AIMC Topic: Food Microbiology
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Machine learning models for prediction of Escherichia coli O157:H7 growth in raw ground beef at different storage temperatures.
Meat science
Dec 30, 2023
Shiga toxin-producing Escherichia coli (STEC) can be life-threatening and lead to major outbreaks. The prevention of STEC-related infections can be provided by control measures at all stages of the food chain. The growth performance of E. coli O157:H...
Deep learning enhanced multiplex detection of viable foodborne pathogens in digital microfluidic chip.
Biosensors & bioelectronics
Nov 17, 2023
Culture plating is worldwide accepted as the gold standard for quantifying viable foodborne pathogens. However, it is time-consuming (1-2 days) and requires specialized laboratory and personnel. This study reported a deep learning enhanced digital mi...
Enhanced detection of Listeria monocytogenes using tetraethylenepentamine-functionalized magnetic nanoparticles and LAMP-CRISPR/Cas12a-based biosensor.
Analytica chimica acta
Oct 11, 2023
BACKGROUND: Listeria monocytogenes is a pathogenic bacterium that can lead to severe illnesses, especially among vulnerable populations. Therefore, the development of rapid and sensitive detection methods is vital to prevent and manage foodborne dise...
Post-harvest biocontrol of Salmonella Enteritidis on Chicken breast meat and Shell eggs using multiphage cocktail.
Veterinaria italiana
Sep 30, 2023
The study aimed to evaluate the efficacy of a phage cocktail to reduce Salmonella Enteritidis contamination on perishable food items viz. chicken breast meat and shell eggs using different concentrations. Initially, four bacteriophages €P54, €P59, €P...
Development of prediction software to describe total mesophilic bacteria in spinach using a machine learning-based regression approach.
Food science and technology international = Ciencia y tecnologia de los alimentos internacional
Apr 18, 2023
The purpose of this study was to create a tool for predicting the growth of total mesophilic bacteria in spinach using machine learning-based regression models such as support vector regression, decision tree regression, and Gaussian process regressi...
Accelerating the Detection of Bacteria in Food Using Artificial Intelligence and Optical Imaging.
Applied and environmental microbiology
Dec 19, 2022
In assessing food microbial safety, the presence of Escherichia coli is a critical indicator of fecal contamination. However, conventional detection methods require the isolation of bacterial macrocolonies for biochemical or genetic characterization,...
Toward in-process technology-aided automation for enhanced microbial food safety and quality assurance in milk and beverages processing.
Critical reviews in food science and nutrition
Sep 6, 2022
Ensuring the safety of food products is critical to food production and processing. In food processing and production, several standard guidelines are implemented to achieve acceptable food quality and safety. This notwithstanding, due to human limit...
An Artificial Intelligence Approach Toward Food Spoilage Detection and Analysis.
Frontiers in public health
Jan 12, 2022
Aiming to increase the shelf life of food, researchers are moving toward new methodologies to maintain the quality of food as food grains are susceptible to spoilage due to precipitation, humidity, temperature, and a variety of other influences. As a...
Accurate classification of Listeria species by MALDI-TOF mass spectrometry incorporating denoising autoencoder and machine learning.
Journal of microbiological methods
Nov 21, 2021
Listeria monocytogenes belongs to the category of facultative anaerobic bacteria, and is the pathogen of listeriosis, potentially lethal disease for humans. There are many similarities between L. monocytogenes and other non-pathogenic Listeria specie...
Machine learning approach for predicting the antifungal effect of gilaburu (Viburnum opulus) fruit extracts on Fusarium spp. isolated from diseased potato tubers.
Journal of microbiological methods
Nov 19, 2021
This work addresses the mathematical model building to detect the diameter of the inhibition zone of gilaburu (Viburnum opulus L.) extract against eight different Fusarium strains isolated from diseased potato tubers. Gilaburu extracts were obtained ...
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