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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...

Study on Multi-Model Soft Sensor Modeling Method and Its Model Optimization for the Fermentation Process of .

Sensors (Basel, Switzerland)
The problems that the key biomass variables in fermentation process are difficult measure in real time; this paper mainly proposes a multi-model soft sensor modeling method based on the piecewise affine (PWA) modeling method, which is optimized by p...

AI-based forecasting of ethanol fermentation using yeast morphological data.

Bioscience, biotechnology, and biochemistry
Several industries require getting information of products as soon as possible during fermentation. However, the trade-off between sensing speed and data quantity presents challenges for forecasting fermentation product yields. In this study, we trie...

Soft Sensor Modeling Method Based on Improved KH-RBF Neural Network Bacteria Concentration in Marine Alkaline Protease Fermentation Process.

Applied biochemistry and biotechnology
Marine alkaline protease (MAP) fermentation is a complex multivariable, multi-coupled, and nonlinear process. Some unmeasured parameters will affect the quality of protease. Aiming at the problem that some parameters are difficult to be detected onli...

Research on soft sensing method of photosynthetic bacteria fermentation process based on ant colony algorithm and least squares support vector machine.

Preparative biochemistry & biotechnology
Photosynthetic bacteria wastewater treatment is an efficient water pollution treatment method, but photosynthetic bacteria fermentation is a multivariable, non-linear, and time-varying process. So it is difficult to establish an accurate model. Aimin...

Continuous biomanufacturing with microbes - upstream progresses and challenges.

Current opinion in biotechnology
Current biomanufacturing facilities are mainly built for batch or fed-batch operations, which are subject to low productivities and do not achieve the great bioconversion potential of the rewired cells generated via modern biotechnology. Continuous b...

An evolutionary deep learning soft sensor model based on random forest feature selection technique for penicillin fermentation process.

ISA transactions
Accurate and reliable measurement of key biological parameters during penicillin fermentation is of great significance for improving penicillin production. In this research context, a new hybrid soft sensor model method based on RF-IHHO-LSTM (random ...

The monitoring of oil production process by deep learning based on morphology in oleaginous yeasts.

Applied microbiology and biotechnology
BACKGROUND: Monitoring jar fermenter-cultured microorganisms in real time is important for controlling productivity of bioproducts in large-scale cultivation settings. Morphological data is used to understand the growth and fermentation states of the...

Machine learning in fermentative biohydrogen production: Advantages, challenges, and applications.

Bioresource technology
Hydrogen can be produced in an environmentally friendly manner through biological processes using a variety of organic waste and biomass as feedstock. However, the complexity of biological processes limits their predictability and reliability, which ...

Prediction of ethanol fermentation under stressed conditions using yeast morphological data.

Journal of bioscience and bioengineering
A high sugar concentration is used as a starting condition in alcoholic fermentation by budding yeast, which shows changes in intracellular state and cell morphology under conditions of high-sugar stress. In this study, we developed artificial intell...