Microbiological and Modeling Approach to Derive Performance Objectives for Bacillus cereus Group in Ready‐to‐Eat Salads

In this article, the performance objectives (POs) for Bacillus cereus group (BC) in celery, cheese, and spelt added as ingredients in a ready‐to‐eat mixed spelt salad, packaged under modified atmosphere, were calculated using a Bayesian approach. In order to derive the POs, BC detection and enumeration were performed in nine lots of naturally contaminated ingredients and final product. Moreover, the impact of specific production steps on the BC contamination was quantified. Finally, a sampling plan to verify the ingredient lots' compliance with each PO value at a 95% confidence level (CL) was defined. To calculate the POs, detection results as well as results above the limit of detection but below the limit of quantification (i.e., censored data) were analyzed. The most probable distribution of the censored data was determined and two‐dimensional (2D) Monte Carlo simulations were performed. The PO values were calculated to meet a food safety objective of 4 log₁₀ cfu of BC for g of spelt salad at the time of consumption. When BC grows during storage between 0.90 and 1.90 log₁₀ cfu/g, the POs for BC in celery, cheese, and spelt ranged between 1.21 log₁₀ cfu/g for celery and 2.45 log₁₀ cfu/g for spelt. This article represents the first attempt to manage the concept of PO and 2D Monte Carlo simulation in the flow chart of a complex food matrix, including raw and cooked ingredients.     

Estimating Listeria monocytogenes Growth in Ready-to-Eat Chicken Salad Using a Challenge Test for Quantitative Microbial Risk Assessment

Currently, there is a growing preference for convenience food products, such as ready-to-eat (RTE) foods, associated with long refrigerated shelf-lives, not requiring a heat treatment prior to consumption. Because Listeria monocytogenes is able to grow at refrigeration temperatures, inconsistent temperatures during production, distribution, and at consumer's household may allow for the pathogen to thrive, reaching unsafe limits. L. monocytogenes is the causative agent of listeriosis, a rare but severe human illness, with high fatality rates, transmitted almost exclusively by food consumption. With the aim of assessing the quantitative microbial risk of L. monocytogenes in RTE chicken salads, a challenge test was performed. Salads were inoculated with a three-strain mixture of cold-adapted L. monocytogenes and stored at 4, 12, and 16 °C for eight days. Results revealed that the salad was able to support L. monocytogenes’ growth, even at refrigeration temperatures. The Baranyi primary model was fitted to microbiological data to estimate the pathogen's growth kinetic parameters. Temperature effect on the maximum specific growth rate (μ_max) was modeled using a square-root-type model. Storage temperature significantly influenced μ_max of L. monocytogenes (p < 0.05). These predicted growth models for L. monocytogenes were subsequently used to develop a quantitative microbial risk assessment, estimating a median number of 0.00008726 listeriosis cases per year linked to the consumption of these RTE salads. Sensitivity analysis considering different time–temperature scenarios indicated a very low median risk per portion (<−7 log), even if the assessed RTE chicken salad was kept in abuse storage conditions.     

Modeling Virus Inactivation on Salad Crops Using Microbial Count Data

Microbial counts of the persistent Bacteroides fragilis bacteriophage B40-8 from a virus decay experiment conducted under glasshouse conditions were used to model the decay of viruses on wastewater-irrigated lettuce and carrot crops. The modeling approach applied gave specific consideration to the discrete nature of microbial count data. The experimental counts were best fit by a negative binomial distribution indicating highly dispersed distribution of viruses on lettuce and carrot crops following irrigation with wastewater. In addition, there was evidence for biphasic inactivation of viruses, signifying the presence of a persistent subpopulation of viruses that decayed slowly, resulting in virus accumulation on the crop surface over subsequent irrigations. Maximum likelihood estimates of initial and persistent subpopulation inactivation rates were 2.48 day(-1) and 0.51 day(-1) for lettuces and 0.84 day(-1) and 0.046 day(-1) for carrots. Maximum likelihood estimates of the persistent virus subpopulation size were 0.12% and 2% for lettuce and carrots, respectively.