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Colony Count, Microbial

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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
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...

Near-infrared spectroscopy coupled with chemometrics algorithms for the quantitative determination of the germinability of Clostridium perfringens in four different matrices.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Clostridium perfringens (C. perfringens) has the ability to form metabolically-dormant spores that can survive food preservation processes and cause food spoilage and foodborne safety risks upon germination outgrowth. This study was conducted to inve...

Evaluation of a protocol for reducing the microbial contamination of dental unit water.

Acta odontologica latinoamericana : AOL
Biofilm on dental unit waterlines can spread microbial contamination in the water. The aim of this study was to investigate microbial contamination of water from supplies and dental units before and after the implementation of a protocol for microbia...

Use of high-content analysis and machine learning to characterize complex microbial samples via morphological analysis.

PloS one
High Content Analysis (HCA) has become a cornerstone of cellular analysis within the drug discovery industry. To expand the capabilities of HCA, we have applied the same analysis methods, validated in numerous mammalian cell models, to microbiology m...

Microbial contamination and efficacy of disinfection procedures of companion robots in care homes.

PloS one
BACKGROUND: Paro and other robot animals can improve wellbeing for older adults and people with dementia, through reducing depression, agitation and medication use. However, nursing and care staff we contacted expressed infection control concerns. Li...

Unified Classification of Bacterial Colonies on Different Agar Media Based on Hyperspectral Imaging and Machine Learning.

Molecules (Basel, Switzerland)
A universal method by considering different types of culture media can enable convenient classification of bacterial species. The study combined hyperspectral technology and versatile chemometric algorithms to achieve the rapid and non-destructive cl...

A fully automated deep learning pipeline for high-throughput colony segmentation and classification.

Biology open
Adenine auxotrophy is a commonly used non-selective genetic marker in yeast research. It allows investigators to easily visualize and quantify various genetic and epigenetic events by simply reading out colony color. However, manual counting of large...

Prediction of population behavior of Listeria monocytogenes in food using machine learning and a microbial growth and survival database.

Scientific reports
In predictive microbiology, statistical models are employed to predict bacterial population behavior in food using environmental factors such as temperature, pH, and water activity. As the amount and complexity of data increase, handling all data wit...

Accelerating the Detection of Bacteria in Food Using Artificial Intelligence and Optical Imaging.

Applied and environmental microbiology
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,...

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
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...