Modeling inactivation kinetics for Enterococcus faecium on the surface of peanuts during convective dry roasting.

Dry roasting can reduce Salmonella contamination on peanuts. While previous studies evaluated impact of product temperature, process humidity, product moisture, and/or product water activity on Salmonella lethality, no published study has tested multiple primary and secondary models on data collected in a real-world processing environment. We tested multiple primary and secondary models to quantify Salmonella surrogate, Enterococcus faecium, inactivation on peanuts. Shelled runner-type peanuts inoculated with E. faecium were treated at various air temperatures (121, 149, and 177 °C) and air velocities (1.0 and 1.3 m/s) for treatment times from 1 to 63 min. Peanut surface temperature was measured during treatment. Water activity and moisture content were measured, and E. faecium were enumerated after treatment. Microbial inactivation was modeled as a function of time, product temperature, and product moisture. Parameters (Dref, zT, zaw, zMC, and/or n) were compared between model fits. The log-linear primary model combined with either the modified Bigelow-type secondary model accounting for aw or moisture content showed improved fit over the log-linear primary model combined with the traditional Bigelow-type secondary model. The Weibull primary model combined with the traditional Bigelow-type secondary model had the best fit. All parameter relative errors were less than 15%, and RMSE values ranged from 0.379 to 0.674 log CFU/g. Incorporating either aw or moisture content in the inactivation models did not make a practical difference within the range of conditions and model forms evaluated, and air velocity did not have a significant impact on inactivation. The models developed can aid processors in developing and validating pathogen reduction during peanut roasting.

Modeling the Effects of Product Temperature, Product Moisture, and Process Humidity on Thermal Inactivation of Salmonella in Pistachios during Hot-Air Heating.

ABSTRACT: Prior efforts to model bacterial thermal inactivation in and on low-moisture foods generally have been based on isothermal and iso-moisture experiments and have rarely included dynamic product and process variables. Therefore, the objective of this study was to test appropriate secondary models to quantify the effect of product temperature, product moisture, and process humidity on thermal inactivation of Salmonella Enteritidis PT30 on pistachios subjected to dynamic dry- or moist-air heating. In-shell pistachios were inoculated with Salmonella Enteritidis PT30, equilibrated in controlled-humidity chambers (to target water activities [aw] of 0.45 or 0.65), and in some cases, subjected to a presoak treatment prior to heating in a laboratory-scale, moist-air convection oven at multiple combinations (in duplicate) of dry bulb (104.4 or 118.3°C) and dew point (∼23.8, 54.4, or 69.4°C) temperatures, with air speed of ∼1.3 m/s. Salmonella survivors, pistachio moisture content, and aw were quantified at six time points for each condition, targeting cumulative lethality of ∼3 to 5 log. The resulting data were used to estimate parameters for five candidate secondary models that included combinations of product temperature, product moisture, aw, and/or process dew point (coupled with a log-linear primary model). A model describing the D-value as a function of temperature and dew point fit the data well (root mean squared error [RMSE] = 0.86 log CFU/g); however, adding a term to account for dynamic product moisture improved the fit (RMSE = 0.83 log CFU/g). In addition, product moisture content yielded better model outcomes, as compared with aw, particularly in the case of the presoaked pistachios. When validated at the pilot scale, the model was conservative, always underpredicting the experimental log reductions. Both dynamic product moisture and process humidity were critical factors in modeling thermal inactivation of Salmonella in a low-moisture product heated in an air-convection system.

Modeling the Risk of Salmonellosis from Consumption of Peanuts in the United States.

Peanut products were the target of the largest food recall in United States history from 2008 to 2009, with more than 3,200 products implicated, economic losses estimated at $1 billion, and more than 700 reported illnesses and 9 deaths. Predictive modeling tools such as quantitative microbial risk assessment can be used to aid processors in making risk management decisions that may reduce the chances of foodborne illness, but published risk assessment for peanuts is not currently available. A quantitative microbial risk assessment was performed to quantify salmonellosis risk from consumption of peanuts in the United States. Prevalence and concentration data for Salmonella on raw, shelled peanuts were used in combination with probability distributions of simulated log reductions achieved during production steps before consumption. Data for time-temperature combinations used in each step were obtained from published literature, industry surveys, or expert opinion, and survival data were obtained from the literature. A beta-Poisson dose-response model was used to predict probability of illness from ingestion of Salmonella cells. The model predicted 14.2 (arithmetic mean) or 0.0123 (geometric mean) illnesses per year. Sensitivity analysis showed that thermal inactivation log reductions applied had the biggest impact on predicted salmonellosis risk, followed by consumer storage time, Salmonella starting concentration, Salmonella starting prevalence, and number of originally contaminated 25-g servings per originally positive 375-g sample. Scenario analysis showed that increasing log reduction variability increased mean salmonellosis risk. Removing the effect of storage on Salmonella survival increased the arithmetic and geometric means to 153 and 0.598 illnesses per year, respectively. This study indicated that the risk of salmonellosis from consumption of peanuts can be lowered by reducing field contamination, control of storage steps, and monitoring of appropriate critical limits in peanut roasting.

Impact of Process Temperature, Humidity, and Initial Product Moisture on Thermal Inactivation of Salmonella Enteritidis PT 30 on Pistachios during Hot-Air Heating.

Some thermal processes, such as pistachio roasting, are not yet well characterized with respect to the impact of product and process variables on Salmonella lethality. This study aimed to quantify the effects of process temperature, humidity, and initial product water activity (aw), on Salmonella lethality for in-shell pistachios. In-shell pistachios were inoculated with Salmonella Enteritidis PT 30 (∼8.5 log CFU/g), equilibrated (0.45 or 0.65 aw), and heated without soaking ("dry") or after a pure-water or 27% NaCl brining pretreatment ("presoaked"). Inoculated pistachio samples (15 g) were heated in a laboratory-scale, moist-air convection oven at 104.4 or 118.3°C, humidities of ∼3, 15, or 30%, v/v (∼24.4, 54.4, or 69.4°C dew point), and air speed of 1.3 m/s. Salmonella survivors were quantified at six times during each treatment, targeting total reductions of ∼3 to 5 log. Survivor data were analyzed using analysis of variance to identify main effects (time, temperature, humidity, and initial aw) and two-term interactions with time. As expected, lethality increased ( P < 0.05) with temperature and humidity. For example, the time to achieve a 4-log reduction decreased 50 to 80% when humidity increased from ∼3 to 30%. When the dry and presoaked treatments were analyzed separately, initial product aw (0.45 versus 0.65 aw or 0.75 versus 0.95 aw) did not affect lethality ( P > 0.05). However, when comparing dry against presoaked treatments, the time to achieve a 4-log reduction decreased 55 to 85% ( P < 0.05) for presoaked pistachios subjected to the same temperature-humidity treatment. Salt had no effect ( P > 0.05) on lethality outcomes. These results, relative to initial aw, process humidity, brining, and salt effects on process lethality, are critically important and must be considered in the design and validation of thermal processes for Salmonella reduction in pistachio processing.

Effect of high-pressure processing of bovine colostrum on immunoglobulin G concentration, pathogens, viscosity, and transfer of passive immunity to calves.

This study aimed to determine the effects of high-pressure processing on the immunoglobulin concentration, microbial load, viscosity, and transfer of passive immunity to calves when applied to bovine colostrum as an alternative to thermal pasteurization. A pilot study using Staphylococcus aureus was conducted to determine which pressure-time treatments are most appropriate for use with bovine colostrum, with the goals of maximizing bacterial inactivation while minimizing IgG content and viscosity changes. Following the pilot study, an inoculation study was conducted in which first-milking colostrum samples from Holstein-Friesian cows were inoculated with known concentrations of various bacteria or viruses and pressure processed at either 300 MPa for up to 60min or at 400MPa for up to 30min. The recovery of total native aerobic bacteria, Escherichia coli, Salmonella enterica ssp. enterica serovar Dublin, Mycobacterium avium ssp. paratuberculosis, bovine herpesvirus type 1, and feline calicivirus were determined after processing. Colostrum IgG content was measured before and after pressure processing. Shear stress and viscosity for each treatment was determined over shear rates encompassing those found during calf feeding and at normal bovine body temperature (37.8°C). Following a calf trial, serum IgG concentration was measured in 14 calves fed 4 L of colostrum pressure processed at 400MPa for 15min. In the pilot study, S. aureus was effectively reduced with pressure treatment at 300 and 400MPa (0, 5, 10, 15, 30, and 45min), with 2 treatments at 400MPa (30, 45min) determined to be inappropriate for use with bovine colostrum due to viscosity and IgG changes. High-pressure processing at 300MPa (30, 45, and 60min) and 400MPa (10, 15, and 20min) was shown to effectively reduce total native aerobic bacteria, E. coli, Salmonella Dublin, bovine herpesvirus type 1, and feline calicivirus populations in bovine colostrum, but no decrease occurred in Mycobacterium avium ssp. paratuberculosis. All inoculation study pressure treatments insignificantly decreased IgG content of colostrum. Treatment of colostrum at 400MPa for 15min during the calf trial decreased IgG content of colostrum. Treatment at 400MPa for 15min increased colostrum viscosity, with 2 of 14 samples requiring dilution with water for calf feeding. Calves fed pressure-processed colostrum had similar serum IgG but lower efficiency of absorption than calves fed heat-treated colostrum. The results of this study suggest that high-pressure processing of bovine colostrum maintains an acceptable IgG level while decreasing bacterial and viral counts. Changes in viscosity sometimes made calf feeding more difficult, but still feasible. Additional research to optimize this technology for on-farm use is necessary.

Modeling the Effect of Temperature and Water Activity on the Thermal Resistance of Salmonella Enteritidis PT 30 in Wheat Flour.

Salmonella continues to be a problem associated with low-moisture foods, particularly given enhanced thermal resistance at lower water activity (aw). However, there is a scarcity of thermal inactivation models accounting for the effect of aw. The objective of this study was to test multiple secondary models for the effect of product (wheat flour) aw on Salmonella enterica Enteritidis phage type 30 thermal resistance. A full-factorial experimental design included three temperatures (75, 80, and 85°C) and four aw values (~0.30, 0.45, 0.60, and 0.70). Prior to isothermal treatment, sample aw was achieved by equilibrating samples in a humidity-controlled conditioning chamber. Two primary models (log linear and Weibull type) and three secondary models (second-order response surface, modified Bigelow type, and combined effects) were evaluated using the corrected Akaike information criterion and root mean squared errors. Statistical analyses of the primary models favored the log-linear model. Incorporating the three secondary models into the log-linear primary model yielded root mean squared errors of 2.1, 0.78, and 0.96 log CFU/g and corrected Akaike information criterion values of 460, -145, and -19 for the response surface, modified Bigelow, and combined-effects models, respectively. The modified Bigelow-type model, which exponentially scaled both temperature and aw effects on thermal inactivation rates, predicted Salmonella lethality significantly better (P < 0.05) than did the other secondary models examined. Overall, aw is a critical factor affecting thermal inactivation of Salmonella in low-moisture products and should be appropriately included in thermal inactivation models for these types of systems.