The growth of Aeromonas hydrophila and aerobic natural flora (APC) on gilthead seabream surfaces was evaluated during the refrigerated storage (21 days). The related growth curves were compared with those obtained by a conventional third order predictive model obtaining a low agreement between observed and predicted data (Root Mean Squared Error = 1.77 for Aeromonas hydrophila and 0.64 for APC). The Lotka-Volterra interspecific competition model was used in order to calculate the degree of interaction between the two bacterial populations (βAh/APC and βAPC/Ah, respectively, the interspecific competition coefficients of APC on Aeromonas hydrophila and vice-versa). Afterwards, the Lotka- Volterra equations were applied as tertiary predictive model, taking into account, simultaneously, the environmental fluctuations and the bacterial interspecific competition. This approach allowed to obtain a best fitting to the observed mean growth curves with a Root Mean Squared Error of 0.09 for Aeromonas hydrophila and 0.28 for APC. Finally, authors carry out some considerations about the necessary use of competitive models in the context of the new trends in predictive microbiology.

Application of an interspecific competition model to predict the growth of Aeromonas hydrophila on fish surfaces during refrigerated storage

GIUFFRIDA, Alessandro;ZIINO, Graziella;DONATO, Giorgio;PANEBIANCO, Antonio
2007-01-01

Abstract

The growth of Aeromonas hydrophila and aerobic natural flora (APC) on gilthead seabream surfaces was evaluated during the refrigerated storage (21 days). The related growth curves were compared with those obtained by a conventional third order predictive model obtaining a low agreement between observed and predicted data (Root Mean Squared Error = 1.77 for Aeromonas hydrophila and 0.64 for APC). The Lotka-Volterra interspecific competition model was used in order to calculate the degree of interaction between the two bacterial populations (βAh/APC and βAPC/Ah, respectively, the interspecific competition coefficients of APC on Aeromonas hydrophila and vice-versa). Afterwards, the Lotka- Volterra equations were applied as tertiary predictive model, taking into account, simultaneously, the environmental fluctuations and the bacterial interspecific competition. This approach allowed to obtain a best fitting to the observed mean growth curves with a Root Mean Squared Error of 0.09 for Aeromonas hydrophila and 0.28 for APC. Finally, authors carry out some considerations about the necessary use of competitive models in the context of the new trends in predictive microbiology.
2007
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/1831909
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