The authors are grateful to the Foundation for Science and Technology
(FCT) for financial support to CIMO (UIDB/00690/2020 and
UIDP/00690/2020), SusTEC (LA/P/0007/2020), L. Barros institutional
contract, and Ana Rita Silva Doctoral Grant (SFRH/BD/145834/2019).
To the ERDF through the Regional Operational Program North 2020,
within the scope of the project OliveBIOextract (NORTE-01-0247-
FEDER-049865). B. Melgar thanks the ERDF through the Regional
Operational Program North 2020 for his contract within the Project
OleaChain (NORTE-06-3559-FSE-000188). To MICINN for supporting
the JDC contract of T. Oludemi (FJC2019-042549-I). Manuel Ayuso
thanks PRIMA and FEDER-Interreg Espana- Portugal programme for
financial support through the Local-NutLeg project (Section 1 2020
Agrofood Value Chain topic 1.3.1
This study optimized the extraction of three major phenolic compounds (oleuropein, tyrosol, and verbascoside)
from olive pomace using microwave- and ultrasonic-assisted methods. Screening factorial design (SFD) and
central composite design (CCD) were employed, and response surface methodology (RSM) and artificial neural
networks (ANN) were used for data modeling. The microwave-assisted method in the SFD yielded higher
compound amounts, with verbascoside showing a four-fold increase compared to the ultrasonic-assisted method.
Factors like vessel diameter, ultrasonic power using UAE, and solvent acidity in both techniques had minimally
impacted extractability. CCD-RSM revealed temperaturés significantly affect on oleuropein, but improved tyrosol
recovery, with the effect on verbascoside being influenced by the temperature range. RSM and ANN integration
enhanced understanding and prediction of factor behavior. Microwave-assisted extraction at 113 ◦C for 26 min,
with minimum ramp time of 7.7 min, yielded 67.4, 57, and 5.1 mg of oleuropein, tyrosol, and verbascoside per
gram of extract, respectively, with a prediction error ranging from 0.83 to 15.19.
