AIMC Topic: Food Microbiology
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Rapid and quantitative detection of Botryosphaeria dothidea by surface-enhanced Raman spectroscopy with size-controlled spherical metal nanoparticles combined with machine learning.
International journal of food microbiology
May 30, 2025
Botryosphaeria dothidea infection has become a major factor affecting the quality of postharvest fruits, so detection of B. dothidea infection is very important to control the spread of infection and ensure food safety. In this study, we built a moni...
Rapid and accurate identification of foodborne bacteria: a combined approach using confocal Raman micro-spectroscopy and explainable machine learning.
Analytical and bioanalytical chemistry
Mar 29, 2025
This study proposes a rapid identification method for foodborne pathogens by combining Raman spectroscopy with explainable machine learning. Spectral data of nine common foodborne pathogens are collected using a laser confocal Raman spectrometer, and...
Quantitative prediction of disinfectant tolerance in Listeria monocytogenes using whole genome sequencing and machine learning.
Scientific reports
Mar 26, 2025
Listeria monocytogenes is a potentially severe disease-causing bacteria mainly transmitted through food. This pathogen is of great concern for public health and the food industry in particular. Many countries have implemented thorough regulations, an...
Exploration of Novel Antimicrobial Agents against Foodborne Pathogens via a Deep Learning Approach.
Journal of agricultural and food chemistry
Mar 13, 2025
The emergence of antibiotic-resistant bacteria poses a severe threat to food safety and human health, necessitating an urgent search for novel antimicrobial agents that can be applied in the food industry. This study utilizes a deep learning approach...
Efficient detection of foodborne pathogens via SERS and deep learning: An ADMIN-optimized NAS-Unet approach.
Journal of hazardous materials
Feb 11, 2025
Amid the increasing global challenge of foodborne diseases, there is an urgent need for rapid and precise pathogen detection methods. This study innovatively integrates surface-enhanced Raman Spectroscopy (SERS) with deep learning technology to devel...
Initializing a Public Repository for Hosting Benchmark Datasets to Facilitate Machine Learning Model Development in Food Safety.
Journal of food protection
Feb 6, 2025
While there is clear potential for artificial intelligence (AI) and machine learning (ML) models to help improve food safety, the development and deployment of these models in the food safety domain are by and large lacking. The absence of publicly a...
High-throughput, rapid, and non-destructive detection of common foodborne pathogens via hyperspectral imaging coupled with deep neural networks and support vector machines.
Food research international (Ottawa, Ont.)
Jan 7, 2025
Foodborne pathogens such as Bacillus cereus, Staphylococcus aureus, and Escherichia coli are major causes of gastrointestinal diseases worldwide and frequently contaminate dairy products. Compared to nucleic acid detection and MALDI-TOF MS, hyperspec...
A drop dispenser for simplifying on-farm detection of foodborne pathogens.
PloS one
Dec 31, 2024
Nucleic-acid biosensors have emerged as useful tools for on-farm detection of foodborne pathogens on fresh produce. Such tools are specifically designed to be user-friendly so that a producer can operate them with minimal training and in a few simple...
Deep learning enabled rapid classification of yeast species in food by imaging of yeast microcolonies.
Food research international (Ottawa, Ont.)
Dec 30, 2024
Diverse species of yeasts are commonly associated with food and food production environments. The contamination of food products by spoilage yeasts poses significant challenges, leading to quality degradation and food loss. Similarly, the introductio...
Machine Learning-Assisted Liquid Crystal Optical Sensor Array Using Cysteine-Functionalized Silver Nanotriangles for Pathogen Detection in Food and Water.
ACS applied materials & interfaces
Dec 12, 2024
The challenge of rapid identification of bacteria in food and water still persists as a major health problem. To tackle this matter, we have developed a single-probe liquid crystal (LC)-based optical sensing platform for the differentiation of five c...
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