Food processing and challenges in the food production and quality: The foodomics approach

Ali, Sher; Rezende, Vanessa Theodoro; Ullah, Sana; de Paiva, Esther Lima; Tonin, Fernando Gustavo; Abdullah,; Corassin, Carlos Humberto; Oliveira, Carlos Augusto Fernandes de

doi:10.1016/j.fbio.2023.103217

Cited by 10 publications

(1 citation statement)

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“…These predictive models enable the evaluation of potential risks linked to microbial contamination, facilitating informed decisions concerning food preservation, storage, and distribution [33]. Moreover, the implementation of predictive microbiology has facilitated the formulation of effective approaches to prolonging the shelf life of food products, thereby reducing food waste and ensuring consumer health and satisfaction [34].…”

Section: Advancements In Technologymentioning

confidence: 99%

The Use of Predictive Microbiology for the Prediction of the Shelf Life of Food Products

Tarlak

2023

Foods

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Microbial shelf life refers to the duration of time during which a food product remains safe for consumption in terms of its microbiological quality. Predictive microbiology is a field of science that focuses on using mathematical models and computational techniques to predict the growth, survival, and behaviour of microorganisms in food and other environments. This approach allows researchers, food producers, and regulatory bodies to assess the potential risks associated with microbial contamination and spoilage, enabling informed decisions to be made regarding food safety, quality, and shelf life. Two-step and one-step modelling approaches are modelling techniques with primary and secondary models being used, while the machine learning approach does not require using primary and secondary models for describing the quantitative behaviour of microorganisms, leading to the spoilage of food products. This comprehensive review delves into the various modelling techniques that have found applications in predictive food microbiology for estimating the shelf life of food products. By examining the strengths, limitations, and implications of the different approaches, this review provides an invaluable resource for researchers and practitioners seeking to enhance the accuracy and reliability of microbial shelf life predictions. Ultimately, a deeper understanding of these techniques promises to advance the domain of predictive food microbiology, fostering improved food safety practices, reduced waste, and heightened consumer confidence.

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Section: Advancements In Technologymentioning

confidence: 99%