Prediction of indigenous Pseudomonas spp. growth on oyster mushrooms (Pleurotus ostreatus) as a function of storage temperature. (August 2019)

• Record Type: Journal Article
• Authors: Manthou, Evanthia; Tarlak, Fatih; Lianou, Alexandra; Ozdemir, Murat; Zervakis, Georgios I.; Panagou, Efstathios Z.; Nychas, George-John E.
• Is Part Of: Lebensmittel-Wissenschaft + Technologie =. Volume 111(2019)
• Page Start: 506
• Page End: 512
• Publication Date: 2019-08
• Subjects: Growth kinetics -- Microbial spoilage -- Modelling -- Storage experiments; Food industry and trade -- Periodicals; Food -- Composition -- Periodicals; Microbiology -- Periodicals; Nutrition -- Periodicals; 664.005
• DOI: 10.1016/j.lwt.2019.05.062
• Languages: English
• ISSNs: 0023-6438

Abstract

Abstract: The growth kinetic behaviour of Pseudomonas spp. naturally occurring on oyster mushrooms ( Pleurotus ostreatus ) was evaluated during storage at different isothermal conditions (4, 10 and 16 °C), and was described quantitatively using a one-step global parameter estimation method. In the context of this modelling approach, the growth kinetic parameters of maximum specific growth rate ( μ max ) and lag phase duration ( λ ) were estimated using the Baranyi model, whereas the effect of temperature on μ max was described using a secondary square-root-type model. The global model's goodness-of-fit indices of root mean square error (RMSE) and adjusted coefficient of determination (adjusted-R 2 ) were estimated to be 0.206 and 0.948, respectively. The global model was then externally validated using growth data generated during storage of oyster mushrooms under dynamic temperature conditions. Specifically, the differential form of the Baranyi model merged with the square-root-type model was solved numerically using the fourth-order Runge-Kutta method in order to predict the Pseudomonas spp. concentration on mushrooms under fluctuating temperature conditions. The developed dynamic modelling approach exhibited satisfactory performance, with the mean deviation and the mean absolute deviation being −0.10 and 0.22 log CFU/g, respectively. Along with further substantiation and optimization, the developed model should be useful in food quality management systems, aiming in particular at the improvement of the microbiological quality of oyster mushrooms. Highlights: Pseudomonas spp. are the dominant spoilage microorganisms of oyster mushrooms. Pseudomonas growth is described with one-step global parameter estimation. The global model's performance is satisfactory under dynamic temperature conditions. The developed model should be useful in oyster mushrooms' quality management.