A Bayesian Approach to Describe and Simulate the pH Evolution of Fresh Meat Products Depending on the Preservation Conditions

Abstract

Measuring the pH of meat products during storage represents an efficient way to monitor microbial spoilage, since pH is often linked to the growth of several spoilage-associated microorganisms under different conditions. The present work aimed to develop a modelling approach to describe and simulate the pH evolution of fresh meat products, depending on the preservation conditions. The measurement of pH on fresh poultry sausages, made with several lactate formulations and packed under three modified atmospheres (MAP), from several industrial production batches, was used as case-study. A hierarchical Bayesian approach was developed to better adjust kinetic models while handling a low number of measurement points. The pH changes were described as a two-phase evolution, with a first decreasing phase followed by a stabilisation phase. This stabilisation likely took place around the 13th day of storage, under all the considered lactate and MAP conditions. The effects of lactate and MAP on pH previously observed were confirmed herein: (i) lactate addition notably slowed down acidification, regardless of the packaging, whereas (ii) the 50%CO2-50%N2 MAP accelerated the acidification phase. The Bayesian modelling workflow—and the script—could be used for further model adaptation for the pH of other food products and/or other preservation strategies.

Improving quality of poultry and its meat products with probiotics, prebiotics, and phytoextracts

“…Hurdle factors ( HF ) with preservative functions disrupt the microbial equilibrium of one or more microorganisms, preventing their growth, reproduction, and even rendering them inactive or dead ( Aaliya et al, 2021 ). The main hurdle factors include temperature, pH, water activity ( Aw ), oxygen reduction value ( Eh ), pressure, irradiation, competitive flora, preservatives, as well as microwave sterilization and high-voltage electric field pulses ( Luong et al, 2022 ). Combining naturally antimicrobial substances with nonthermal processing methods is particularly appealing, as this hurdle technology can effectively preserve the biological activity of these compounds while meeting the preservation standards for most foods ( Peng et al, 2020 ; Bigi et al, 2023 ).…”

Problems and alternatives of testing significance using null hypothesis and P-value in food research

“…Bayesian statistics can be applied in various ways to the food industry. It can estimate the shelf life of food products by analyzing data on degradation and considering factors such as temperature, humidity, and pH (Calle et al, 2006 ; Luong et al, 2022 ). In sensory analysis, Bayesian statistics can evaluate food samples and estimate the distribution of sensory attributes in the population, helping food companies make informed decisions about product development (Calle et al, 2006 ).…”