Response Surface Modeling and Multi-objective Genetic Algorithm Optimization of Polyphenol/terpineol Yield from Luffa cylindrica Oil
Using the Response surface methodology (RSM) and multi-objective genetic algorithm (MOGA) techniques, this study investigated the optimal extraction conditions of polyphenol and terpineol from luffa cylindrica oil. The antioxidant activity was examined using the stable free radical: 2,2-diphenyl-1-p...
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| Vydáno v: | Proceedings of the National Academy of Sciences, India. Section B: Biological sciences Ročník 94; číslo 5; s. 1041 - 1049 |
|---|---|
| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
New Delhi
Springer India
01.11.2024
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| Témata: | |
| ISSN: | 0369-8211, 2250-1746 |
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| Abstract | Using the Response surface methodology (RSM) and multi-objective genetic algorithm (MOGA) techniques, this study investigated the optimal extraction conditions of polyphenol and terpineol from
luffa cylindrica
oil. The antioxidant activity was examined using the stable free radical: 2,2-diphenyl-1-picrylhydrazyl (DPPH). Under optimal conditions,
luffa cylindrica
oil was extracted for terpineol/polyphenol yield analysis. The process was optimized using a Box–Behnken design with a genetic algorithm (GA) solver and response surface technique. The process variables are time and temperature, with terpineol and polyphenol yield being the responses. The ability of the models built from the process variables and the response was assessed using the coefficient of determination (for terpineol:
R
2
—0.9999, Adj
R
2
—0.9998, Pred
R
2
—0.9991; for polyphenol:
R
2
—0.9880, Adj
R
2
—0.9795, Pred
R
2
—0.9149). The results indicated a good agreement between the observed and predicted data. RSM achieved an optimum extraction of 7.71907 mg/g terpineol and 2.36748 mg/g polyphenol at 62.71 °C and 4.87 h. In contrast, MOGA predicted extraction optimal conditions of 7.264 mg/g terpineol and 2.327 mg/g polyphenol was obtained at 60.231 °C and 4 h. While the gas chromatography-mass spectrometry validated the percentages of 29.1 and 16.8 for terpineol and polyphenol, respectively, the Fourier transform infrared spectroscopy showed that terpineol and polyphenol were present at the peak of 1461.1 and 3008.0 cm
−1
. Terpineol and polyphenol also showed significant scavenging of DPPH radicals with (32.5 and 34.5)% at 100 μg/ml. This study's novelty dwells on optimizing the extraction process of terpineol/polyphenol using RSM and GA techniques. |
|---|---|
| AbstractList | Using the Response surface methodology (RSM) and multi-objective genetic algorithm (MOGA) techniques, this study investigated the optimal extraction conditions of polyphenol and terpineol from luffa cylindrica oil. The antioxidant activity was examined using the stable free radical: 2,2-diphenyl-1-picrylhydrazyl (DPPH). Under optimal conditions, luffa cylindrica oil was extracted for terpineol/polyphenol yield analysis. The process was optimized using a Box–Behnken design with a genetic algorithm (GA) solver and response surface technique. The process variables are time and temperature, with terpineol and polyphenol yield being the responses. The ability of the models built from the process variables and the response was assessed using the coefficient of determination (for terpineol: R²—0.9999, Adj R²—0.9998, Pred R²—0.9991; for polyphenol: R²—0.9880, Adj R²—0.9795, Pred R²—0.9149). The results indicated a good agreement between the observed and predicted data. RSM achieved an optimum extraction of 7.71907 mg/g terpineol and 2.36748 mg/g polyphenol at 62.71 °C and 4.87 h. In contrast, MOGA predicted extraction optimal conditions of 7.264 mg/g terpineol and 2.327 mg/g polyphenol was obtained at 60.231 °C and 4 h. While the gas chromatography-mass spectrometry validated the percentages of 29.1 and 16.8 for terpineol and polyphenol, respectively, the Fourier transform infrared spectroscopy showed that terpineol and polyphenol were present at the peak of 1461.1 and 3008.0 cm⁻¹. Terpineol and polyphenol also showed significant scavenging of DPPH radicals with (32.5 and 34.5)% at 100 μg/ml. This study's novelty dwells on optimizing the extraction process of terpineol/polyphenol using RSM and GA techniques. Using the Response surface methodology (RSM) and multi-objective genetic algorithm (MOGA) techniques, this study investigated the optimal extraction conditions of polyphenol and terpineol from luffa cylindrica oil. The antioxidant activity was examined using the stable free radical: 2,2-diphenyl-1-picrylhydrazyl (DPPH). Under optimal conditions, luffa cylindrica oil was extracted for terpineol/polyphenol yield analysis. The process was optimized using a Box–Behnken design with a genetic algorithm (GA) solver and response surface technique. The process variables are time and temperature, with terpineol and polyphenol yield being the responses. The ability of the models built from the process variables and the response was assessed using the coefficient of determination (for terpineol: R 2 —0.9999, Adj R 2 —0.9998, Pred R 2 —0.9991; for polyphenol: R 2 —0.9880, Adj R 2 —0.9795, Pred R 2 —0.9149). The results indicated a good agreement between the observed and predicted data. RSM achieved an optimum extraction of 7.71907 mg/g terpineol and 2.36748 mg/g polyphenol at 62.71 °C and 4.87 h. In contrast, MOGA predicted extraction optimal conditions of 7.264 mg/g terpineol and 2.327 mg/g polyphenol was obtained at 60.231 °C and 4 h. While the gas chromatography-mass spectrometry validated the percentages of 29.1 and 16.8 for terpineol and polyphenol, respectively, the Fourier transform infrared spectroscopy showed that terpineol and polyphenol were present at the peak of 1461.1 and 3008.0 cm −1 . Terpineol and polyphenol also showed significant scavenging of DPPH radicals with (32.5 and 34.5)% at 100 μg/ml. This study's novelty dwells on optimizing the extraction process of terpineol/polyphenol using RSM and GA techniques. |
| Author | Dzarma, Goziya W. Nwosu, Ozioma Linus, Chiemenem Udemgba, Chinonso Nwosu-Obieogu, Kenechi |
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| Cites_doi | 10.3390/antiox8120647 10.1016/j.heliyon.2022.e09216 10.1016/j.clet.2021.100360 10.54287/gujsa.972137 10.1016/j.clcb.2022.100019 10.1039/C9RA10349J 10.1111/jfpp.15078 10.1007/s11694-018-9974-2 10.1134/S2070050420020129 10.1155/2020/1251957 10.1007/s41660-021-00210-6 10.5958/0974-0112.2022.00013.5 10.1007/s00500-020-05009-0 10.1016/j.compchemeng.2019.106618 10.1016/j.foodchem.2020.127862 10.1007/s11947-020-02461-6 10.1007/s13399-021-01329-9 10.1051/e3sconf/202014201006 10.1155/2018/6391414 |
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| References | Rui Min, Aileen, Shao, Lassabliere, Kwong-Chee, Jingcan, Haxel, Lay, Wen, Bin (CR29) 2019; 6 Nwosu-Obieogu, Dzarma, Ugwuodo, Chiemenem, Akatobi (CR1) 2022; 6 Oke, Nwosu-Obieogu, Okolo, Adeyi, Omotoso (CR11) 2022; 23 Silva, Pogacnik (CR10) 2020; 9 Oke, Nwosu-Obieogu, Okolo, Adeyi, Ude (CR22) 2021; 1 CR15 Raghavendra, Sethi, Bhowmik, Varghese, Joshi (CR18) 2022; 79 Agu, Menkiti, Agulanna, Okolo, Nwosu-Obieogu (CR26) 2022; 6 Sales, Felipe, Bicas (CR3) 2020; 8 Stagos (CR9) 2019; 9 Nwosu-Obieogu (CR19) 2021; 8 Zainullin, Zagoruiko, Koledina, Gubaidullin, Faskhutdinova (CR20) 2020; 12 Kakhki, Mohammadpoor, Faridi, Bahadori (CR24) 2020; 10 Khaleel, Tabanca, Buchbauer (CR4) 2017; 2018 Adeyi, Oke, Okolo, Adeyi, Otolorin, Nwosu-Obieogu, Onu (CR13) 2022; 8 Kahlaoui, Vechhia, Giovine, Kbaier, Bouzouita, Pereira, Zeppa (CR8) 2019; 8 CR2 Haya, Bentahar, Trari (CR28) 2019; 13 Campone, Celano, Rizzo, Piccinelli, Rastrelli, Russo (CR5) 2020; 2 CR7 Skrypnik, Novikova (CR6) 2020; 10 CR23 Aguele, Nwosu-Obieogu, Osoh, Onyekwulu, Chiemenem (CR14) 2021; 1 Su, Jin, Zhang, Shen, Eden, Ren (CR21) 2020; 132 Abdullah, Pradhan, Pradhan, Mishra (CR16) 2021; 339 Gino Sophia, Ceronmani Sharmila, Suchitra, Sudalai Muthu, Pavithra (CR25) 2020; 24 Nwosu-Obieogu, Adeyi, Dzarma (CR27) 2022; 5 Rakshit, Srivastav (CR17) 2021; 45 Nwosu-Obieogu, Dzarma, Chiemenem (CR12) 2021; 14 RZ Zainullin (1635_CR20) 2020; 12 L Campone (1635_CR5) 2020; 2 FO Aguele (1635_CR14) 2021; 1 D Stagos (1635_CR9) 2019; 9 L Skrypnik (1635_CR6) 2020; 10 Y Su (1635_CR21) 2020; 132 RM Kakhki (1635_CR24) 2020; 10 1635_CR15 K Nwosu-Obieogu (1635_CR27) 2022; 5 EO Oke (1635_CR11) 2022; 23 M Kahlaoui (1635_CR8) 2019; 8 SG Gino Sophia (1635_CR25) 2020; 24 O Adeyi (1635_CR13) 2022; 8 S Abdullah (1635_CR16) 2021; 339 K Nwosu-Obieogu (1635_CR12) 2021; 14 1635_CR2 HR Raghavendra (1635_CR18) 2022; 79 K Nwosu-Obieogu (1635_CR19) 2021; 8 M Rakshit (1635_CR17) 2021; 45 1635_CR23 CM Agu (1635_CR26) 2022; 6 K Nwosu-Obieogu (1635_CR1) 2022; 6 RFM Silva (1635_CR10) 2020; 9 VG Rui Min (1635_CR29) 2019; 6 EM Oke (1635_CR22) 2021; 1 A Sales (1635_CR3) 2020; 8 S Haya (1635_CR28) 2019; 13 1635_CR7 C Khaleel (1635_CR4) 2017; 2018 |
| References_xml | – volume: 8 start-page: 647 issue: 12 year: 2019 end-page: 654 ident: CR8 article-title: Characterization of polyphenolic compounds extracted from different varieties of almond hulls (Prunus dulcis L.) publication-title: Antioxidants doi: 10.3390/antiox8120647 – ident: CR2 – volume: 8 start-page: e09216 issue: 4 year: 2022 ident: CR13 article-title: Process optimization, scale-up studies, economic analysis, and risk assessment of phenolic-rich bioactive extracts production from Carica papaya L. leaves via heat-assisted extraction technology publication-title: Heliyon doi: 10.1016/j.heliyon.2022.e09216 – volume: 6 start-page: 100360 year: 2022 ident: CR26 article-title: Modeling methyl ester yield from Terminalia catappa L. kernel oil by artificial neural network and response surface methodology for possible industrial application publication-title: Clean Eng Technol doi: 10.1016/j.clet.2021.100360 – volume: 8 start-page: 494 issue: 4 year: 2021 end-page: 504 ident: CR19 article-title: Artificial neural network predictive modelling of seed oil antioxidant yield publication-title: Gazi Univ J Sci Part A Eng Innov doi: 10.54287/gujsa.972137 – volume: 5 start-page: 100019 year: 2022 ident: CR27 article-title: Response surface methodology and artificial neural network modelling and optimization of peel sulphuric acid hydrolysis publication-title: Clean Circular Bioecon doi: 10.1016/j.clcb.2022.100019 – volume: 10 start-page: 5951 issue: 10 year: 2020 end-page: 5960 ident: CR24 article-title: The development of an artificial neural network–genetic algorithm model (ANN-GA) for the adsorption and photocatalysis of methylene blue on a novel sulfur–nitrogen co- doped Fe 2 O 3 nanostructure surface publication-title: RSC Adv doi: 10.1039/C9RA10349J – volume: 6 start-page: 1 issue: 2 year: 2019 end-page: 10 ident: CR29 article-title: Characterization of volatile and non-volatile compounds in pomelo by gas chromatography-olfactometry, gas chromatography-quadrupole time-of-flight mass spectrometry publication-title: J Essential Oil Res – ident: CR23 – volume: 14 start-page: 65 issue: 4 year: 2021 end-page: 68 ident: CR12 article-title: ANFIS prediction of antioxidant yields for publication-title: Acta Technica Corviniensis-Bulletin of Engineering – volume: 1 start-page: 1 year: 2021 end-page: 15 ident: CR22 article-title: oil epoxidation: hybrid genetic algorithm-neural fuzzy-Box Bhenken (GA-ANFIS-BB) modeling with sensitivity and uncertainty analyses publication-title: Multiscale Multidiscip Modell Exp Des – volume: 23 start-page: 103 issue: 2 year: 2022 end-page: 118 ident: CR11 article-title: Optimization of the extraction of antioxidant compounds from the plant publication-title: Sci Study Res Chem Chem Eng Biotechnol Food Ind – volume: 45 issue: 1 year: 2021 ident: CR17 article-title: Optimization of pulsed ultrasonic-assisted extraction of punicalagin from pomegranate (Punica granatum) peel: a comparison between response surface methodology and artificial neural network-multiobjective genetic algorithm publication-title: J Food Process Preserv doi: 10.1111/jfpp.15078 – volume: 1 start-page: 61 year: 2021 end-page: 68 ident: CR14 article-title: Optimization of the epoxidation process parameters of huracrepitan seed oil publication-title: Ann Faculty Eng Hunedoara Internation J Eng – volume: 10 start-page: 1 issue: 92 year: 2020 end-page: 18 ident: CR6 article-title: Response surface modeling and optimization of polyphenols extraction from apple pomace based on nonionic emulsifiers publication-title: Agronomy – volume: 13 start-page: 614 issue: 1 year: 2019 end-page: 621 ident: CR28 article-title: Optimization of polyphenols extraction from orange peel publication-title: J Food Measure Character doi: 10.1007/s11694-018-9974-2 – ident: CR15 – volume: 12 start-page: 133 issue: 2 year: 2020 end-page: 140 ident: CR20 article-title: Multi-criterion optimization of a catalytic reforming reactor unit using a genetic algorithm publication-title: Catal Ind doi: 10.1134/S2070050420020129 – volume: 2018 start-page: 349 issue: 16 year: 2017 end-page: 361 ident: CR4 article-title: α- Terpineol, a natural monoterpene: a review of its biological properties publication-title: Open Chem – volume: 2 start-page: 1 issue: 4 year: 2020 end-page: 9 ident: CR5 article-title: Development of an enriched polyphenol (natural antioxidant) extract from orange juice ( by adsorption on macroporous resins publication-title: J Food Qual doi: 10.1155/2020/1251957 – volume: 6 start-page: 175 issue: 1 year: 2022 end-page: 188 ident: CR1 article-title: Seed oil extraction: response surface and neuro-fuzzy modelling performance evaluation and optimization publication-title: Process Integrat Opt Sustain doi: 10.1007/s41660-021-00210-6 – volume: 79 start-page: 83 issue: 1 year: 2022 end-page: 90 ident: CR18 article-title: Phenolics from potato peel and its extraction intensification using response surface methodology and genetic algorithm approach publication-title: Indian J Horticulture doi: 10.5958/0974-0112.2022.00013.5 – volume: 24 start-page: 17153 issue: 22 year: 2020 end-page: 17165 ident: CR25 article-title: Water management using genetic algorithm-based machine learning publication-title: Soft Comput doi: 10.1007/s00500-020-05009-0 – volume: 9 start-page: 1 issue: 61 year: 2020 end-page: 13 ident: CR10 article-title: Polyphenols from foods and natural products: Neuroprotection and safety publication-title: Antioxidants – volume: 132 year: 2020 ident: CR21 article-title: Stakeholder-oriented multi-objective process optimization based on an improved genetic algorithm publication-title: Comput Chem Eng doi: 10.1016/j.compchemeng.2019.106618 – ident: CR7 – volume: 339 year: 2021 ident: CR16 article-title: Modeling and optimization of pectinase-assisted low-temperature extraction of cashew apple juice using artificial neural network coupled with genetic algorithm publication-title: Food Chem doi: 10.1016/j.foodchem.2020.127862 – volume: 8 start-page: 120 year: 2020 end-page: 125 ident: CR3 article-title: Production, properties and application of terpineol publication-title: Food Bioprocess Technol doi: 10.1007/s11947-020-02461-6 – volume: 9 start-page: 1 issue: 19 year: 2019 end-page: 7 ident: CR9 article-title: Antioxidant activity of polyphenolic plant extracts publication-title: Antioxidants – volume: 8 start-page: 494 issue: 4 year: 2021 ident: 1635_CR19 publication-title: Gazi Univ J Sci Part A Eng Innov doi: 10.54287/gujsa.972137 – volume: 1 start-page: 1 year: 2021 ident: 1635_CR22 publication-title: Multiscale Multidiscip Modell Exp Des – volume: 2018 start-page: 349 issue: 16 year: 2017 ident: 1635_CR4 publication-title: Open Chem – volume: 5 start-page: 100019 year: 2022 ident: 1635_CR27 publication-title: Clean Circular Bioecon doi: 10.1016/j.clcb.2022.100019 – volume: 6 start-page: 175 issue: 1 year: 2022 ident: 1635_CR1 publication-title: Process Integrat Opt Sustain doi: 10.1007/s41660-021-00210-6 – volume: 8 start-page: 120 year: 2020 ident: 1635_CR3 publication-title: Food Bioprocess Technol doi: 10.1007/s11947-020-02461-6 – volume: 9 start-page: 1 issue: 61 year: 2020 ident: 1635_CR10 publication-title: Antioxidants – volume: 339 year: 2021 ident: 1635_CR16 publication-title: Food Chem doi: 10.1016/j.foodchem.2020.127862 – volume: 6 start-page: 1 issue: 2 year: 2019 ident: 1635_CR29 publication-title: J Essential Oil Res – volume: 9 start-page: 1 issue: 19 year: 2019 ident: 1635_CR9 publication-title: Antioxidants – volume: 79 start-page: 83 issue: 1 year: 2022 ident: 1635_CR18 publication-title: Indian J Horticulture doi: 10.5958/0974-0112.2022.00013.5 – volume: 6 start-page: 100360 year: 2022 ident: 1635_CR26 publication-title: Clean Eng Technol doi: 10.1016/j.clet.2021.100360 – volume: 10 start-page: 5951 issue: 10 year: 2020 ident: 1635_CR24 publication-title: RSC Adv doi: 10.1039/C9RA10349J – ident: 1635_CR15 – volume: 23 start-page: 103 issue: 2 year: 2022 ident: 1635_CR11 publication-title: Sci Study Res Chem Chem Eng Biotechnol Food Ind – volume: 12 start-page: 133 issue: 2 year: 2020 ident: 1635_CR20 publication-title: Catal Ind doi: 10.1134/S2070050420020129 – volume: 132 year: 2020 ident: 1635_CR21 publication-title: Comput Chem Eng doi: 10.1016/j.compchemeng.2019.106618 – volume: 1 start-page: 61 year: 2021 ident: 1635_CR14 publication-title: Ann Faculty Eng Hunedoara Internation J Eng – volume: 14 start-page: 65 issue: 4 year: 2021 ident: 1635_CR12 publication-title: Acta Technica Corviniensis-Bulletin of Engineering – volume: 8 start-page: e09216 issue: 4 year: 2022 ident: 1635_CR13 publication-title: Heliyon doi: 10.1016/j.heliyon.2022.e09216 – volume: 8 start-page: 647 issue: 12 year: 2019 ident: 1635_CR8 publication-title: Antioxidants doi: 10.3390/antiox8120647 – ident: 1635_CR23 doi: 10.1007/s13399-021-01329-9 – ident: 1635_CR7 doi: 10.1051/e3sconf/202014201006 – volume: 10 start-page: 1 issue: 92 year: 2020 ident: 1635_CR6 publication-title: Agronomy – volume: 13 start-page: 614 issue: 1 year: 2019 ident: 1635_CR28 publication-title: J Food Measure Character doi: 10.1007/s11694-018-9974-2 – ident: 1635_CR2 doi: 10.1155/2018/6391414 – volume: 2 start-page: 1 issue: 4 year: 2020 ident: 1635_CR5 publication-title: J Food Qual doi: 10.1155/2020/1251957 – volume: 24 start-page: 17153 issue: 22 year: 2020 ident: 1635_CR25 publication-title: Soft Comput doi: 10.1007/s00500-020-05009-0 – volume: 45 issue: 1 year: 2021 ident: 1635_CR17 publication-title: J Food Process Preserv doi: 10.1111/jfpp.15078 |
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| SubjectTerms | 2,2-diphenyl-1-picrylhydrazyl algorithms antioxidant activity Behavioral Sciences Biomedical and Life Sciences Fourier transform infrared spectroscopy free radicals gas chromatography-mass spectrometry India Life Sciences Luffa aegyptiaca Nucleic Acid Chemistry oils Plant Biochemistry polyphenols Research Article response surface methodology temperature terpineol |
| Title | Response Surface Modeling and Multi-objective Genetic Algorithm Optimization of Polyphenol/terpineol Yield from Luffa cylindrica Oil |
| URI | https://link.springer.com/article/10.1007/s40011-024-01635-y https://www.proquest.com/docview/3154181720 |
| Volume | 94 |
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