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

Scientific reports, 2021-05, Vol.11 (1), p.10613-10613, Article 10613

2021

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Microbial Responses Viewer (MRV): A new ComBase-derived database of microbial responses to food environments

International journal of food microbiology, 2009-08, Vol.134 (1), p.75-82

Koseki, Shige

2009

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Development of automatic detection model for stem-end rots of ‘Hass’ avocado fruit using X-ray imaging and image processing

Postharvest biology and technology, 2022-10, Vol.192, p.111996, Article 111996

2022

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Predicting sensory evaluation of spinach freshness using machine learning model and digital images

PloS one, 2021-03, Vol.16 (3), p.e0248769-e0248769

2021

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Calculating stochastic inactivation of individual cells in a bacterial population using variability in individual cell inactivation time and initial cell number

Journal of theoretical biology, 2019-05, Vol.469, p.172-179

2019

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Evaluation of Strain Variability in Inactivation of Campylobacter jejuni in Simulated Gastric Fluid by Using Hierarchical Bayesian Modeling

Applied and environmental microbiology, 2021-07, Vol.87 (15), p.e0091821-e0091821

2021

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Bayesian Generalized Linear Model for Simulating Bacterial Inactivation/Growth Considering Variability and Uncertainty

Frontiers in microbiology, 2021-06, Vol.12, p.674364-674364

2021

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Describing Uncertainty in Salmonella Thermal Inactivation Using Bayesian Statistical Modeling

Frontiers in microbiology, 2019-09, Vol.10, p.2239-2239

2019

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Study on the quality and myofibrillar protein structure of chicken breasts during thawing of ultrasound-assisted slightly acidic electrolyzed water (SAEW)

Ultrasonics sonochemistry, 2022-08, Vol.88, p.106105-106105, Article 106105

2022

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Alternative Approach To Modeling Bacterial Lag Time, Using Logistic Regression as a Function of Time, Temperature, pH, and Sodium Chloride Concentration

Applied and Environmental Microbiology, 2012-09, Vol.78 (17), p.6103-6112

2012

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Modeling of Pathogen Survival during Simulated Gastric Digestion

Applied and Environmental Microbiology, 2011-02, Vol.77 (3), p.1021-1032

2011

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Data mining for prediction and interpretation of bacterial population behavior in food

Frontiers in Food Science and Technology (Online), 2022-12, Vol.2

2022

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Prevalence and antimicrobial resistance of Shiga toxin-producing Escherichia coli in milk and dairy products in Egypt

Journal of environmental science and health. Part B, Pesticides, food contaminants, and agricultural wastes, 2020-03, Vol.55 (3), p.265-272

2020

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A Novel Approach to Predict the Growth of Staphylococcus aureus on Rice Cake

Frontiers in microbiology, 2017-06, Vol.8, p.1140-1140

2017

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Prediction of a Required Log Reduction with Probability for Enterobacter sakazakii during High-Pressure Processing, Using a Survival/Death Interface Model

Applied and Environmental Microbiology, 2009-04, Vol.75 (7), p.1885-1891

2009

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Thermal Stability of Fructooligosaccharides Extracted from Defatted Rice Bran: A Kinetic Study Using Liquid Chromatography-Tandem Mass Spectrometry

Foods, 2022-07, Vol.11 (14), p.2054

2022

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Automated detection of internal fruit rot in Hass avocado via deep learning-based semantic segmentation of X-ray images

Postharvest biology and technology, 2023-09, Vol.203, p.112390, Article 112390

2023

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Hierarchical ranking sensory evaluation test of fresh produce quality: A case study of injured cherry tomato images

Food quality and preference, 2024-09, Vol.118, p.105167, Article 105167

2024

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Is skipping the definition of primary and secondary models possible? Prediction of Escherichia coli O157 growth by machine learning

Journal of microbiological methods, 2022-01, Vol.192, p.106366-106366, Article 106366

2022

Volltextzugriff (PDF)

Alternative approaches to predicting microbial behaviour: A probabilistic modelling approach for microbial inactivation and a revised web-tool, the Microbial Responses Viewer

Food control, 2013-02, Vol.29 (2), p.416-421

Koseki, Shige

2013

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Prediction of growth/no growth status of previously unseen bacterial strain using Raman spectroscopy and machine learning

Food science & technology, 2023-01, Vol.174, p.114449, Article 114449

2023

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Growth-Inhibitory Effect of d-Tryptophan on Vibrio spp. in Shucked and Live Oysters

Applied and environmental microbiology, 2018-10, Vol.84 (19)

2018

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Application of growth rate from kinetic model to calculate stochastic growth of a bacteria population at low contamination level

Journal of theoretical biology, 2021-09, Vol.525, p.110758-110758, Article 110758

2021

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Classification of food spoilage bacterial species and their sodium chloride, sodium acetate and glycine tolerance using chemometrics analysis and Raman spectroscopy

Journal of microbiological methods, 2021-11, Vol.190, p.106326-106326, Article 106326

2021

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Recent advances in predictive microbiology: theory and application of conversion from population dynamics to individual cell heterogeneity during inactivation process

Current opinion in food science, 2021-06, Vol.39, p.60-67

2021

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

Microbial Responses Viewer (MRV): A new ComBase-derived database of microbial responses to food environments

Development of automatic detection model for stem-end rots of ‘Hass’ avocado fruit using X-ray imaging and image processing

Predicting sensory evaluation of spinach freshness using machine learning model and digital images

Calculating stochastic inactivation of individual cells in a bacterial population using variability in individual cell inactivation time and initial cell number

Evaluation of Strain Variability in Inactivation of Campylobacter jejuni in Simulated Gastric Fluid by Using Hierarchical Bayesian Modeling

Bayesian Generalized Linear Model for Simulating Bacterial Inactivation/Growth Considering Variability and Uncertainty

Describing Uncertainty in Salmonella Thermal Inactivation Using Bayesian Statistical Modeling

Study on the quality and myofibrillar protein structure of chicken breasts during thawing of ultrasound-assisted slightly acidic electrolyzed water (SAEW)

Alternative Approach To Modeling Bacterial Lag Time, Using Logistic Regression as a Function of Time, Temperature, pH, and Sodium Chloride Concentration

Modeling of Pathogen Survival during Simulated Gastric Digestion

Data mining for prediction and interpretation of bacterial population behavior in food

Prevalence and antimicrobial resistance of Shiga toxin-producing Escherichia coli in milk and dairy products in Egypt

A Novel Approach to Predict the Growth of Staphylococcus aureus on Rice Cake

Prediction of a Required Log Reduction with Probability for Enterobacter sakazakii during High-Pressure Processing, Using a Survival/Death Interface Model

Thermal Stability of Fructooligosaccharides Extracted from Defatted Rice Bran: A Kinetic Study Using Liquid Chromatography-Tandem Mass Spectrometry

Automated detection of internal fruit rot in Hass avocado via deep learning-based semantic segmentation of X-ray images

Hierarchical ranking sensory evaluation test of fresh produce quality: A case study of injured cherry tomato images

Is skipping the definition of primary and secondary models possible? Prediction of Escherichia coli O157 growth by machine learning

Alternative approaches to predicting microbial behaviour: A probabilistic modelling approach for microbial inactivation and a revised web-tool, the Microbial Responses Viewer

Prediction of growth/no growth status of previously unseen bacterial strain using Raman spectroscopy and machine learning

Growth-Inhibitory Effect of d-Tryptophan on Vibrio spp. in Shucked and Live Oysters

Application of growth rate from kinetic model to calculate stochastic growth of a bacteria population at low contamination level

Classification of food spoilage bacterial species and their sodium chloride, sodium acetate and glycine tolerance using chemometrics analysis and Raman spectroscopy

Recent advances in predictive microbiology: theory and application of conversion from population dynamics to individual cell heterogeneity during inactivation process

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