Prediction of growth of Pseudomonas fluorescens in milk during storage under fluctuating temperature
Accurate prediction of growth of undesirable organisms (e.g., Pseudomonas fluorescens) in perishable foods (e.g., milk), held under sub-ideal storage conditions, can help ensure the quality and safety of these foods at the point of consumption. In this investigation, we inoculated sterile milk with...
Gespeichert in:
Veröffentlicht in: | Journal of dairy science 2016-03, Vol.99 (3), p.1822-1830 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Accurate prediction of growth of undesirable organisms (e.g., Pseudomonas fluorescens) in perishable foods (e.g., milk), held under sub-ideal storage conditions, can help ensure the quality and safety of these foods at the point of consumption. In this investigation, we inoculated sterile milk with P. fluorescens (~103cfu/mL) and monitored inoculum growth behavior at constant and fluctuating storage temperatures. Three storage temperatures, 4°C, 15°C and 29°C, were selected to simulate proper refrigeration conditions (4°C) and temperature abuse, respectively. To simulate temperature fluctuation, milk held at 4°C was subjected to temperature shifts to 15°C or 29°C for 4 to 6h. A modified logistic model was used to obtain the best-fit curve for the microbial growth under constant storage temperature. The specific growth rates at 4°C, 15°C, and 29°C, obtained from experimental data, were 0.056±0.00, 0.17±0.05, and 0.46±0.02h−1, respectively, and the lag time values were 29.5±4.2, 12.7±4.4, and 2.8±0.3h, respectively. A model predicting bacterial growth under different temperature fluctuations was obtained using the growth parameters extracted from constant temperature experiments. Growth behavior predicted by the fluctuating temperature model and that obtained experimentally were in good agreement. Lag time exhibited a larger variation compared with specific growth rate, suggesting that it depends not only on growth temperature but also on the sample population and temperature gradient. Additionally, experimental data showed that changing the temperature during the lag phase induced an additional lag time before growth; however, no significant lag time was observed under the temperature fluctuation during the exponential phase. The results of this study provide information for precise shelf-life determination and reduction of food waste, particularly for milk and milk-containing food products. |
---|---|
ISSN: | 0022-0302 1525-3198 |
DOI: | 10.3168/jds.2015-10179 |