Predictive modeling and sensitivity analysis to estimate the experimental data of inulinase fermentation by Aspergillus niger grown on sugar beet molasses‐based medium optimized using Plackett–Burman Design.
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| Title: | Predictive modeling and sensitivity analysis to estimate the experimental data of inulinase fermentation by Aspergillus niger grown on sugar beet molasses‐based medium optimized using Plackett–Burman Design. |
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| Authors: | Germec, Mustafa1 (AUTHOR), Turhan, Irfan1 (AUTHOR) iturhan@akdeniz.edu.tr |
| Source: | Biotechnology & Applied Biochemistry. Dec2022, Vol. 69 Issue 6, p2399-2421. 23p. |
| Subjects: | Inulase, Aspergillus niger, Sensitivity analysis, Prediction models, Fermentation, Sugar beets |
| Abstract: | The present work aimed to model Aspergillus niger inulinase fermentation performed in the medium using sigmoidal functions, validate the selected models using an independent set of the experimental values, and perform a sensitivity analysis of the selected models. Based on the results, the selected models were Stannard and Fitzhugh models for substrate consumption (R2 = 0.9976 and 0.9974, respectively), Huang model for inulinase production (R2 = 0.9967), Weibull model for invertase‐type production (R2 = 0.9963), and modified logistic model for invertase‐type activity/inulinase activity ratio (R2 = 0.9292) with high R2 values (>0.90). Kinetics predicted by particularly selected models mentioned above fit well with the experimental kinetic results. Besides, validation of the selected models with an independent set of the experimental data indicated that they gave satisfying results with high R2 values for consumption and production (R2 > 0.90). Sensitivity analysis of the selected models showed that the yielded R2 values (R2 ≥ 0.9775) were in good agreement with those obtained from the selected models. Consequently, A. niger inulinase fermentation was successfully modeled and the selected models were successfully validated with an independent set of the observed data. Besides, the sensitivity analysis also verified the reliability of the selected models. Those models can serve as universal equations to describe the A. niger inulinase fermentation. [ABSTRACT FROM AUTHOR] |
| Copyright of Biotechnology & Applied Biochemistry is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 160964985 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Predictive modeling and sensitivity analysis to estimate the experimental data of inulinase fermentation by Aspergillus niger grown on sugar beet molasses‐based medium optimized using Plackett–Burman Design. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Germec%2C+Mustafa%22">Germec, Mustafa</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Turhan%2C+Irfan%22">Turhan, Irfan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> iturhan@akdeniz.edu.tr</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Biotechnology+%26+Applied+Biochemistry%22">Biotechnology & Applied Biochemistry</searchLink>. Dec2022, Vol. 69 Issue 6, p2399-2421. 23p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Inulase%22">Inulase</searchLink><br /><searchLink fieldCode="DE" term="%22Aspergillus+niger%22">Aspergillus niger</searchLink><br /><searchLink fieldCode="DE" term="%22Sensitivity+analysis%22">Sensitivity analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Prediction+models%22">Prediction models</searchLink><br /><searchLink fieldCode="DE" term="%22Fermentation%22">Fermentation</searchLink><br /><searchLink fieldCode="DE" term="%22Sugar+beets%22">Sugar beets</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The present work aimed to model Aspergillus niger inulinase fermentation performed in the medium using sigmoidal functions, validate the selected models using an independent set of the experimental values, and perform a sensitivity analysis of the selected models. Based on the results, the selected models were Stannard and Fitzhugh models for substrate consumption (R2 = 0.9976 and 0.9974, respectively), Huang model for inulinase production (R2 = 0.9967), Weibull model for invertase‐type production (R2 = 0.9963), and modified logistic model for invertase‐type activity/inulinase activity ratio (R2 = 0.9292) with high R2 values (>0.90). Kinetics predicted by particularly selected models mentioned above fit well with the experimental kinetic results. Besides, validation of the selected models with an independent set of the experimental data indicated that they gave satisfying results with high R2 values for consumption and production (R2 > 0.90). Sensitivity analysis of the selected models showed that the yielded R2 values (R2 ≥ 0.9775) were in good agreement with those obtained from the selected models. Consequently, A. niger inulinase fermentation was successfully modeled and the selected models were successfully validated with an independent set of the observed data. Besides, the sensitivity analysis also verified the reliability of the selected models. Those models can serve as universal equations to describe the A. niger inulinase fermentation. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Biotechnology & Applied Biochemistry is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/bab.2291 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 23 StartPage: 2399 Subjects: – SubjectFull: Inulase Type: general – SubjectFull: Aspergillus niger Type: general – SubjectFull: Sensitivity analysis Type: general – SubjectFull: Prediction models Type: general – SubjectFull: Fermentation Type: general – SubjectFull: Sugar beets Type: general Titles: – TitleFull: Predictive modeling and sensitivity analysis to estimate the experimental data of inulinase fermentation by Aspergillus niger grown on sugar beet molasses‐based medium optimized using Plackett–Burman Design. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Germec, Mustafa – PersonEntity: Name: NameFull: Turhan, Irfan IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 08854513 Numbering: – Type: volume Value: 69 – Type: issue Value: 6 Titles: – TitleFull: Biotechnology & Applied Biochemistry Type: main |
| ResultId | 1 |
