ArticleFood science and biotechnology2025
Application of machine learning for quantitative analysis of industrial fermentation using image processing.
Article in Food science and biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Hybrid Sensor-Vision Machine Learning for Predicting Mahewu Fermentation Dynamics.Journal of food science · 2026Article
- Pressure-Guided LSTM Modeling for Fermentation Quantification Prediction.Sensors (Basel, Switzerland) · 2025Article
- Intelligent Gas Sensors for Food Safety and Quality Monitoring: Advances, Applications, and Future Directions.Foods (Basel, Switzerland) · 2025Review
- Proposed SmartBarrel System for Monitoring and Assessment of Wine Fermentation Processes Using IoT Nose and Tongue Devices.Sensors (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Real-time Fermentation Quantification Sensor (RFQS) was developed to quantitatively assess fermentation by detecting airlock bubbles created by fermentation gas pressure. The Convolutional Neural Network-based Fermentation Measurement Model was integrated into the RFQS to analyze and classify these bubble images, enabling continuous fermentation monitoring and real-time fermentation degree measurement. Validation experiments revealed that varying the quantities of dry yeast and glucose significantly impacted fermentation duration and degree. Upon fermentation completion, the total degree was calculated using real-time data. These results confirmed that AI-based image processing technology can effectively serve as a quantitative measurement tool in the fermentation food industry.
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Registered trials
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