Modeling and Validation of the Effects of Amino Group Concentrations in Food on the Growth of Escherichia coli

Predictive models for bacterial growth developed on the basis of experimental data obtained from culture media often yield different results from observations in actual foods. Although this discrepancy may be due to differences in compositional characteristics, food structure, and other factors, the...

Full description

Saved in:
Bibliographic Details
Main Authors: Masaki Kato, Kento Koyama, Shige Koseki
Format: Article
Language:English
Published: Elsevier 2025-05-01
Series:Journal of Food Protection
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S0362028X2500064X
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850269559791026176
author Masaki Kato
Kento Koyama
Shige Koseki
author_facet Masaki Kato
Kento Koyama
Shige Koseki
author_sort Masaki Kato
collection DOAJ
description Predictive models for bacterial growth developed on the basis of experimental data obtained from culture media often yield different results from observations in actual foods. Although this discrepancy may be due to differences in compositional characteristics, food structure, and other factors, the impacts on bacterial behavior have not yet been quantified and modeled mathematically. This study first aimed to quantify the effects of amino group concentrations on the growth kinetics of Escherichia coli. A predictive model incorporating the effect of the amino group concentration was subsequently developed, and its potential for improving prediction accuracy in foods was verified. The growth kinetics of E. coli ATCC 25922 were examined at 37 °C in a protein mixture comprising albumin (0.001–30% (w/w)) and phosphate-buffered saline. The maximum specific growth rate (μmax) and maximum population density (Nmax) estimated by the Baranyi and Roberts models were successfully described as equations of the amino group concentration in the form of Monod’s model (Monod, 1949)and logarithm, respectively. The developed μmax equation was further incorporated into the square-root type μmax model developed by Ross (2003) to improve the predictive robustness. The model performance was validated using the experimentally obtained changes in E. coli numbers over time in actual foods. The root mean squared error (RMSE) of the model incorporating amino group concentration was better (RMSE = 0.652) than that of the model without amino group concentration (RMSE = 0.681). Notably, for lettuce, the prediction accuracy was significantly improved with the model incorporating amino group concentration (RMSE = 0.661) compared to the model without it (RMSE = 1.015). The developed model incorporating the effect of the amino group concentration indicated the potential to reduce the discrepancy between observed bacterial growth in actual foods and model predictions depending on the food type.
format Article
id doaj-art-0174c2bd07a646b28502d96910dce9a5
institution OA Journals
issn 0362-028X
language English
publishDate 2025-05-01
publisher Elsevier
record_format Article
series Journal of Food Protection
spelling doaj-art-0174c2bd07a646b28502d96910dce9a52025-08-20T01:53:05ZengElsevierJournal of Food Protection0362-028X2025-05-0188610051210.1016/j.jfp.2025.100512Modeling and Validation of the Effects of Amino Group Concentrations in Food on the Growth of Escherichia coliMasaki Kato0Kento Koyama1Shige Koseki2Graduate School of Agricultural Science, Hokkaido University, Kita-9, Nishi-9, Kita-ku, Sapporo 060-8589, JapanGraduate School of Agricultural Science, Hokkaido University, Kita-9, Nishi-9, Kita-ku, Sapporo 060-8589, JapanCorresponding author.; Graduate School of Agricultural Science, Hokkaido University, Kita-9, Nishi-9, Kita-ku, Sapporo 060-8589, JapanPredictive models for bacterial growth developed on the basis of experimental data obtained from culture media often yield different results from observations in actual foods. Although this discrepancy may be due to differences in compositional characteristics, food structure, and other factors, the impacts on bacterial behavior have not yet been quantified and modeled mathematically. This study first aimed to quantify the effects of amino group concentrations on the growth kinetics of Escherichia coli. A predictive model incorporating the effect of the amino group concentration was subsequently developed, and its potential for improving prediction accuracy in foods was verified. The growth kinetics of E. coli ATCC 25922 were examined at 37 °C in a protein mixture comprising albumin (0.001–30% (w/w)) and phosphate-buffered saline. The maximum specific growth rate (μmax) and maximum population density (Nmax) estimated by the Baranyi and Roberts models were successfully described as equations of the amino group concentration in the form of Monod’s model (Monod, 1949)and logarithm, respectively. The developed μmax equation was further incorporated into the square-root type μmax model developed by Ross (2003) to improve the predictive robustness. The model performance was validated using the experimentally obtained changes in E. coli numbers over time in actual foods. The root mean squared error (RMSE) of the model incorporating amino group concentration was better (RMSE = 0.652) than that of the model without amino group concentration (RMSE = 0.681). Notably, for lettuce, the prediction accuracy was significantly improved with the model incorporating amino group concentration (RMSE = 0.661) compared to the model without it (RMSE = 1.015). The developed model incorporating the effect of the amino group concentration indicated the potential to reduce the discrepancy between observed bacterial growth in actual foods and model predictions depending on the food type.http://www.sciencedirect.com/science/article/pii/S0362028X2500064XGrowth kineticsNinhydrin reactionPredictive microbiologyProtein
spellingShingle Masaki Kato
Kento Koyama
Shige Koseki
Modeling and Validation of the Effects of Amino Group Concentrations in Food on the Growth of Escherichia coli
Journal of Food Protection
Growth kinetics
Ninhydrin reaction
Predictive microbiology
Protein
title Modeling and Validation of the Effects of Amino Group Concentrations in Food on the Growth of Escherichia coli
title_full Modeling and Validation of the Effects of Amino Group Concentrations in Food on the Growth of Escherichia coli
title_fullStr Modeling and Validation of the Effects of Amino Group Concentrations in Food on the Growth of Escherichia coli
title_full_unstemmed Modeling and Validation of the Effects of Amino Group Concentrations in Food on the Growth of Escherichia coli
title_short Modeling and Validation of the Effects of Amino Group Concentrations in Food on the Growth of Escherichia coli
title_sort modeling and validation of the effects of amino group concentrations in food on the growth of escherichia coli
topic Growth kinetics
Ninhydrin reaction
Predictive microbiology
Protein
url http://www.sciencedirect.com/science/article/pii/S0362028X2500064X
work_keys_str_mv AT masakikato modelingandvalidationoftheeffectsofaminogroupconcentrationsinfoodonthegrowthofescherichiacoli
AT kentokoyama modelingandvalidationoftheeffectsofaminogroupconcentrationsinfoodonthegrowthofescherichiacoli
AT shigekoseki modelingandvalidationoftheeffectsofaminogroupconcentrationsinfoodonthegrowthofescherichiacoli