Foodborne pathogens such as Listeria spp. contain the ability to survive and multiply in poultry farming environments, which provides a route of contamination for poultry processing environments and ...final poultry products. An understanding of the effect of meteorological variables on the prevalence of Listeria spp. in the farming environment is lacking. Soil and feces samples were collected from 11 pastured poultry farms from 2014 to 2017. Random forest (RF) and gradient boosting machine (GBM) predictive models were generated to describe and predict Listeria spp. prevalence in feces and soil samples based on meteorological factors at the farming location. This study attempted to demonstrate the use of GBM models in a food safety context and compare their use to RF models. Both feces models performed very well, with area under the curve (AUC) values of 0.905 and 0.855 for the RF and GBM models, respectively. The soil GBM model outperformed the RF model with AUCs of 0.873 and 0.700, respectively. The developed models can be used to predict the prevalence of Listeria spp. in pastured poultry farm environments and should be of great use to poultry farmers, producers, and risk managers.
Display omitted
•Environmental samples were evaluated from poultry farms for Listeria prevalence.•Listeria prevalence can be predicted by machine learning models based on weather.•Wind speed, temperature, and humidity affect Listeria spp. prevalence.•This study provides a framework for future use of machine learning in food safety.
Salmonella and Campylobacter are common bacterial hazards causing foodborne illnesses worldwide. A large proportion of Salmonella and Campylobacter illnesses are attributed to contaminated poultry ...products that are mishandled or under cooked. Processing interventions such as chilling and post-chill dip are critical to reducing microbial contamination of poultry. A comprehensive search of the literature published between 2000 and 2021 was conducted in the databases Web of Science, Academic Search Complete, and Academic OneFile. Studies were included if they were in English and investigated the effects of interventions against Salmonella and/or Campylobacter on whole carcasses and/or parts during the chilling or post-chill stages of poultry processing. Random-effects meta-analyses were performed using the “meta” package in the R programming language. Subgroup analyses were assessed according to outcome measure reported, microorganism tested, processing stage assessed, and chemical treatment used. The results included 41 eligible studies. Eighteen studies reported results of 28 separate interventions against Salmonella and 31 reported results of 50 separate interventions against Campylobacter. No significant difference (P> 0.05) was observed when comparing the combined mean difference of all interventions targeting Salmonella to the combined mean difference of all interventions targeting Campylobacter or when comparing chilling times within each pathogen subgroup. For analyses examining antimicrobial additives, peroxyacetic acid (PAA) had the largest reduction against Salmonella population regardless of chilling time (P< 0.05). PAA also had the largest reduction against Campylobacter population and prevalence during primary chilling (P< 0.01). Air chilling showed a lower reduction for Campylobacter than any immersion chilling intervention (P< 0.05). Chilling time and antimicrobial used during poultry processing had varying effects depending on the pathogen and outcome measure investigated (concentration or prevalence). High heterogeneity and low sample numbers in most analyses suggest that more high-quality research that is well-designed and has transparent reporting of methodology and results is needed to corroborate the results.
•Microbiome provides the relationship between farm management, the environment, and the host.•Knowledge of various microbiomes across the processing chain improves food safety management.•This review ...outlines the relationship between foodborne pathogens and microbiomes in chickens.
Despite the continuous progress in food science and technology, the global burden of foodborne illnesses remains substantial, with pathogens in food causing millions of infections each year. Traditional microbiological culture methods are inadequate in detecting the full spectrum of these microorganisms, highlighting the need for more comprehensive detection strategies. This review paper aims to elucidate the relationship between foodborne pathogen colonization and the composition of the poultry microbiome, and how this knowledge can be used for improved food safety. Our review highlights that the relationship between pathogen colonization varies across different sections of the poultry microbiome. Further, our review suggests that the microbiome profile of poultry litter, farm soil, and farm dust may serve as potential indicators of the farm environment's food safety issues. We also agree that the microbiome of processed chicken samples may reveal potential pathogen contamination and food quality issues. In addition, utilizing predictive modeling techniques on the collected microbiome data, we suggest establishing correlations between particular taxonomic groups and the colonization of pathogens, thus providing insights into food safety, and offering a comprehensive overview of the microbial community. In conclusion, this review underscores the potential of microbiome analysis as a powerful tool in food safety, pathogen detection, and risk assessment.
The occurrence of antibiotic resistant (ABR) bacteria in foods is a growing public health challenge. We evaluated sanitizer cross-tolerance among ABR
(
) O157:H7 and non-O157:H7 Shiga-toxin producing
...(STEC) serogroups. Sanitizer tolerance in STEC could be a public health concern as mitigation strategies against the pathogen might be compromised.
Resistance to ampicillin and streptomycin were evolved in
serogroups: O157:H7 (H1730, and ATCC 43895), O121:H19 and O26:H11. Resistance to antibiotics was evolved chromosomally through incremental exposure to ampicillin (amp C) and streptomycin (strep C). Transformation using a plasmid was performed to confer resistance to ampicillin to generate amp P strep C.
The minimum inhibitory concentration (MIC) of lactic acid for all strains evaluated was 0.375% v/v. Analysis of bacterial growth parameters in tryptic soy broth amended with 0.0625% v/v, 0.125% v/v, and 0.25% v/v (subMIC) lactic acid indicated that growth correlated positively with the lag phase duration, and negatively with both the maximum growth rate and change in population density for all strains evaluated except for the highly tolerant variant- O157:H7 amp P strep C. Strains O121 NR (non-ABR), O121 amp C, O121 amp P strep C, O157:H7 H1730 amp C and O157:H7 H1730 amp P strep C were not inactivated after exposure to 1% and 2.5% v/v lactic acid for 300 s. No recovery of cells was observed after the strains were exposed to 5% v/v lactic acid for 300 s. ABR strains O157:H7 H1730 amp C and O157: H7 H1730 amp P strep C demonstrated a high tolerance to lactic acid (
≤ 0.05).
ABR in isolate
O157: H7 H1730 may improve tolerance to lactic acid. Increased tolerance may be discerned by evaluating growth parameters of bacteria in presence of sub-MIC levels of lactic acid.
The antimicrobial properties of Pelargonic acid (PA), a component of tomatoes, makes it an attractive candidate as a food additive and sanitizer. The antimicrobial efficacy of PA emulsions generated ...using surfactants: Tween 80, Triton X100, Sodium Dodecyl Sulfate (SDS) and Quillaja Saponin was evaluated against Salmonella serotypes Newport, Oranienburg and Typhimurium. Micelle/dropletsize, and minimal inhibitory concentrations (MIC) were determined. Surfactant type and concentration significantly influenced the antimicrobial efficacy of PA (p < 0.05). Overall, Salmonella Newport was the most (p < 0.05) susceptible serotype to PA emulsions. PA emulsions generated with 1.00% SDS had the highest (p < 0.05) antimicrobial activity, with MIC of 7.82 mM against S. Newport and 15.62 mM against S. Oranienburg/S. Typhimurium, respectively. Addition of PA to Trypticase Soy Broth resulted in a decreased growth rate and an increased lag phase duration. Cells exposed to PA formed elongated filaments (>5 µm). Additionally, Salmonella serotypes Typhimurium and Newport also formed floccular biofilms. PA emulsions at a concentration of 31.25 mM generated using 1% SDS and 1% Quillaja saponin resulted in >6 log CFU/ml reduction in Salmonella population. Althought all PA emulsions evalauted inhibited Salmonella, morphological changes to this antimicrobial varied substantially among the Salmonella serotypes tested.
Millets have various nutrition qualities, and have rightly been called “nutri-cereals”. Wheat is traditionally used in breads, and consumption of millet can be increased by replacing wheat by millet ...to a required extent. The aim of this study was to optimize millet-based composite flours for the preparation of breads. Barnyard-millet and wheat composite flour (BWCF) was formulated and prepared by mixing 61.8 g/100 g barnyard-millet, 31.4 g/100 g wheat and 6.8 g/100 g gluten. Another formulation barnyard-millet, finger-millet, proso-millet and wheat composite flour (BFPWCF) was developed using 9.1 g/100 g barnyard, 10.1 g/100 g finger-millet, 10.2 g/100 g proso-millet and 69.6 g/100 g wheat. Bread samples were prepared using two composite flours and wheat flour, which was used to compare the quality of the breads prepared from the composite flours. A sensory study was conducted for analysis of acceptability of these samples. The analysis of this sensory study was conducted using fuzzy logic. The results of sensory analysis showed that the acceptability of bread samples prepared from composite flours was almost equal to the wheat bread.
► Preparation of millet-based dough and breads. ► Study of extensibility, firmness and color of the breads. ► Sensory analysis of prepared bread samples using fuzzy logic and comparison with control (wheat bread).
Recently, there has been a consumer push for natural and organic food products. This has caused alternative poultry production, such as organic, pasture, and free-range systems, to grow in ...popularity. Due to the stricter rearing practices of alternative poultry production systems, different types of levels of microbiological risks might be present for these systems when compared to conventional production systems. Both conventional and alternative production systems have complex supply chains that present many different opportunities for flocks of birds or poultry meat to be contaminated with foodborne pathogens. As such, it is important to understand the risks involved during each step of production. The purpose of this review is to detail the potential routes of foodborne pathogen transmission throughout the conventional and alternative supply chains, with a special emphasis on the differences in risk between the two management systems, and to identify gaps in knowledge that could assist, if addressed, in poultry risk-based decision making.
In December, 2019, a highly infectious and rapidly spreading new pneumonia of unknown cause was reported to the Chinese WHO Country Office. A cluster of these cases had appeared in Wuhan, a city in ...the Hubei Province of China. These infections were found to be caused by a new coronavirus which was given the name "2019 novel coronavirus" (2019-nCoV). It was later renamed "severe acute respiratory syndrome coronavirus 2," or SARS-CoV-2 by the International Committee on Taxonomy of Viruses on February 11, 2020. It was named SARS-CoV-2 due to its close genetic similarity to the coronavirus which caused the SARS outbreak in 2002 (SARS-CoV-1). The aim of this review is to provide information, primarily to the food industry, regarding a range of biocides effective in eliminating or reducing the presence of coronaviruses from fomites, skin, oral/nasal mucosa, air, and food contact surfaces. As several EPA approved sanitizers against SARS-CoV-2 are commonly used by food processors, these compounds are primarily discussed as much of the industry already has them on site and is familiar with their application and use. Specifically, we focused on the effects of alcohols, povidone iodine, quaternary ammonium compounds, hydrogen peroxide, sodium hypochlorite (NaOCl), peroxyacetic acid (PAA), chlorine dioxide, ozone, ultraviolet light, metals, and plant-based antimicrobials. This review highlights the differences in the resistance or susceptibility of different strains of coronaviruses, or similar viruses, to these antimicrobial agents.
In the last decade, the proactive diagnosis of diseases with artificial intelligence and its aligned technologies has been an exciting and fruitful area. One of the areas in medical care where ...constant monitoring is required is cardiovascular diseases. Arrhythmia, one of the cardiovascular diseases, is generally diagnosed by doctors using Electrocardiography (ECG), which records the heart's rhythm and electrical activity. The use of neural networks has been extensively adopted to identify abnormalities in the last few years. It is found that the probability of detecting arrhythmia increases if the denoised signal is used rather than the raw input signal. This paper compares six filters implemented on ECG signals to improve classification accuracy. Custom convolutional neural networks (CCNNs) are designed to filter ECG data. Extensive experiments are drawn by considering the six ECG filters and the proposed custom CCNN models. Comparative analysis reveals that the proposed models outperform the competitive models in various performance metrics.
Bacillus cereus is frequently implicated in foodborne outbreaks associated with the consumption of cooked rice. The main contributing factors leading to outbreaks is rice cooked in large quantities ...and subsequently, inadequately chilled or stored at room temperatures for a prolonged period of time prior to consumption. Bacillus cereus growth in cooked rice inoculated with approximately 2 log CFU/g of heat-shocked (80 °C/10 min) spores at several isothermal conditions (between 10 and 49 °C) was quantified. B. cereus populations were determined by plating on mannitol egg yolk polymyxin agar and incubating at 30 °C for 24 h. Primary growth models, namely Baranyi, Huang, modified Gompertz, and logistic models were fitted to growth data. Specific growth rates from all four primary models were used to fit the modified Ratkowsky square-root model with respect to temperature. All four primary models were well fitted by the modified Ratkowsky model (R2 values from 0.90–0.99). Based on the goodness of fit secondary model statistics (R2, SSE, RMSE), the Baranyi model performed the best and was chosen for tertiary modeling. Acceptable prediction zone (APZ) analysis was performed for validation of the Baranyi model predictions during single rate exponential and biphasic linear cooling temperature profiles. For single rate cooling, 23 of the 24 predictions fell within the APZ (−1.0 to 0.5 log CFU/g). For biphasic linear cooling, 26 of the 28 predictions fell within the APZ. The developed dynamic model can be used to predict potential B. cereus growth from spores in cooked rice during chilling and thus, support the disposition of product subject to cooling deviations.
•We investigated the growth kinetics of Bacillus cereus in cooked rice.•Four different growth models were used to estimate the growth in cooked rice.•A dynamic model to estimate growth was developed.•The model will assist the food industry to evaluate risk of B. cereus growth in cooked rice.
PDF
