Management of Listeria monocytogenes in fermented sausages using the Food Safety Objective concept underpinned by stochastic modeling and meta-analysis

The Prevalence and Antibiotic-Resistant of Listeria monocytogenes in Livestock and Poultry Meat in China and the EU from 2001 to 2022: A Systematic Review and Meta-Analysis

To compare the prevalence and antibiotic resistance rate of Listeria monocytogenes in livestock and poultry (beef, pork and chicken) meat between China and the European Union (EU), a meta-analysis was conducted. Ninety-one out of 2156 articles in Chinese and English published between January 2001 and February 2022 were selected from four databases. The prevalence of L. monocytogenes in livestock and poultry (beef, pork and chicken) meat in China and Europe was 7.1% (3152/56,511, 95% CI: 5.8-8.6%) and 8.3% (2264/889,309, 95% CI: 5.9-11.0%), respectively. Moreover, a decreasing trend was observed in both regions over time. Regarding antibiotic resistance, for the resistance to 15 antibiotics, the pooled prevalence was 5.8% (95% CI: 3.1-9.1%). In both regions, the highest prevalence was found in oxacillin, ceftriaxone and tetracycline, and a large difference was reported between China and the EU in ceftriaxone (52.6% vs. 17.3%) and cefotaxime (7.0% vs. 0.0%). Based on the above, it remains a significant challenge to enforce good control measures against the meat-sourced L. monocytogenes both in China and in the EU.

Application of Quantitative Microbiology and Challenge Tests to Reach a Suggested Food Safety Objective in a Middle Eastern-Style Ready-to-Cook Chicken Product

The contamination of ready-to-eat (RTE) and ready-to-cook (RTC) food products is a major global issue raising worry to consumers. Therefore, the behavior of Listeria monocytogenes and Salmonella spp., inoculated on a traditional Middle Eastern (M.E.) ready-to-cook (RTC) chicken product (“Taouk”-style), using the Risk Ranger^® tool and the necessary management options (to accomplish the hypothetical food safety objectives (FSO)), when unsuspecting consumers may taste such a product were the primary subjects of our study. The behavior of the aforementioned pathogens was studied in the presence and absence of a selected natural antimicrobial combination (chitosan [CH] and thyme oil [T]), and were added as a combined treatment (M-CH-T) to the RTs chicken samples, stored at 4 or 8 °C for a period of 8 d. In the product, wherein no antimicrobials were added (control treatment, M), the initial counts of L. monocytogenes increased by ca. 1.5 (4 °C) and 3.0 (8 °C) log colony-forming units (CFU)/g during an 8-d storage. Salmonella spp. numbers did not increase during storage at 4 °C in the non-treated product, but at 8 °C, an increase of ca. 2.5 log CFU/g occurred. Addition of CH in combination with T to the RTC product (M-CH-T) inhibited the growth of L. monocytogenes and produced lower counts of Salmonella at 4 °C. However, M-CH-T treatment was less effective against both pathogens compared to the control after the 6th day of storage (8 °C). Predictive models based on quantitative microbiology, combined with hazard identification applied in the present study, may be potential means of assessing the safety of the RTC chicken products. It must be noted that for warranting the food safety of especially perishable items (e.g., chicken products), an efficient food safety management system must be applied, in addition to testing of the finished product, (e.g., based on the HACCP principles).

Modeling of starter cultures growth for improved Thai sausage fermentation and cost estimating for sausage preparation and transportation

The purpose of this study was to improve Thai fermented sausage flavor by adding starter cultures (i.e., Pediococcus pentosaceus, Pediococcus acidilactici, Weissella cibaria, Lactobacillus plantarum, Lactobacillus pentosus, and Lactobacillus sakei) as compared with naturally fermented sausage. The predictive mathematical models for growth of P. acidilactici and natural lactic acid bacteria (LAB) in Thai fermented sausage were developed to obtain specific prepared sausage quality. Furthermore, comparisons of sausage preparation and transportation cost between nonrefrigerated and refrigerated trucks were studied. The concentration of 3-methyl-butanoic acid synthesized from LAB inoculated sausage was higher than in the control sample which contributed to the flavor forming. Moreover, the proposed unstructured kinetic models of Thai fermented sausage substrates and products describing the consumption of total protein and glucose, and the production of nonprotein nitrogen responsible for flavor enhancer, lactic acid and formic acid concentration were successfully fitted with two selected experimental data sets of the in situ fermentation of Thai fermented sausage. Finally, the transportation of inoculated sausages in a nonrefrigerated truck by combining fermentation process and transportation was more cost efficient for delivering sausages in a long distance.

Impact of Unit Operations From Farm to Fork on Microbial Safety and Quality of Foods

Unit operations modify material properties aiming to produce uniform and high-quality food products with greater acceptance by the increasingly demanding consumers or with longer shelf life and better possibilities of storage and transport. Microorganisms, including bacteria, molds, viruses, and parasites, may have different susceptibilities to unit operations employed during food processing. On-farm (cleaning, selection and classification, cooling, storage, and transport) and on-factory unit operations (heating, refrigeration/freezing, dehydration, modification of atmosphere, irradiation, and physical, chemical, and microbial-based operations) are commonly employed throughout food production chain. The intensity and combination of unit operations along with food composition, packaging, and storage conditions will influence on the dominance of specific microorganisms, which can be pathogenic or responsible for spoilage. Thus, in the context of food safety objective (FSO), the knowledge and the quantification of the effects caused by each step of processing can enable to control and ensure the quality and safety of manufactured products.

Integrating predictive models and sensors to manage food stability in supply chains

Food products move through complex supply chains, which require effective logistics to ensure food safety and to maximize shelf-life. Predictive models offer an efficient means to monitor and manage the safety and quality of perishable foods, however models require environmental data to estimate changes in microbial growth and sensory attributes. Currently, several companies produce Time-Temperature Indicators that react at rates that closely approximate predictive models; these devices are simple and cost-effective for food companies. However, even greater outcomes could be realized using sensors that transfer data to predictive models in real-time. This report describes developments in predictive models designed for supply chain management, as well as advances in environmental sensors. Important innovation can be realized in both supply chain logistics and food safety management by integrating these technologies.