Academic Journal
Automatic control technology in fermentation engineering: a review.
| Τίτλος: | Automatic control technology in fermentation engineering: a review. |
|---|---|
| Συγγραφείς: | Jungang, Chuan |
| Πηγή: | Frontiers in Food Science & Technology (2674-1121); 2026, p1-6, 6p |
| Θεματικοί όροι: | Automatic control systems, Fermentation products industry, Detectors, Artificial neural networks, Cloud computing, Digital twin, Fuzzy logic |
| Περίληψη: | Fermentation engineering is a cornerstone of modern biotechnology, playing a pivotal role in the production of pharmaceuticals, biofuels, food additives, and industrial enzymes. The escalating demand for high yields, consistent product quality, and enhanced process efficiency has rendered the integration of advanced automatic control theory indispensable. This technical Mini Review shifts focus from mature data acquisition hardware to advanced control strategies, emphasizing soft sensors as algorithmic bridges for intelligent control, and expanding technical analysis of modern architectures tailored to the non-linear and time-variant nature of biological systems. It addresses key advanced control technologies including fuzzy logic, inverse neural networks (INN), cloud computing, digital twins, evolutive algorithms, and control vector parameterization (CVP), while clarifying the research gap in automated control of organoleptic profiles to ensure final sensory quality. Supported by recent and foundational studies (including recommended citations), this review integrates and analyzes the latest advancements in advanced control for fermentation, equipping researchers and industry professionals with comprehensive insights to foster the intelligent upgrading of fermentation processes. It also discusses challenges in industrial scalability and solutions such as coupling computational fluid dynamics (CFD) with fermentation kinetics. By filling a critical knowledge integration gap within this interdisciplinary domain, it aims to equip researchers and industry professionals with comprehensive insights to foster the intelligent upgrading of fermentation processes. [ABSTRACT FROM AUTHOR] |
| Copyright of Frontiers in Food Science & Technology (2674-1121) is the property of Frontiers Media S.A. 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.) | |
| Βάση Δεδομένων: | Complementary Index |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://resolver.ebsco.com/c/fiv2js/result?sid=EBSCO:edb&genre=article&issn=26741121&ISBN=&volume=&issue=&date=20260617&spage=1&pages=1-6&title=Frontiers in Food Science & Technology (2674-1121)&atitle=Automatic%20control%20technology%20in%20fermentation%20engineering%3A%20a%20review.&aulast=Jungang%2C%20Chuan&id=DOI:10.3389/frfst.2026.1780601 Name: Full Text Finder (for New FTF UI) (ns324271) Category: fullText Text: Full Text Finder MouseOverText: Full Text Finder |
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| Items | – Name: Title Label: Title Group: Ti Data: Automatic control technology in fermentation engineering: a review. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Jungang%2C+Chuan%22">Jungang, Chuan</searchLink> – Name: TitleSource Label: Source Group: Src Data: Frontiers in Food Science & Technology (2674-1121); 2026, p1-6, 6p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Automatic+control+systems%22">Automatic control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Fermentation+products+industry%22">Fermentation products industry</searchLink><br /><searchLink fieldCode="DE" term="%22Detectors%22">Detectors</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Cloud+computing%22">Cloud computing</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+twin%22">Digital twin</searchLink><br /><searchLink fieldCode="DE" term="%22Fuzzy+logic%22">Fuzzy logic</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Fermentation engineering is a cornerstone of modern biotechnology, playing a pivotal role in the production of pharmaceuticals, biofuels, food additives, and industrial enzymes. The escalating demand for high yields, consistent product quality, and enhanced process efficiency has rendered the integration of advanced automatic control theory indispensable. This technical Mini Review shifts focus from mature data acquisition hardware to advanced control strategies, emphasizing soft sensors as algorithmic bridges for intelligent control, and expanding technical analysis of modern architectures tailored to the non-linear and time-variant nature of biological systems. It addresses key advanced control technologies including fuzzy logic, inverse neural networks (INN), cloud computing, digital twins, evolutive algorithms, and control vector parameterization (CVP), while clarifying the research gap in automated control of organoleptic profiles to ensure final sensory quality. Supported by recent and foundational studies (including recommended citations), this review integrates and analyzes the latest advancements in advanced control for fermentation, equipping researchers and industry professionals with comprehensive insights to foster the intelligent upgrading of fermentation processes. It also discusses challenges in industrial scalability and solutions such as coupling computational fluid dynamics (CFD) with fermentation kinetics. By filling a critical knowledge integration gap within this interdisciplinary domain, it aims to equip researchers and industry professionals with comprehensive insights to foster the intelligent upgrading of fermentation processes. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Frontiers in Food Science & Technology (2674-1121) is the property of Frontiers Media S.A. 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: 10.3389/frfst.2026.1780601 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 6 StartPage: 1 Subjects: – SubjectFull: Automatic control systems Type: general – SubjectFull: Fermentation products industry Type: general – SubjectFull: Detectors Type: general – SubjectFull: Artificial neural networks Type: general – SubjectFull: Cloud computing Type: general – SubjectFull: Digital twin Type: general – SubjectFull: Fuzzy logic Type: general Titles: – TitleFull: Automatic control technology in fermentation engineering: a review. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Jungang, Chuan IsPartOfRelationships: – BibEntity: Dates: – D: 17 M: 06 Text: 2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 26741121 Titles: – TitleFull: Frontiers in Food Science & Technology (2674-1121) Type: main |
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