AIMC Topic: Fermentation

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Sensory and flavor-aroma profiles of passion fruit juice fermented by potentially probiotic Lactiplantibacillus plantarum CCMA 0743 strain.

Food research international (Ottawa, Ont.)
Several non-dairy probiotic beverages are already available to consumers and have been considered suitable carriers for probiotic bacteria. This study aimed to investigate the effect of Lactiplantibacillus plantarum CCMA 0743 in single and co-culture...

Synergisms of machine learning and constraint-based modeling of metabolism for analysis and optimization of fermentation parameters.

Biotechnology journal
Recent noteworthy advances in developing high-performing microbial and mammalian strains have enabled the sustainable production of bio-economically valuable substances such as bio-compounds, biofuels, and biopharmaceuticals. However, to obtain an in...

Kinetic modeling and quasi-economic analysis of fermentative glycolipopeptide biosurfactant production in a medium co-optimized by statistical and neural network approaches.

Preparative biochemistry & biotechnology
This study presents the kinetics of production of a glycolipopeptide biosurfactant in a medium previously co-optimized by response surface and neural network methods to gain some insight into its volumetric and specific productivities for possible sc...

Machine learning applied for metabolic flux-based control of micro-aerated fermentations in bioreactors.

Biotechnology and bioengineering
Various bio-based processes depend on controlled micro-aerobic conditions to achieve a satisfactory product yield. However, the limiting oxygen concentration varies according to the micro-organism employed, while for industrial applications, there is...

Using neural networks to mine text and predict metabolic traits for thousands of microbes.

PLoS computational biology
Microbes can metabolize more chemical compounds than any other group of organisms. As a result, their metabolism is of interest to investigators across biology. Despite the interest, information on metabolism of specific microbes is hard to access. I...

Machine Learning Modeling for Ultrasonication-Mediated Fermentation of Penicillium brevicompactum to Enhance the Release of Mycophenolic Acid.

Ultrasound in medicine & biology
Described here is the modeling used to improve the mycophenolic acid (MPA) titer from Penicillium brevicompactum using central composite design and a comparatively newer, data-centric approach method k-nearest-neighbor algorithm. The two models for e...

A robust soft sensor to monitor 1,3-propanediol fermentation process by Clostridium butyricum based on artificial neural network.

Biotechnology and bioengineering
With the aggravation of environmental pollution and energy crisis, the sustainable microbial fermentation process of converting glycerol to 1,3-propanediol (1,3-PDO) has become an attractive alternative. However, the difficulty in the online measurem...

Gas-phase volatilomic approaches for quality control of brewing hops based on simultaneous GC-MS-IMS and machine learning.

Analytical and bioanalytical chemistry
For the first time, a prototype HS-GC-MS-IMS dual-detection system is presented for the analysis of volatile organic compounds (VOCs) in fields of quality control of brewing hop. With a soft ionization and drift time-based ion separation in IMS and a...

Metatranscriptomics reveals the gene functions and metabolic properties of the major microbial community during Chinese Sichuan Paocai fermentation.

Food microbiology
Chinese Sichuan Paocai (CSP) is one of the world's best-known fermented vegetables with a large presence in the Chinese market. The dynamic microbial community is the main contributor to Paocai fermentation. However, little is known about the ecologi...

An integrated approach based on virtual data augmentation and deep neural networks modeling for VFA production prediction in anaerobic fermentation process.

Water research
Data-driven models are suitable for simulating biological wastewater treatment processes with complex intrinsic mechanisms. However, raw data collected in the early stage of biological experiments are normally not enough to train data-driven models. ...