AIMC Topic: Food Microbiology
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Artificial intelligence-driven quantification of antibiotic-resistant Bacteria in food by color-encoded multiplex hydrogel digital LAMP.
Food chemistry
Dec 4, 2024
Antibiotic-resistant bacteria pose considerable risks to global health, particularly through transmission in the food chain. Herein, we developed the artificial intelligence-driven quantification of antibiotic-resistant bacteria in food using a color...
Intelligent identification of foodborne pathogenic bacteria by self-transfer deep learning and ensemble prediction based on single-cell Raman spectrum.
Talanta
Dec 2, 2024
Foodborne pathogenic infections pose a significant threat to human health. Accurate detection of foodborne diseases is essential in preventing disease transmission. This study proposed an AI model for precisely identifying foodborne pathogenic bacter...
Machine learning-driven fluorescent sensor array using aqueous CsPbBr perovskite quantum dots for rapid detection and sterilization of foodborne pathogens.
Journal of hazardous materials
Nov 24, 2024
With the growing global concern over food safety, the rapid detection and disinfection of foodborne pathogens have become critical in public health. This study presents a novel machine learning-driven fluorescent sensor array utilizing aqueous CsPbBr...
Active Quantum Biomaterials-Enhanced Microrobots for Food Safety.
Small (Weinheim an der Bergstrasse, Germany)
Oct 24, 2024
Timely disruptive tools for the detection of pathogens in foods are needed to face global health and economic challenges. Herein, the utilization of quantum biomaterials-enhanced microrobots (QBEMRs) as autonomous mobile sensors designed for the prec...
Predictive microbiology through the last century. From paper to Excel and towards AI.
Advances in food and nutrition research
Oct 22, 2024
This chapter provides a historical perspective on predictive microbiology: from its inception till its current state, and including potential future developments. A look back to its origins in the 1920s underlies that scientists at the time had great...
Machine Learning Prediction of Leuconostoc spp. Growth Inducing Spoilage in Cooked Deli Foods Considering the Effect of Glycine and Sodium Acetate.
Journal of food protection
Oct 16, 2024
To control spoilage by lactic acid bacteria (Leuconostoc spp.) in cooked deli food, various combinations of environmental and/or intrinsic factors have been employed based on hurdle technology. Since many factors and their combinations greatly influe...
Development and evaluation of statistical and artificial intelligence approaches with microbial shotgun metagenomics data as an untargeted screening tool for use in food production.
mSystems
Oct 10, 2024
UNLABELLED: The increasing knowledge of microbial ecology in food products relating to quality and safety and the established usefulness of machine learning algorithms for anomaly detection in multiple scenarios suggests that the application of micro...
A novel ensemble approach with deep transfer learning for accurate identification of foodborne bacteria from hyperspectral microscopy.
Computational biology and chemistry
Oct 9, 2024
The detection of foodborne bacteria is critical in ensuring both consumer safety and food safety. If these pathogens are not properly identified, it can lead to dangerous cross-contamination. One of the most common methods for classifying bacteria is...
Progress of machine learning-based biosensors for the monitoring of food safety: A review.
Biosensors & bioelectronics
Sep 12, 2024
Rapid urbanization and growing food demand caused people to be concerned about food safety. Biosensors have gained considerable attention for assessing food safety due to selectivity, and sensitivity but poor stability inherently limits their applica...
Machine learning supported single-stranded DNA sensor array for multiple foodborne pathogenic and spoilage bacteria identification in milk.
Food chemistry
Sep 6, 2024
Ensuring food safety through rapid and accurate detection of pathogenic bacteria in food products is a critical challenge in the food supply chain. In this study, a non-specific optical sensor array was proposed for the identification of multiple pat...
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