| Predicting sensory evaluation of spinach freshness using machine learning model and digital images K Koyama, M Tanaka, BH Cho, Y Yoshikawa, S Koseki Plos one 16 (3), e0248769, 2021 | 43 | 2021 |
| Survival kinetics of Salmonella enterica and enterohemorrhagic Escherichia coli on a plastic surface at low relative humidity and on low–water activity foods H Hokunan, K Koyama, M Hasegawa, S Kawamura, S Koseki Journal of food protection 79 (10), 1680-1692, 2016 | 39 | 2016 |
| Determination of “Hass” avocado ripeness during storage based on smartphone image and machine learning model BH Cho, K Koyama, E Olivares Díaz, S Koseki Food and Bioprocess Technology 13 (9), 1579-1587, 2020 | 33 | 2020 |
| Do bacterial cell numbers follow a theoretical Poisson distribution? Comparison of experimentally obtained numbers of single cells with random number generation via computer … K Koyama, H Hokunan, M Hasegawa, S Kawamura, S Koseki Food microbiology 60, 49-53, 2016 | 31 | 2016 |
| Prediction of population behavior of Listeria monocytogenes in food using machine learning and a microbial growth and survival database S Hiura, S Koseki, K Koyama Scientific reports 11 (1), 10613, 2021 | 29 | 2021 |
| Modeling stochastic variability in the numbers of surviving Salmonella enterica, enterohemorrhagic Escherichia coli, and Listeria monocytogenes cells at the single-cell level … K Koyama, H Hokunan, M Hasegawa, S Kawamura, S Koseki Applied and Environmental Microbiology 83 (4), e02974-16, 2017 | 26 | 2017 |
| Describing uncertainty in Salmonella thermal inactivation using Bayesian statistical modeling K Koyama, Z Aspridou, S Koseki, K Koutsoumanis Frontiers in microbiology 10, 464667, 2019 | 22 | 2019 |
| Stochastic modeling of variability in survival behavior of Bacillus simplex spore population during isothermal inactivation at the single cell level using a Monte Carlo simulation H Abe, K Koyama, S Kawamura, S Koseki Food microbiology 82, 436-444, 2019 | 21 | 2019 |
| Antibacterial properties of melanoidins produced from various combinations of Maillard reaction against pathogenic bacteria S Kukuminato, K Koyama, S Koseki Microbiology spectrum 9 (3), e01142-21, 2021 | 17 | 2021 |
| Stochastic simulation for death probability of bacterial population considering variability in individual cell inactivation time and initial number of cells K Koyama, H Abe, S Kawamura, S Koseki International journal of food microbiology 290, 125-131, 2019 | 17 | 2019 |
| Classification of food spoilage bacterial species and their sodium chloride, sodium acetate and glycine tolerance using chemometrics analysis and Raman spectroscopy T Yamamoto, JN Taylor, S Koseki, K Koyama Journal of Microbiological Methods 190, 106326, 2021 | 16 | 2021 |
| Calculating stochastic inactivation of individual cells in a bacterial population using variability in individual cell inactivation time and initial cell number K Koyama, H Abe, S Kawamura, S Koseki Journal of Theoretical Biology 469, 172-179, 2019 | 16 | 2019 |
| Determination of ‘Hass’ avocado ripeness during storage by a smartphone camera using artificial neural network and support vector regression BH Cho, K Koyama, S Koseki Journal of Food Measurement and Characterization 15 (2), 2021-2030, 2021 | 15 | 2021 |
| Transforming kinetic model into a stochastic inactivation model: Statistical evaluation of stochastic inactivation of individual cells in a bacterial population S Hiura, H Abe, K Koyama, S Koseki Food microbiology 91, 103508, 2020 | 15 | 2020 |
| Recent advances in predictive microbiology: theory and application of conversion from population dynamics to individual cell heterogeneity during inactivation process S Koseki, K Koyama, H Abe Current opinion in food science 39, 60-67, 2021 | 14 | 2021 |
| Development of a Maillard reaction–based time-temperature integrator/indicator (TTI) for visual monitoring of chilled beef during long-term storage and distribution K Sakai, JH Lee, C Kocharunchitt, T Ross, I Jenson, K Koyama, S Koseki Food and Bioprocess Technology 13, 2094-2103, 2020 | 13 | 2020 |
| Estimation of the probability of bacterial population survival: development of a probability model to describe the variability in time to inactivation of Salmonella enterica K Koyama, H Hokunan, M Hasegawa, S Kawamura, S Koseki Food Microbiology 68, 121-128, 2017 | 12 | 2017 |
| Why does Cronobacter sakazakii survive for a long time in dry environments? Contribution of the glass transition of dried bacterial cells K Lee, K Koyama, K Kawai, S Koseki Microbiology Spectrum 9 (3), e01384-21, 2021 | 11 | 2021 |
| Stochastic evaluation of Salmonella enterica lethality during thermal inactivation H Abe, K Koyama, S Kawamura, S Koseki International journal of food microbiology 285, 129-135, 2018 | 11 | 2018 |
| Describing the individual spore variability and the parameter uncertainty in bacterial survival kinetics model by using second-order Monte Carlo simulation H Abe, K Koyama, K Takeoka, S Doto, S Koseki Frontiers in microbiology 11, 985, 2020 | 10 | 2020 |
