, ss.4584-4596, 2018 (SCI İndekslerine Giren Dergi) identifier identifier identifier

  • Cilt numarası: 98 Konu: 12
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1002/jsfa.8987
  • Dergi Adı: JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE
  • Sayfa Sayıları: ss.4584-4596

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.