Scientific journal

59 2020

Journal of Food and Nutrition Research
Summary No. 4 / 2020

Tarlak, F.
Development and validation of one-step modelling approach for prediction of mushroom spoilage
Journal of Food and Nutrition Research, 59, 2020, No. 4, s. 281-289

Fatih Tarlak, Department of Nutrition and Dietetics, Faculty of Health Science, Istanbul Gedik University, Cumhuriyet Street Number: 1, 34876 Kartal, Istanbul, Turkey. E-mail: ftarlak@gtu.edu.tr

Received 8 July 2020; 1st revised 18 August 2020; accepted 25 September 2020; published online 4 October 2020.

Summary: The primary aims of this work were to improve the prediction capability of the traditionally used two-step modelling approach with the most popular primary growth models in the predictive food microbiology field, and to validate the prediction capability of the one-step modelling approach, a proposed alternative way to traditional modelling approach. For this purpose, the growth behaviour of Pseudomonas spp. existing in the natural microflora of button mushrooms (Agaricus bisporus) was simulated with two-step and one-step modelling approaches. The Baranyi model yielded the best fitting performance when it was employed in the two-step modelling approach. The fitting capability of all the primary models was also compared using the one-step modelling approach. No matter which primary model was used, the one-step modelling approach significantly improved the prediction capability of the models, and all the primary models gave root mean squared error lower than 0.299 and adjusted coefficient of determination higher than 0.948. Successfully validated Baranyi model in one-step modelling approach provided the highest prediction capability and exhibited considerable potential to be used as a prediction tool. This indicated that the one-step modelling approach could be reliably employed to assess and predict mushroom spoilage as a function of time and storage temperature.

Keywords: one-step modelling approach; simulation; mushroom spoilage; prediction

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