Boosting Purnica granatum L. Seed Oil Yield: An Adaptive Neuro-Fuzzy Interference System Fuels SC-CO2 Extraction Breakthrough-Reference-Cited by-同舟云学术

Boosting Purnica granatum L. Seed Oil Yield: An Adaptive Neuro-Fuzzy Interference System Fuels SC-CO2 Extraction Breakthrough

Published:2024-01-02 Issue:1 Volume:13 Page:161
ISSN:2304-8158
Container-title:Foods
language:en
Short-container-title:Foods

Author:

Pao-la-or Padej¹,Marungsri Boonruang¹^ORCID,Chirinang Pornariya²,Posridee Kakanang³^ORCID,Oonsivilai Ratchadaporn³⁴^ORCID,Oonsivilai Anant¹^ORCID

Affiliation:

1. School of Electrical Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand

2. Applied Food and Nutrition Division, Faculty of Science and Technology, Phetchaburi Rajabhat University, Phetchaburi 76000, Thailand

3. School of Food Technology, Institute of Agricultural Technology, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand

4. Health and Wellness Research Group, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand

Abstract

This study used supercritical fluid extraction to successfully enhance the conditions for extracting oil from pomegranate seeds. To determine the optimal extraction conditions for maximizing pomegranate oil yield, the researchers employed a Box–Behnken design experimental strategy, involving three parameters with three levels each: extraction pressure, extraction temperature, and extraction time. To determine the optimal optimization conditions, the Response Surface Method (RSM) and the Artificial Neural Fuzzy Intelligent System (ANFIS) were also used. The results revealed a strong correlation with the experimental data, demonstrating that both strategies were helpful in optimizing the extraction process. The ideal extraction parameters, according to this study, were an extraction pressure of 40 MPa, an extraction temperature of 55 °C, and an extraction time of 120 min with a CO2 flow rate of 21.3 L/h.

Funder

SUT Research and Development Fund

Publisher

MDPI AG

Subject

Plant Science,Health Professions (miscellaneous),Health (social science),Microbiology,Food Science

Link

https://www.mdpi.com/2304-8158/13/1/161/pdf

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