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Mathematical Models to Describe the Kinetic Behavior of Staphylococcus aureus in Jerky.

Jimyeong HaJeeyeon LeeSoomin LeeSejeong KimYukyung ChoiHyemin OhYujin KimYewon LeeYeongeun SeoYohan Yoon
Published in: Food science of animal resources (2019)
The objective of this study was to develop mathematical models for describing the kinetic behavior of Staphylococcus aureus (S. aureus) in seasoned beef jerky. Seasoned beef jerky was cut into 10-g pieces. Next, 0.1 mL of S. aureus ATCC13565 was inoculated into the samples to obtain 3 Log CFU/g, and the samples were stored aerobically at 10°C, 20°C, 25°C, 30°C, and 35°C for 600 h. S. aureus cell counts were enumerated on Baird Parker agar during storage. To develop a primary model, the Weibull model was fitted to the cell count data to calculate Delta (required time for the first decimal reduction) and ρ (shape of curves). For secondary modeling, a polynomial model was fitted to the Delta values as a function of storage temperature. To evaluate the accuracy of the model prediction, the root mean square error (RMSE) was calculated by comparing the predicted data with the observed data. The surviving S. aureus cell counts were decreased at all storage temperatures. The Delta values were longer at 10°C, 20°C, and 25°C than at 30°C and 35°C. The secondary model well-described the temperature effect on Delta with an R2 value of 0.920. In validation analysis, RMSE values of 0.325 suggested that the model performance was appropriate. S. aureus in beef jerky survives for a long period at low storage temperatures and that the model developed in this study is useful for describing the kinetic behavior of S. aureus in seasoned beef jerky.
Keyphrases
  • staphylococcus aureus
  • single cell
  • electronic health record
  • stem cells
  • machine learning
  • big data
  • mesenchymal stem cells
  • pseudomonas aeruginosa
  • peripheral blood
  • biofilm formation