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Optimization of the sugar hydrothermal extraction process from olive cake using neuro-fuzzy models
A Pérez1, G Blázquez1, I Iáñez-Rodríguez1
1Department of Chemical Engineering, Avenida Fuentenueva s/n, University of Granada, 18071 Granada, Spain.
Bioresource Technology
|August 4, 2018
Summary
This study optimized hydrothermal extraction from olive cake to yield sugars and antioxidants. A neuro-fuzzy model proved more accurate than traditional methods for predicting extraction yields.
Area of Science:
- Biorefinery processes
- Green chemistry
- Waste valorization
Background:
- Olive cake is a lignocellulosic byproduct with potential for valuable compound extraction.
- Hydrothermal extraction using water offers a sustainable method for biomass processing.
- Optimization is crucial for efficient recovery of sugars and antioxidants from olive cake.
Purpose of the Study:
- To optimize hydrothermal extraction conditions for sugars and antioxidants from olive cake.
- To investigate the influence of key process variables on extraction yields.
- To compare the predictive accuracy of polynomial and neuro-fuzzy models for extraction yields.
Main Methods:
- Central Composite Design (CCD) of experiments was employed.
- Four variables were tested: temperature, time, particle diameter, and solid/liquid ratio.
- Extraction yields of glucose, xylose, polyphenols, and oligomers were analyzed.
Main Results:
- Particle diameter and solid/liquid ratio were the most influential variables.
- Experimental data were modeled using a classical polynomial approach and a neuro-fuzzy system.
- The neuro-fuzzy system demonstrated superior accuracy in predicting experimental extraction values.
Conclusions:
- Hydrothermal extraction is a viable method for valorizing olive cake.
- Particle size and solid/liquid ratio are critical parameters for optimizing sugar and antioxidant recovery.
- Neuro-fuzzy modeling offers enhanced predictive capabilities for biorefinery processes.
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