Predictive microbial growth modelling for an effective shelf-life extension strategy of Chhana (Indian cottage cheese)

Abstract

This study aims towards understanding microbial growth dynamics in Chhana (Indian cottage cheese) using three different primary models (viz., Logistic, Gompertz, and Barayni) for development of secondary models and relating it with the intrinsic chemical compositional properties of the samples under different storage conditions. For this purpose, Chhana was prepared in a commercial setup and shelf-life studies were performed in isothermal conditions 8 degrees C (with/without im-mersion in whey), 20 degrees C, 37 degrees C and dynamic refrigerated (8 degrees C) condition with immersion in whey. Immersion in whey was effective for extending the shelf life of Chhana. Barayni model was found better than the other models (0.94 0.99). Despite high correlation values all three models presented their own limitations which was then successfully overcome by novel application of three phased linearized growth model. Differential secondary models were successfully developed, and goodness of fit was evaluated with RMSE (0.032-0.084), and prediction rates achieved as high as 96.2%. The developed methods of data analysis and methods of modelling wild microbial population presented in this research would be beneficial in developing valuable insights for estimation/prediction of product shelf-life in a real-life industrial situation.

Published in

Food Control
2023, Volume: 149, article number: 109697Publisher: ELSEVIER SCI LTD

SLU Authors

• Basu, Santanu

  • Department of Molecular Sciences, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Food Science


Publication identifier

DOI: https://doi.org/10.1016/j.foodcont.2023.109697

Permanent link to this page (URI)

https://res.slu.se/id/publ/121892