Estimation of growth of Clostridium perfringens in cooked beef under fluctuating temperature conditions

Enhancing sulfide mitigation via the sustainable supply of oxygen from air-nanobubbles in gravity sewers

Traditional air or oxygen injection is an effective and economical mitigation strategy for sulfide control in pressure sewers, but it is not suitable for gravity sewers due to the low solubility of oxygen in water under normal atmospheric conditions. Herein, an air-nanobubble (ANB) injection method was proposed for sulfide mitigation in gravity sewers, and its sulfide control efficiency was evaluated by long-term laboratory gravity sewer reactors. The results showed that an average inhibition rate of 45.36% for sulfide was obtained when ANBs were implemented, which was 3.75 times higher than that of the traditional air injection method, revealing the effectiveness and feasibility of the ANB injection method. As suggested by microbial community analysis of sewer biofilms, the relative abundance of sulfate-reducing bacteria (SRB) decreased 40.57% while that of sulfur oxidizing bacteria (SOB) increased 215.27% in the presence of ANBs, indicating that sulfide mitigation by ANB injection included both the inhibition of sulfide production and the oxidation of dissolved sulfide. The specific cost consumption of ANB injection was 1.7 $/kg-S, which was only 6.85% of that of traditional air injection (24.8 $/kg-S), suggesting that the sustainable supply of oxygen based on ANB injection is not only environmentally but also economically beneficial for sulfide mitigation. The findings of this study may provide an efficient sulfide mitigation strategy for the management of corrosion and malodour issues in the poorly ventilated gravity sewers.

Application of deep neural techniques in predictive modelling for the estimation of Escherichia coli growth rate

AIMS

To develop a predictive model for Escherichia coli using deep neural networks.

METHODS AND RESULTS

Batch experiments are conducted at different temperatures closer to optimum value (36·5°C, 37°C, 37·5°C, 38°C and 38·5°C) to obtain the growth curves of E .coli K-12. Two primary models namely modified Gompertz and new logistic are chosen. Three secondary models namely Gaussian, nonlinear autoregressive eXogenous (NARX) model and long short-term memory (LSTM) are developed. The novelty in this paper is the development of secondary models using artificial neural network (ANN) and deep network. The performance measures chosen to compare the developed primary and secondary models are correlation coefficient (R² ), root-mean-square error (RMSE) and accuracy factor (A_f ). Results show that modified Gompertz model has better R² (0·99) and RMSE (0·019) when compared to new logistic model. Also, the deep network model outperforms other secondary models. Based on the primary and novel secondary model, a predictive model (tertiary model) is developed with improved accuracy and is validated.

CONCLUSIONS

The proposed predictive model exhibit good validation results in terms of RMSE and R² values and can be applied for determining the growth rate of E. coli at a particular temperature value.

SIGNIFICANCE AND IMPACT OF THE STUDY

The proposed model can be used in food processing industries during enzyme production such as Chymosin, to predict the growth rate of E. coli as a function of temperature. Also, the developed LSTM and NARX models can be used to predict maximum specific growth rate of other microbial strains with proper training.

Rapid and strong biocidal effect of ferrate on sulfidogenic and methanogenic sewer biofilms

For the control of sulfide and methane in sewers, it is favorable to reduce their production rather than to remove them after generation. In this study, we revealed rapid and strong biocidal effect of ferrate (Fe(VI)) on sulfidogenic and methanogenic sewer biofilms, leading to control of sulfide and methane production in sewer. The inactivation of the microorganisms in sewer biofilms by Fe(VI) could be accomplished within 15 min for a single dosing event and the biocidal effect could be enhanced by applying pulse dosing strategy. The microbiological analysis showed that the key functional genes involved in sulfide and methane production, i.e. dsrA and mcrA, in the viable cells after Fe(VI) dosing were decreased substantially by 84.2% and 86.6%, respectively. Significant drops were also observed in the relative abundances of viable sulfide reducing bacteria (SRB) and methanogenic archaea (MA). The direct dosing of Fe(VI) into a sewer reactor led to instant and complete suppression of sulfidogenic and methanogenic activities, and the recovery of the activities resembled the regrowth of residual SRB and MA. The results of this study suggested the feasibility for developing an efficient and cost-effective sulfide and methane control strategy using Fe(VI).

Growth and Modeling of Staphylococcus aureus in Flour Products under Isothermal and Nonisothermal Conditions

This study was conducted to investigate the growth of Staphylococcus aureus in traditional Chinese flour products under isothermal (10, 15, 20, 25, 30, and 37°C) and nonisothermal (10 to 20, 20 to 30, and 25 to 37°C) conditions. Then, models for the growth of S. aureus in flour products as a function of storage temperature, pH, and water activity (a_w) were developed, and the goodness of fit of models was evaluated using the determination coefficient (R²), root mean square error (RMSE), bias factor (B_f), and accuracy factor (A_f). Based on the above information, S. aureus growth in steamed bread under nonisothermal conditions was predicted from experiments performed under isothermal conditions. It was shown that different combinations of temperature and a_w in flour products have a strong influence on the growth of S. aureus . The modified Gompertz model was found to be more suitable for describing the growth data of S. aureus in flour products, with an R² of >0.99 and an RMSE of <0.37. The newly developed secondary models were validated, and for the specific growth rate and the lag time, the R² values were 0.96 and 0.97, A_f was 1.12 and 1.06, and B_f was 1.13 and 1.05, respectively. The predicted nonisothermal growth curves of S. aureus were in agreement with the reported experimental ones, with RMSE <0.29, A_f value 1.02 to 1.09, and B_f value 0.92 to 0.99. These results indicated that the predictive models provided useful information for the establishment of safety standards and a risk assessment for S. aureus in flour products.

Differential outgrowth potential of Clostridium perfringens food-borne isolates with various cpe-genotypes in vacuum-packed ground beef during storage at 12°C

In the current study, the outgrowth of spores of 15 different food isolates of Clostridium perfringens was evaluated in vacuum-packed ground beef during storage at 12°C and 25°C. This included enterotoxic strains carrying the gene encoding the CPE enterotoxin on the chromosome (C-cpe), on a plasmid (P-cpe) and cpe-negative strains. The 15 strains were selected from a larger group of strains that were first evaluated for their ability to sporulate in modified Duncan-Strong sporulating medium. Sporulation ability varied greatly between strains but was not associated with a particular cpe genotype. In line with previous studies, the tested C-cpe strains produced spores with significantly higher heat resistance than the cpe-negative and P-cpe strains (both IS1151 and IS1470-like) with the exception of strain VWA009. Following inoculation of vacuum-packed cooked ground beef with spores, the heat-resistant C-cpe strains showed lower outgrowth potential in this model food stored at 12°C than the P-cpe and cpe-negative strains, while no significant differences were observed at 25°C. These results suggest that the latter strains may have a competitive advantage over C-cpe strains at reduced temperatures during storage of foods that support the growth of C. perfringens. While spores of P-cpe strains are readily inactivated by heat processing, post-processing contamination by food handlers who may carry P-cpe strains that have a better growth potential at lower temperatures must be avoided. The varying responses of C. perfringens spores to heat and the differences in outgrowth capacity at different temperatures are factors to be considered in strain selection for challenge tests, and for predictive modelling of C. perfringens.

Cold shock CspA and CspB protein production during periodic temperature cycling in Escherichia coli

Background

Temperature is an important environmental factor which can dramatically affect biochemical processes in bacteria. Temperatures above optimal cause heat shock, while low temperatures induce cold shock. Since the physiological response of the bacterium Escherichia coli to slow temperature fluctuation is not well known, we investigated the effect of periodic temperature cycling between 37° and 8°C with a period of 2 h on proteome profile, cold shock CspA and CspB protein and gene production.

Results

Several proteins (i.e. succinyl-CoA synthetase subunit alpha, periplasmic oligopeptide-binding protein, maltose-binding periplasmic protein, outer membrane porin protein, flavodoxin-1, phosphoserine aminotransferase) were up or down regulated during temperature cycling, in addition to CspA and CspB production. The results indicate that transcription of cspA and cspB increased during each temperature downshift and consistently decreased after each temperature upshift. In sharp contrast CspA-FLAG and CspB-FLAG protein concentrations in the cell increased during the first temperature down-shift and remained unresponsive to further temperature fluctuations. The proteins CspA-FLAG and CspB-FLAG were not significantly degraded during the temperature cycling.

Conclusion

The study demonstrated that slow periodic temperature cycling affected protein production compared to cells constantly incubated at 37°C or during classical cold shock. Bacterial cspA and cspB mRNA transcript levels fluctuated in synchrony with the temperature fluctuations. There was no corresponding pattern of CspA and CspB protein production during temperature cycling.

Effects of nitrite concentration and exposure time on sulfide and methane production in sewer systems

Nitrite dosing is a promising technology to prevent sulfide and methane formation in sewers, due to the known inhibitory/toxic effect of nitrite on sulfate-reducing bacteria (SRB) and methanogenic Archaea (MA). The dependency of nitrite-induced inhibition on sulfide and methane producing activities of anaerobic sewer biofilms on nitrite levels and exposure time is investigated using a range of nitrite concentrations (40, 80, 120 mg-N/L) and exposure time up to 24 days. The recovery of these activities after the 24-day nitrite dosage was also monitored for more than two months. The inhibition level was found to be dependent on both nitrite concentration and exposure time, with stronger inhibition observed at higher nitrite concentrations and/or longer exposure time. However, the time required for achieving 50% recovery of both sulfate-reducing and methanogenic activities after the cessation of nitrite dosage only marginally depended on nitrite concentration. Model-based analysis of the recovery data showed that the recovery was likely due to the regrowth of SRB and methanogens. The lab studies and mathematical analysis supported the development of an intermittent dosing strategy, which was tested in a 1-km long rising main sewer. The field trial confirmed that intermittent dosing of nitrite can effectively reduce/prevent the formation of both sulfide and methane.

Growth parameters of Escherichia coli O157:H7, Salmonella spp., Listeria monocytogenes, and aerobic mesophilic bacteria of apple cider amended with nisin-EDTA

The effect of nisin (0 or 300 IU/mL), ethylenediamine tetraacetic acid (EDTA, 20 mM), and nisin (300 IU)-EDTA (20 mM) on growth parameters, including lag period (LP) and generation time, of Escherichia coli O157:H7, Listeria monocytogenes, and Salmonella spp. in the presence or absence of aerobic mesophilic bacteria of apple cider during storage at 5 degrees C for up to 16 days or 23 degrees C for 16 h was investigated. The growth data were analyzed and fitted to the modified Gompertz model. The LP values for aerobic mesophilic bacteria of apple cider (control) and those amended with EDTA and nisin during storage at 5 degrees C were 1.61, 1.76, and 5.45 days, respectively. In apple cider stored at 23 degrees C for 16 h, the LP values for the same bacteria and treatment were 3.24, 3.56, and 5.85 h, respectively. The LP values for E. coli O157:H7 determined in the presence of aerobic mesophilic bacteria of apple cider stored at 23 degrees C for 16 h was 1.48 h, while populations for L. monocytogenes and Salmonella in the same cider declined. In sterile apple cider left at 23 degrees C for 16 h, the LP values for E. coli O157:H7, Salmonella, and L. monocytogenes averaged 2.74, 2.37, and 3.16 h, respectively. The generation time for these pathogens were 0.402, 0.260, and 0.187 log (CFU/mL)/h, respectively. Addition of nisin and EDTA combination caused a decline in lag phase duration and the populations for all pathogens tested, suggesting possible addition of this additive to freshly prepared apple cider to enhance its microbial safety and prevent costly recalls.

Model on the microbial quality change of seasoned soybean sprouts for on-line shelf life prediction

The growth of aerobic bacteria on Korean seasoned soybean sprouts was modelled as a function of temperature to estimate microbial spoilage and shelf life on a real-time basis under dynamic storage conditions. Counts of aerobic bacteria on seasoned soybean sprouts stored at constant temperatures between 0 degrees C and 15 degrees C were recorded. The bootstrapping method was applied to generate many resampled data sets of mean microbial plate counts that were then used to estimate the parameters of the microbial growth model of Baranyi and Roberts. The distributions of the model parameters were quantified, and their temperature dependencies were expressed as mathematical functions. When the temperature functions of the parameters were incorporated into differential equations describing microbial growth, predictions of microbial growth under fluctuating temperature conditions were similar to observed microbial growth.

Predictive model for Clostridium perfringens growth in roast beef during cooling and inhibition of spore germination and outgrowth by organic acid salts

Spores of foodborne pathogens can survive traditional thermal processing schedules used in the manufacturing of processed meat products. Heat-activated spores can germinate and grow to hazardous levels when these products are improperly chilled. Germination and outgrowth of Clostridium perfringens spores in roast beef during chilling was studied following simulated cooling schedules normally used in the processed-meat industry. Inhibitory effects of organic acid salts on germination and outgrowth of C. perfringens spores during chilling and the survival of vegetative cells and spores under abusive refrigerated storage was also evaluated. Beef top rounds were formulated to contain a marinade (finished product concentrations: 1% salt, 0.2% potassium tetrapyrophosphate, and 0.2% starch) and then ground and mixed with antimicrobials (sodium lactate and sodium lactate plus 2.5% sodium diacetate and buffered sodium citrate and buffered sodium citrate plus 1.3% sodium diacetate). The ground product was inoculated with a three-strain cocktail of C. perfringens spores (NCTC 8238, NCTC 8239, and ATCC 10388), mixed, vacuum packaged, heat shocked for 20 min at 75 degrees C, and chilled exponentially from 54.5 to 7.2 degrees C in 9, 12, 15, 18, or 21 h. C. perfringens populations (total and spore) were enumerated after heat shock, during chilling, and during storage for up to 60 days at 10 degrees C using tryptose-sulfite-cycloserine agar. C. perfringens spores were able to germinate and grow in roast beef (control, without any antimicrobials) from an initial population of ca. 3.1 log CFU/g by 2.00, 3.44, 4.04, 4.86, and 5.72 log CFU/g after 9, 12, 15, 18, and 21 h of exponential chilling. A predictive model was developed to describe sigmoidal C. perfringens growth curves during cooling of roast beef from 54.5 to 7.2 degrees C within 9, 12, 15, 18, and 21 h. Addition of antimicrobials prevented germination and outgrowth of C. perfringens regardless of the chill times. C. perfringens spores could be recovered from samples containing organic acid salts that were stored up to 60 days at 10 degrees C. Extension of chilling time to > or =9 h resulted in >1 log CFU/g growth of C. perfringens under anaerobic conditions in roast beef. Organic acid salts inhibited outgrowth of C. perfringens spores during chilling of roast beef when extended chill rates were followed. Although C. perfringens spore germination is inhibited by the antimicrobials, this inhibition may represent a hazard when such products are incorporated into new products, such as soups and chili, that do not contain these antimicrobials, thus allowing spore germination and outgrowth under conditions of temperature abuse.

Development of an integrated model for heat transfer and dynamic growth of Clostridium perfringens during the cooling of cooked boneless ham

Numerous small meat processors in the United States have difficulties complying with the stabilization performance standards for preventing growth of Clostridium perfringens by 1 log10 cycle during cooling of ready-to-eat (RTE) products. These standards were established by the Food Safety and Inspection Service (FSIS) of the US Department of Agriculture in 1999. In recent years, several attempts have been made to develop predictive models for growth of C. perfringens within the range of cooling temperatures included in the FSIS standards. Those studies mainly focused on microbiological aspects, using hypothesized cooling rates. Conversely, studies dealing with heat transfer models to predict cooling rates in meat products do not address microbial growth. Integration of heat transfer relationships with C. perfringens growth relationships during cooling of meat products has been very limited. Therefore, a computer simulation scheme was developed to analyze heat transfer phenomena and temperature-dependent C. perfringens growth during cooling of cooked boneless cured ham. The temperature history of ham was predicted using a finite element heat diffusion model. Validation of heat transfer predictions used experimental data collected in commercial meat-processing facilities. For C. perfringens growth, a dynamic model was developed using Baranyi's nonautonomous differential equation. The bacterium's growth model was integrated into the computer program using predicted temperature histories as input values. For cooling cooked hams from 66.6 degrees C to 4.4 degrees C using forced air, the maximum deviation between predicted and experimental core temperature data was 2.54 degrees C. Predicted C. perfringens growth curves obtained from dynamic modeling showed good agreement with validated results for three different cooling scenarios. Mean absolute values of relative errors were below 6%, and deviations between predicted and experimental cell counts were within 0.37 log10 CFU/g. For a cooling process which was in exact compliance with the FSIS stabilization performance standards, a mean net growth of 1.37 log10 CFU/g was predicted. This study introduced the combination of engineering modeling and microbiological modeling as a useful quantitative tool for general food safety applications, such as risk assessment and hazard analysis and critical control points (HACCP) plans.