Modeling the behavior of Listeria monocytogenes in pH-modified chicken salad during cold storage and temperature abuse conditions

Listeria monocytogenes grows at refrigeration temperatures (5C or below) and tolerates various environmental stressors. The Food and Drug Administration specifies a zero tolerance for this pathogen in certain ready-to-eat processed foods. Modeling its dynamic behavior to fluctuation in temperature at various pH levels is critical to the safety of food. This study presents linear and nonlinear models to predict the behavior of L. monocytogenes in pH-modified chicken salad at various cold storage and temperature abuse conditions. A linear model of the kinetics accounting for simple and interactive effects of storage time, temperature and pH was developed. Predictions of the linear model were inconsistent with laboratory observations. The limitations of the linear model were reflected in the poor correlation of model predictions to the observed values (r 2 = 0.58). A proposed nonlinear model was therefore used to model the observed data. The four model parameters (N(0), C c(0), k max and N res ) were optimized for each of the nine treatments. Correlation coefficient (r 2) values ranged from 0.70 (pH 5.2, 7.2C) to 0.99 (pH 4.0, 21.1C), indicating an improved accuracy. Developing a functional and validated microbial predictive model for chicken salad requires further analyses and collection of data at additional pH and temperature values to determine a single set of parameter values that would represent the microbial behavior at the full range of pH and temperatures observed under storage conditions. Future experiments should address the adaptive nature of L. monocytogenes, as the response to environmental stressors affects the survival of the organism in food systems. © 2006, Blackwell Publishing

Modelling the impacts of water efficient technologies on energy intensive water systems in remote and isolated communities

Essential service providers face unique challenges that are specific delivering a secure and safe water and energy supply to remote communities such as islands and isolated mainland townships. Many remote communities rely on energy intensive water supply systems which are inherently costly to operate. Water demand management programmes such as retrofitting households with water-efficient devices and appliances are one way of reducing the water-energy costs in these communities. This paper presents modelling results from a comparison between business as usual and a scenario where water-efficient strategies were retrofitted in households in three remote communities in Northern Australia. The modelling demonstrated considerable savings to both the water and energy average daily consumption and associated economic costs though reduced reliance on desalination plants and bore pumping. The retrofit scenario was shown to reduce water demand by between 14 and 39 ML/y and total energy demand in off-grid communities by between 83 and 208 MWh/y. Cost reductions for delivering treated water to households ranged between around AUD$11,000 and AUD$70,000 per year, depending on uptake rates of the retrofit programme by each community. This paper forms part of Stage 1 of the Remote and Isolated Communities Essential Services (RICES) project. Stage 2 will confirm many of the assumptions underlying the modelling and build on the smart metering datasets and community engagement process currently underway in Stage 1. The overall outcome of the RICES project is to ensure that such strategies are practical to implement on a broader scale to ultimately achieve more sustainable water and energy efficient off-grid communities.Griffith Sciences, Griffith School of EngineeringFull Tex