LAPSE:2023.4557v1
Published Article

LAPSE:2023.4557v1
Optimization of Ultrasound-Assisted Extraction of Spent Coffee Grounds Oil Using Response Surface Methodology
February 23, 2023
Abstract
Spent coffee grounds (SCGs) generated in coffee processing for beverages and other products are a very significant organic residue that needs to be properly treated. Waste valorization via oil extraction has the potential to obtain compounds that can be used for producing biodiesel or other high-value products, such as polymers. This work focuses on the ultrasound-assisted extraction of SCG oil using n-hexane as a solvent. Three key process parameters are analyzed: temperature, extraction time, and liquid/solid (L/S) rate of solvent, using a central composite rotatable design (CCRD), an analysis that, to the author’s knowledge, is not yet available in the literature. The data were analyzed using the software StatSoft STATISTICA 13.1 (TIBCO Software Inc., Palo Alto, CA, USA). Results show that all parameters have a statistical influence on the process performance (p < 0.05), being the L/S ratio the most significant, followed by extraction time and temperature. An analysis of variance (ANOVA) showed that the empirical model is a good fit to the experimental data at a 95% confidence level. For the range of conditions considered in this work, the optimal operating conditions for obtaining an oil extraction yield in the range of 12 to 13%wt are a solvent L/S ratio of around 16 mL g−1, for a temperature in the range of 50 to 60 °C, and the longest contact time, limited by the process economics and health and safety issues and also, by the n-hexane boiling temperature.
Spent coffee grounds (SCGs) generated in coffee processing for beverages and other products are a very significant organic residue that needs to be properly treated. Waste valorization via oil extraction has the potential to obtain compounds that can be used for producing biodiesel or other high-value products, such as polymers. This work focuses on the ultrasound-assisted extraction of SCG oil using n-hexane as a solvent. Three key process parameters are analyzed: temperature, extraction time, and liquid/solid (L/S) rate of solvent, using a central composite rotatable design (CCRD), an analysis that, to the author’s knowledge, is not yet available in the literature. The data were analyzed using the software StatSoft STATISTICA 13.1 (TIBCO Software Inc., Palo Alto, CA, USA). Results show that all parameters have a statistical influence on the process performance (p < 0.05), being the L/S ratio the most significant, followed by extraction time and temperature. An analysis of variance (ANOVA) showed that the empirical model is a good fit to the experimental data at a 95% confidence level. For the range of conditions considered in this work, the optimal operating conditions for obtaining an oil extraction yield in the range of 12 to 13%wt are a solvent L/S ratio of around 16 mL g−1, for a temperature in the range of 50 to 60 °C, and the longest contact time, limited by the process economics and health and safety issues and also, by the n-hexane boiling temperature.
Record ID
Keywords
analysis of variance (ANOVA), central composite rotatable design (CCRD), factorial design, n-hexane, spent coffee grounds (SCG), ultrasound-assisted extraction (UAE) method, waste valorization
Subject
Suggested Citation
Miladi M, Martins AA, Mata TM, Vegara M, Pérez-Infantes M, Remmani R, Ruiz-Canales A, Núñez-Gómez D. Optimization of Ultrasound-Assisted Extraction of Spent Coffee Grounds Oil Using Response Surface Methodology. (2023). LAPSE:2023.4557v1
Author Affiliations
Miladi M: Engineering Department, Miguel Hernández University, Carretera de Beniel, Km 3.2, Orihuela, 03312 Alicante, Spain
Martins AA: LEPABE—Laboratory for Process Engineering, Environment, Biotechnology and Energy, Faculty of Engineering, University of Porto (FEUP), R. Dr. Roberto Frias S/N, 4200-465 Porto, Portugal
Mata TM: INEGI—Institute of Science and Innovation in Mechanical and Industrial Engineering, R. Dr. Roberto Frias 400, 4200-465 Porto, Portugal [ORCID]
Vegara M: Chemical Engineering Department, University of Alicante, Carretera de San Vicente del Raspeig S/N, San Vicente del Raspeig, 03690 Alicante, Spain
Pérez-Infantes M: Faculty of Biology, University of Murcia, Avda. Teniente Flomesta, 30003 Murcia, Spain
Remmani R: Applied Chemistry Laboratory LCA, University of Biskra, P.O. Box 145, Biskra 07000, Algeria [ORCID]
Ruiz-Canales A: Engineering Department, Miguel Hernández University, Carretera de Beniel, Km 3.2, Orihuela, 03312 Alicante, Spain
Núñez-Gómez D: Plant Production and Microbiology Department, Miguel Hernández University, Carretera de Beniel, Km 3.2, Orihuela, 03312 Alicante, Spain [ORCID]
Martins AA: LEPABE—Laboratory for Process Engineering, Environment, Biotechnology and Energy, Faculty of Engineering, University of Porto (FEUP), R. Dr. Roberto Frias S/N, 4200-465 Porto, Portugal
Mata TM: INEGI—Institute of Science and Innovation in Mechanical and Industrial Engineering, R. Dr. Roberto Frias 400, 4200-465 Porto, Portugal [ORCID]
Vegara M: Chemical Engineering Department, University of Alicante, Carretera de San Vicente del Raspeig S/N, San Vicente del Raspeig, 03690 Alicante, Spain
Pérez-Infantes M: Faculty of Biology, University of Murcia, Avda. Teniente Flomesta, 30003 Murcia, Spain
Remmani R: Applied Chemistry Laboratory LCA, University of Biskra, P.O. Box 145, Biskra 07000, Algeria [ORCID]
Ruiz-Canales A: Engineering Department, Miguel Hernández University, Carretera de Beniel, Km 3.2, Orihuela, 03312 Alicante, Spain
Núñez-Gómez D: Plant Production and Microbiology Department, Miguel Hernández University, Carretera de Beniel, Km 3.2, Orihuela, 03312 Alicante, Spain [ORCID]
Journal Name
Processes
Volume
9
Issue
11
First Page
2085
Year
2021
Publication Date
2021-11-22
ISSN
2227-9717
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Original Submission
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PII: pr9112085, Publication Type: Journal Article
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LAPSE:2023.4557v1
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https://doi.org/10.3390/pr9112085
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