AIMC Topic: Fermentation
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Comparative studies on modeling and optimization of fermentation process conditions for fungal asparaginase production using artificial intelligence and machine learning techniques.
Preparative biochemistry & biotechnology
Jun 19, 2024
The L-asparaginase is commercial enzyme used as chemotherapeutic agent in cancer treatment and food processing agent in backed and fried food industries. In the present research work, the artificial intelligence and machine learning techniques were e...
Modeling and Optimization of an Enhanced Soft Sensor for the Fermentation Process of .
Sensors (Basel, Switzerland)
May 9, 2024
This paper proposes a novel soft sensor modeling approach, MIC-TCA-INGO-LSSVM, to address the decline in performance of soft sensor models during the fermentation process of , caused by changes in working conditions. Initially, the transfer component...
Rapid determination of starch and alcohol contents in fermented grains by hyperspectral imaging combined with data fusion techniques.
Journal of food science
May 8, 2024
Starch and alcohol serve as pivotal indicators in assessing the quality of lees fermentation. In this paper, two hyperspectral imaging (HSI) techniques (visible-near-infrared (Vis-NIR) and NIR) were utilized to acquire separate HSI data, which were t...
Optimization of pullulan production by Aureobasidium pullulans using semi-solid-state fermentation and artificial neural networks: Characterization and antibacterial activity of pullulan impregnated with Ag-TiO nanocomposite.
International journal of biological macromolecules
May 5, 2024
This study presents a novel and efficient approach for pullulan production using artificial neural networks (ANNs) to optimize semi-solid-state fermentation (S-SSF) on faba bean biomass (FBB). This method achieved a record-breaking pullulan yield of ...
Optimization of α-L-arabinofuranosidase CcABF on clarification and beneficial active substances in fermented ginkgo kernel juice by artificial neural network and genetic algorithm.
Food chemistry
Apr 15, 2024
This study aimed at using α-L-arabinofuranosidase CcABF to improve the clarity and active substances in fermented ginkgo kernel juice by artificial neural network (ANN) modeling and genetic algorithm (GA) optimization. A credible three-layer feedforw...
Statistical versus neural network-embedded swarm intelligence optimization of a metallo-neutral-protease production: activity kinetics and food industry applications.
Preparative biochemistry & biotechnology
Mar 16, 2024
An integrated approach involving response surface methodology (RSM) and artificial neural network-ant-colony hybrid optimization (ANN-ACO) was adopted to develop a bioprocess medium to increase the yield of neutral protease under submerged fermentat...
In-depth discovery and taste presentation mechanism studies on umami peptides derived from fermented sea bass based on peptidomics and machine learning.
Food chemistry
Mar 16, 2024
Umami peptides originating from fermented sea bass impart a distinctive flavor to food. Nevertheless, large-scale and rapid screening for umami peptides using conventional techniques is challenging because of problems such as prolonged duration and c...
NIR spectroscopy-CNN-enabled chemometrics for multianalyte monitoring in microbial fermentation.
Biotechnology and bioengineering
Feb 23, 2024
As the biopharmaceutical industry looks to implement Industry 4.0, the need for rapid and robust analytical characterization of analytes has become a pressing priority. Spectroscopic tools, like near-infrared (NIR) spectroscopy, are finding increasin...
Genetic algorithm-based semisupervised convolutional neural network for real-time monitoring of Escherichia coli fermentation of recombinant protein production using a Raman sensor.
Biotechnology and bioengineering
Jan 22, 2024
As a non-destructive sensing technique, Raman spectroscopy is often combined with regression models for real-time detection of key components in microbial cultivation processes. However, achieving accurate model predictions often requires a large amo...
Multimodal deep learning as a next challenge in nutrition research: tailoring fermented dairy products based on -mediated lipid metabolism.
Critical reviews in food science and nutrition
Aug 24, 2023
Deep learning is evolving in nutritional epidemiology to address challenges including precise nutrition and data-driven disease modeling. Fermented dairy products consumption as the implementation of specific dietary priority contributes to a lower r...
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