Effect of a previous heat shock on the thermal resistance of Listeria monocytogenes and Pseudomonas aeruginosa at different pHs

In this work we study the effect of heat shocks of various durations up to 60 min, at different temperatures between 35 and 45 degrees C, in media of pH 4.0, 5.5 and 7.4 on the heat resistance of Listeria monocytogenes and Pseudomonas aeruginosa. The pattern of survival curves after heat treatment did not change with the application of a previous heat shock. However, the kinetics of inactivation was different for the two microorganisms studied. Whereas the inactivation of L. monocytogenes was similar to an exponential function of heating time and therefore straight survival curves were obtained, survival curves corresponding to P. aeruginosa showed convex profiles. All survival curves obtained in this investigation were fitted to Weibull-based Mafart equation: log(10)S(t)=-(t / delta)(p). The magnitude of the heat shock induced thermotolerance increased with treatment medium pH. At pH 7.4 the increase in heat tolerance depended on the duration and temperature of the heat shock. On the contrary, at pH 5.5 and pH 4.0, the heat-shock temperature did not exert any effect. The observed maximum delta values increased 2.3, 4.0 and 9.3 fold for L. monocytogenes, and 1.3, 2.1 and 8.4 fold for P. aeruginosa, at pH 4.0, 5.5 and 7.4, respectively. This research has proven that Mafart equation allows studying and quantifying the effect of heat shocks on bacterial heat resistance.     

Modelling inactivation of Listeria monocytogenes by pulsed electric fields in media of different pH

A study of the effect of square-wave pulsed electric fields (PEF) on the inactivation of Listeria monocytogenes in McIlvaine buffer of different pH (3.5-7.0) was conducted. L. monocytoges was more PEF sensitive at higher electric field strengths (E) and in media of low pH. A treatment at 28 kV/cm for 400 mus that inactivated 1.5, 2.3 and 3.0 Log10 cycles at pH 7.0, 6.5 and 5.0 respectively destroyed almost 6.0 Log10 cycles at pH 3.5. The general shape of survival curves of L. monocytogenes PEF treated at different pH was convex/concave upwards. A mathematical model based on the Weibull distribution accurately described these survival curves. At each pH, the shape parameter (n value) did not depend on E. The relationship between n value of the Weibull model and the pH of the treatment medium was described by the Gompertz equation. A multiple linear regression model using three predictor variables (E, E2, pH2) related the Log10 of the scale paramenter (b value) of the Weibull model with E and pH of the treatment medium. A tertiary model developed using McIlvaine buffer as treatment medium predicted satisfactorily the inactivation of L. monocytogenes in apple juice.     

Temperature-assisted pressure inactivation of Listeria monocytogenes in turkey breast meat

Ready-to-eat turkey breast meat samples were surface-inoculated with a five-strain cocktail of Listeria monocytogenes cultures to a final concentration of approximately 10(7) CFU/g. The inoculated meat samples were vacuum-packaged and pressure treated at 300 MPa for 2 min, 400 MPa for 1 min, and 500 MPa for 1 min at initial sample temperatures of 1, 10, 20, 30, 40, 50, and 55 degrees C. L. monocytogenes was most resistant to pressure at temperatures between 10 and 30 degrees C. As temperature decreased below 10 degrees C or increased over 30 degrees C, its pressure sensitivity increased. This enhanced inactivation effect was more pronounced when meat samples were treated at higher temperature than at lower temperature. For example, a 1-min treatment of 500 MPa at 40 degrees C reduced the counts by 3.8 log(10), while at 1 and 20 degrees C the same treatment reduced counts by 1.4 and 0.9 log(10), respectively (P<0.05). The survival curves of L. monocytogenes were obtained at 300 MPa and 55 degrees C, 400 MPa and 50 degrees C, and 500 MPa and 40 degrees C. With increasing treatment time, the three survival curves showed a rapid initial drop in bacteria counts with a diminishing inactivation rate or tailing effect. The survival data were fitted with a linear and a nonlinear, Weibull, models. The Weibull model consistently produced better fit to the survival data than the linear model.     

Modeling the survival of Salmonella spp. in chorizos

The survival of Salmonella spp. in chorizos has been studied under the effect of storage conditions; namely temperature (T=6, 25, 30 degrees C), air inflow velocity (F=0, 28.4 m/min), and initial water activity (a(w0)=0.85, 0.90, 0.93, 0.95, 0.97). The pH was held at 5.0. A total of 20 survival curves were experimentally obtained at various combinations of operating conditions. The chorizos were stored under four conditions: in the refrigerator (Ref: T=6 degrees C, F=0 m/min), at room temperature (RT: T=25 degrees C, F=0 m/min), in the hood (Hd: T=25 degrees C, F=28.4 m/min), and in the incubator (Inc: T=30 degrees C, F=0 m/min). Semi-logarithmic plots of counts vs. time revealed nonlinear trends for all the survival curves, indicating that the first-order kinetics model (exponential distribution function) was not suitable. The Weibull cumulative distribution function, for which the exponential function is only a special case, was selected and used to model the survival curves. The Weibull model was fitted to the 20 curves and the model parameters (alpha and beta) were determined. The fitted survival curves agreed with the experimental data with R(2)=0.951, 0.969, 0.908, and 0.871 for the Ref, RT, Hd, and Inc curves, respectively. Regression models relating alpha and beta to T, F, and a(w0) resulted in R(2) values of 0.975 for alpha and 0.988 for beta. The alpha and beta models can be used to generate a survival curve for Salmonella in chorizos for a given set of operating conditions. Additionally, alpha and beta can be used to determine the times needed to reduce the count by 1 or 2 logs t(1D) and t(2D). It is concluded that the Weibull cumulative distribution function offers a powerful model for describing microbial survival data. A comparison with the pathogen modeling program (PMP) revealed that the survival kinetics of Salmonella spp. in chorizos could not be adequately predicted using PMP which underestimated the t(1D) and t(2D). The mean of the Weibull probability density function correlated strongly with t(1D) and t(2D), and can serve as an alternative to the D-values normally used with first-order kinetic models. Parametric studies were conducted and sensitivity of survival to operating conditions was evaluated and discussed in the paper. The models derived herein provide a means for the development of a reliable risk assessment system for controlling Salmonella spp. in chorizos.     

MATHEMATICAL MODEL FOR THE SURVIVAL OF LISTERIA MONOCYTOGENES IN MEXICAN-STYLE SAUSAGE

Survival of Listeria monocytogenes in chorizos (Mexican‐style sausages) was modeled in relation to initial water activity (a_w0) and storage conditions using the Weibull cumulative distribution function. Twenty survival curves were generated from chorizos formulated at a_w0 = 0.85–0.97 then stored under four temperature (T) and air inflow velocity (F) conditions. The Weibull model parameters (α and β) were determined for every curve. Predicted survival curves agreed with experimental curves with R² = 0.945–0.992. Regression models (R² = 0.981–0.984) were developed to relate α and β to operating conditions. The times to one‐ and two‐log reduction in count (t_1D and t_2D) were derived from the Weibull model in terms of α and β. A parametric study revealed that L. monocytogenes survival was most sensitive to a_w0 between 0.90 and 0.95. The inactivation of L. monocytogenes could be maximized with higher T and lower a_w0; however, F did not significantly influence survival.     

Survival curves of Listeria monocytogenes in chorizos modeled with artificial neural networks

Using artificial neural networks (ANNs), a highly accurate model was developed to simulate survival curves of Listeria monocytogenes in chorizos as affected by the initial water activity (a(w0)) of the sausage formulation, temperature (T), and air inflow velocity (F) where the sausages are stored. The ANN-based survival model (R(2)=0.970) outperformed the regression-based cubic model (R(2)=0.851), and as such was used to derive other models (using regression) that allow prediction of the times needed to drop count by 1, 2, 3, and 4 logs (i.e., nD-values, n=1, 2, 3, 4). The nD-value regression models almost perfectly predicted the various times derived from a number of simulated survival curves exhibiting a wide variety of the operating conditions (R(2)=0.990-0.995). The nD-values were found to decrease with decreasing a(w0), and increasing T and F. The influence of a(w0) on nD-values seems to become more significant at some critical value of a(w0), below which the variation is negligible (0.93 for 1D-value, 0.90 for 2D-value, and <0.85 for 3D- and 4D-values). There is greater influence of storage T and F on 3D- and 4D-values than on 1D- and 2D-values.     

Survival curves of heated bacterial spores: effect of environmental factors on Weibull parameters

The classical D-value of first order inactivation kinetic is not suitable for quantifying bacterial heat resistance for non-log linear survival curves. One simple model derived from the Weibull cumulative function describes non-log linear kinetics of micro-organisms. The influences of environmental factors on Weibull model parameters, shape parameter "p" and scale parameter "delta", were studied. This paper points out structural correlation between these two parameters. The environmental heating and recovery conditions do not present clear and regular influence on the shape the parameter "p" and could not be described by any model tried. Conversely, the scale parameter "delta" depends on heating temperature and heating and recovery medium pH. The models established to quantify these influences on the classical "D" values could be applied to this parameter "delta". The slight influence of the shape parameter p variation on the goodness of fit of these models can be neglected and the simplified Weibull model with a constant p-value for given microbial population can be applied for canning process calculations.     

Predicting heat inactivation of Listeria monocytogenes under nonisothermal treatments

The aim of this study was to find a model that accurately predicts the heat inactivation of Listeria monocytogenes (ATCC 15313) at constantly rising heating rates (0.5 to 9 degrees C/min) in media of different pH values (4.0 to 7.4). Survival curves of L. monocytogenes obtained under isothermal treatments at any temperature were nearly linear. Estimations of survival curves under nonisothermal treatments obtained from heat resistance parameters of isothermal treatments adequately fit experimental values obtained at pH 4.0. On the contrary, survivors were much higher than estimations at pH 5.5 and 7.4. The slower the heating rate and the longer the treatment time, the greater the differences between the experimental and estimated values. An equation based on the Weibullian-like distribution, log S(t) = (t/delta)p, accurately described survival curves of L. monocytogenes obtained under nonisothermal conditions within the range of heating rates investigated. A nonlinear relationship was observed between the scale parameter (delta) and the heating rate, which allowed the development of an equation capable of predicting the inactivation rate of L. monocytogenes under nonisothermal treatments at pH 5.5 and 7.4. The model predictions were a good fit to the measured data independent of the magnitude of the thermotolerance increase. This work might contribute to the increase in safety of those food products that require long heating lag phases during the pasteurization process.     

Adaptive growth responses of Listeria monocytogenes to acid and osmotic shifts above and across the growth boundaries

The effect of acid and osmotic shifts on the growth of Listeria monocytogenes was evaluated at 10°C. Two types of shifts were tested: (i) within the range of pH and water activity (a(w)) levels that allow growth of L. monocytogenes and (ii) after habituation at no-growth conditions back to growth-permitting conditions. A L. monocytogenes cheese isolate, with high survival capacity during cheesemaking, was inoculated (10(2) CFU/ml) in tryptic soy broth supplemented with 0.6% yeast extract at six pH levels (5.1 to 7.2; adjusted with lactic acid) and 0.5% NaCl (a(w) 0.995), or four a(w) levels (0.995 to 0.93, adjusted with 0.5 to 10.5% NaCl) at pH 7.2 and grown to early stationary phase. L. monocytogenes was then shifted (at 10(2) CFU/ml) to each of the aforementioned growth-permitting pH and a(w) levels and incubated at 10°C. Shifts from no-growth to growth-permitting conditions were carried out by transferring L. monocytogenes habituated at pH 4.9 or a(w) 0.90 (12.5% NaCl) for 1, 5, and 10 days to all pH and a(w) levels permitting growth. Reducing a(w) or pH at different levels in the range of 0.995 to 0.93 and 7.2 to 5.1, respectively, decreased the maximum specific growth rate of L. monocytogenes. The lag time of the organism increased with all osmotic downshifts, as well as by the reduction of pH to 5.1. Conversely, any type of shift within pH 5.5 to 7.2 did not markedly affect the lag times of L. monocytogenes. The longer the cells were incubated at no-growth a(w) (0.90), the faster they initiated growth subsequently, suggesting adaptation to osmotic stress. Conversely, extended habituation at pH 4.9 had the opposite effect on subsequent growth of L. monocytogenes, possibly due to cell injury. These results suggest that there is an adaptation or injury rate induced at conditions inhibiting the growth of the pathogen. Thus, quantifying adaptation phenomena under growth-limiting environments, such as in fermented dairy and meat products or products preserved in brine, is essential for reliable growth simulations of L monocytogenes during transportation and storage of foods.     

Quantifying the effects of heating temperature, and combined effects of heating medium pH and recovery medium pH on the heat resistance of Salmonella typhimurium

The influence of heating treatment temperature, pH of heating and recovery medium on the survival kinetics of Salmonella typhimurium ATCC 13311 is studied and quantified. From each non-log linear survival curve, Weibull model parameters were estimated. An average shape parameter value of 1.67 was found, which is characteristic of downward concavity curves and is in agreement with values estimated from other S. typhimurium strains. Bigelow type models quantifying the heating temperature, heating and recovery medium pH influences are fitted on scale parameter delta data (time of first decimal reduction), which reflects the bacterial heat resistance. The estimate of z(T) (4.64 degrees C) is in the range of values given in the literature for this species. The influence of pH of the heating medium on the scale parameter (z(pH): 8.25) is lower than that of the recovery pH medium influence (z(')(pH): 3.65).     

Effect of water activity on thermal resistance of Salmonella krefeld in liquid medium and on rawhide surface

The thermal resistivity of Salmonella krefeld at 60 and 65 degrees C as affected by water activity (0.99-0.60) was investigated in a liquid medium viz. Trypticase Soy Broth (TSB) and on rawhide surface. A reduction of the a(w) of the liquid medium resulted in an increase in the heat resistance of Salmonella krefeld. At a particular water activity the type of solute played a significant role with Salmonella krefeld exhibiting much higher heat sensitivity in the media with glycerol compared to the media with sucrose. The heat resistance of Salmonella krefeld inoculated onto the surface of rawhide was also investigated during hot air drying at 60 and 65 degrees C at two initial levels of a(w), 0.99 and 0.90, prior to drying as determined at 250 degrees C. The rate of water loss or a(w) decrease during drying was not significantly influenced by the initial water activity but was clearly dependent on the drying temperature with all survival curves displaying an upward concavity. Salmonella on rawhide with an initial a(w) of 0.90 exhibited higher heat tolerance than with an initial a(w) of 0.99 during a prolonged heating period with the initial a(w) significantly affecting the heat resistance particularly at higher drying temperatures.     

Use of carvacrol and cymene to control growth and viability of Listeria monocytogenes cells and predictions of survivors using frequency distribution functions

The antibacterial action of carvacrol and cymene on two Listeria monocytogenes strains (STCC4031 and NCTN4032) was studied. Carvacrol or cymene showed inhibitory effect on the growth of L. monocytogenes during lag and exponential growth phases and was more evident with increasing concentrations in brain heart infusion broth at 30 degrees C. Carvacrol or cymene also decreased the survival of mid-exponential-growth-phase L. monocytogenes STCC4031 cells in potassium-N-2-hydroxy-ethylpiperazine-N-ethanesulfo nic acid, at 30 degrees C. The combination of carvacrol and cymene resulted in an increased antibacterial effect on the growth and a synergistic effect on the viability of L. monocytogenes compared with the natural compounds applied separately. The analysis of survival curves by the Weibull frequency distribution function allowed an accurate prediction of the level of inactivation achieved. Interestingly, an important bactericidal effect (4.7-log reduction) of low concentrations of both antimicrobials combined (0.75 mM) was observed on L. monocytogenes in carrot juice. This study indicates the potential use of carvacrol and cymene applied simultaneously for preservation of minimally processed foods.     

On the use of the Weibull model to describe thermal inactivation of microbial vegetative cells

This paper evaluates the applicability of the Weibull model to describe thermal inactivation of microbial vegetative cells as an alternative for the classical Bigelow model of first-order kinetics; spores are excluded in this article because of the complications arising due to the activation of dormant spores. The Weibull model takes biological variation, with respect to thermal inactivation, into account and is basically a statistical model of distribution of inactivation times. The model used has two parameters, the scale parameter alpha (time) and the dimensionless shape parameter beta. The model conveniently accounts for the frequently observed nonlinearity of semilogarithmic survivor curves, and the classical first-order approach is a special case of the Weibull model. The shape parameter accounts for upward concavity of a survival curve (beta < 1), a linear survival curve (beta = 1), and downward concavity (beta > 1). Although the Weibull model is of an empirical nature, a link can be made with physiological effects. Beta < 1 indicates that the remaining cells have the ability to adapt to the applied stress, whereas beta > 1 indicates that the remaining cells become increasingly damaged. Fifty-five case studies taken from the literature were analyzed to study the temperature dependence of the two parameters. The logarithm of the scale parameter alpha depended linearly on temperature, analogous to the classical D value. However, the temperature dependence of the shape parameter beta was not so clear. In only seven cases, the shape parameter seemed to depend on temperature, in a linear way. In all other cases, no statistically significant (linear) relation with temperature could be found. In 39 cases, the shape parameter beta was larger than 1, and in 14 cases, smaller than 1. Only in two cases was the shape parameter beta = 1 over the temperature range studied, indicating that the classical first-order kinetics approach is the exception rather than the rule. The conclusion is that the Weibull model can be used to model nonlinear survival curves, and may be helpful to pinpoint relevant physiological effects caused by heating. Most importantly, process calculations show that large discrepancies can be found between the classical first-order approach and the Weibull model. This case study suggests that the Weibull model performs much better than the classical inactivation model and can be of much value in modelling thermal inactivation more realistically, and therefore, in improving food safety and quality.     

Modeling the inactivation of Salmonella Typhimurium, Listeria monocytogenes, and Salmonella Enteritidis on poultry products exposed to pulsed UV light

Pulsed UV light inactivation of Salmonella Typhimurium on unpackaged and vacuum-packaged chicken breast, Listeria monocytogenes on unpackaged and vacuum-packaged chicken frankfurters, and Salmonella Enteritidis on shell eggs was explained by log-linear and Weibull models using inactivation data from previous studies. This study demonstrated that the survival curves of Salmonella Typhimurium and L. monocytogenes were nonlinear exhibiting concavity. The Weibull model was more successful than the log-linear model in estimating the inactivations for all poultry products evaluated, except for Salmonella Enteritidis on shell eggs, for which the survival curve was sigmoidal rather than concave, and the use of the Weibull model resulted in slightly better fit than the log-linear model. The analyses for the goodness of fit and performance of the Weibull model produced root mean square errors of 0.059 to 0.824, percent root mean square errors of 3.105 to 21.182, determination coefficients of 0.747 to 0.989, slopes of 0.842 to 1.042, bias factor values of 0.505 to 1.309, and accuracy factor values of 1.263 to 6.874. Overall, this study suggests that the survival curves of pathogens on poultry products exposed to pulsed UV light are nonlinear and that the Weibull model may generally be a useful tool to describe the inactivation patterns for pathogenic microorganisms affiliated with poultry products.     

牛肉中沙门氏菌热失活模型的建立

为了建立牛肉中沙门氏菌的热失活动力学模型,将4种不同血清型的沙门氏菌混合菌液接种到牛肉表面,将接种后的牛肉分别在55、57.5、60、62.5和65 ℃下进行加热处理。不同温度下的沙门氏菌热失活曲线用Weibull模型进行了拟合,判定系数(R2)分别为0.993(55 ℃)、0.984(57.5 ℃)、0.999(60 ℃)、0.999(62.5 ℃)和0.998(65 ℃)。进一步建立了温度对Weibull一级失活模型参数(b)影响的二级模型,即ln(b)=0.47T-28.07。用58.5和64 ℃下实际的沙门氏菌存活数对所建的模型进行验证,准确度(A_f)和偏差度(B_f)分别为1.071和1.056,0.998和1.002,均在可接受范围内。本研究所建立的模型能较好的模拟不同温度(55~65 ℃)对牛肉中沙门氏菌热失活的影响。     

脉冲强光对大肠杆菌的灭活效果及其动力学模型的建立

为研究脉冲强光对大肠杆菌的杀菌效应,试验以大肠杆菌ATCC 8739为对象,研究了不同生长期、pH和温度对脉冲强光杀菌效果的影响,并对其杀菌动力学进行Linear和Weibull模型拟合。结果表明:培养了6 h的对数期大肠杆菌对脉冲强光处理最为敏感,处理1 s能够降低(2.31±0.16)lg cfu/mL。pH和温度对脉冲强光杀菌效果有很大影响,介质温度在35~45 ℃,pH4.0~6.0或pH8.0都能促进脉冲强光的灭活作用。不同脉冲距离和时间下,Linear和Weibull模型都能够很好地拟合脉冲强光对大肠杆菌的杀菌效果(R2>0.99),且Weibull模型更为精确,但杀菌效果最终取决于辐射通量(可通过调节脉冲距离和脉冲时间改变)。总之,脉冲强光技术可以作为一种有效杀灭大肠杆菌的非热杀菌技术,其杀菌过程符合Linear和Weibull模型,且Weibull更为精确,该模型可以为饮用水消毒提供参考。     

Comparing predicting models for heat inactivation of Listeria monocytogenes and Pseudomonas aeruginosa at different pH

Under the same experimental conditions it has been demonstrated that whereas survival curves of Listeria monocytogenes in the range of temperatures from 54 to 62 °C followed a first-order kinetic, those of Pseudomonas aeruginosa in the range of temperatures from 50 to 56 °C were not linear showing a shoulder followed by a linear region. The first order kinetic model did not describe survival curves of P. aeruginosa. A model based on the Weibull distribution (Log₁₀(N_t/N₀)=(1/−2.303)*(t/b)ⁿ)) accurately described the inactivation kinetics of both microorganisms at the three pHs of 4, 5.5, 7.4 investigated. For both microorganisms, the b value depended on the treatment temperature and the pH of the treatment medium. Whereas for L. monocytogenes the n value was independent of the treatment conditions, for P. aeruginosa the n value depended on the pH of the treatment medium.

The model based on the Weibull distribution was capable of accurately predicting the treatment time to inactivate five Log₁₀ cycles of both microorganisms at the three pHs investigated.     

Inactivation kinetics of Yersinia enterocolitica by citric and lactic acid at different temperatures

Inactivation of Yersinia enterocolitica by citric (1--20% w/v) and lactic (0.3--4.0% v/v) acids at different temperatures (4, 20, 40 degrees C) has been investigated. Inactivation effect of citric and lactic acids was dependent on time and temperature of exposure and acid concentration. Survival curves of Y. enterocolitica suspended in citric acid solutions at 4 and 20 degrees C displayed a shoulder followed by an exponential inactivation, but at 40 degrees C a shoulder was not observed. At all temperatures investigated, survival curves of Y. enterocolitica suspended in lactic acid solutions were linear or slightly concave upwards. A mathematical model based on the Weibull distribution accurately described the kinetics of inactivation of Y. enterocolitica by both acids. The influence of the citric acid concentration on Y. enterocolitica resistance was independent of the treatment temperature. However for lactic acid, the influence of the acid concentration on microbial inactivation depended on the temperature. At any temperature investigated, lactic acid was significantly more effective than citric acid.     

Heat resistance of Listeria monocytogenes in semi-skim milk supplemented with vanillin

The kinetics of destruction of Listeria monocytogenes Scott A in semi-skim milk heated at 55, 58, 60 and 62°C without and with addition of 900, 1400 and 1800 ppm of vanillin was studied. Survival curves displayed an initial shoulder phase followed by an accelerating killing phase. Addition of vanillin to semi-skim milk heated between 55 and 62°C reduced the heat resistance of L. monocytogenes, effect that was more evident at the lowest temperatures. Two kinetic inactivation models were used to fit the data: the shoulder+log-linear model and the Weibull model. The presence of vanillin increased the death rate and reduced the shoulder length of L. monocytogenes in milk when working at low temperatures, while at the highest temperatures, this effect was less evident. Weibull model also showed that at lower temperatures 55°C-58°C, the population was inactivated at different treatment times, leaving a larger proportion of resistant microorganisms. Increasing the heating temperature to 60°C and 62°C, the biggest proportion of the population was destroyed in a very short time, while a very little proportion with higher resistance remained viable. Results suggest that the use of subinhibitory concentrations of vanillin added in combination with mild heat treatment could be used to enhance the inactivation of L. monocytogenes in semi-skim milk.     

Pathogen survival in chorizos: ecological factors

This study addressed health risks from ethnic sausages produced on a small scale, without inspection, in California and elsewhere. Mexican-style chorizo, a raw pork sausage that is not cured, fermented, or smoked, was contaminated experimentally in the batter with Escherichia coli O157:H7, Listeria monocytogenes, or Salmonella serotypes and stuffed into natural casings. Formulations were based on a market survey in California. Physical parameters that were controlled were pH, water activity (a(w)), and storage temperature. The pH was adjusted with vinegar, stabilizing at 5.0 within 24 h. Initial a(w) levels adjusted with salt were 0.97, 0.95, 0.93, 0.90, and 0.85; levels declined with time because of evaporation. Pathogen numbers declined with storage up to 7 days, with few brief exceptions. Main effects and interactions of constant temperature and pH with declining a(w) on survival of the pathogens were determined. Maximum death rates occurred at higher a(w) for E. coli O157:H7 and Salmonella than for L. monocytogenes. Salt used to adjust a(w) affected palatability. Spices (black pepper, chili pepper, chili powder, cumin, garlic, guajillo pepper, oregano, and paprika) comprised another, potentially significant aspect of the sausage formulation. Some (notably black pepper and cumin) carried an indigenous microflora that contributed significantly to the microbial load of the sausage batter. Only undiluted fresh and powdered garlic exhibited a significant antimicrobial effect on the pathogens. Although each of the tested formulations caused death of the inoculated pathogens, none of the death rates was sufficiently rapid to ensure safety within the probable shelf life of the product.