Lihan Huang

Eastern Idaho Regional Medical Center, Idaho Falls, Idaho, United States

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Publications (37)72.8 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: Most fresh produce, such as strawberries, receives minimal processing and is often eaten raw. Contamination of produce with pathogenic bacteria may occur during growth, harvest, processing, transportation, and storage (abuse temperature) and presents a serious public health risk. Strawberries have been implicated in an outbreak of Escherichia coli O157:H7 infection that sickened 15 people, including one death. Strawberries may also be contaminated by other serogroups of non-O157 Shiga toxin-producing E. coli (STEC), including O26, O45, O103, O111, O121 and O145, which have become known as the “Big Six” or “Top Six” non-O157 STECs. The objective of this research was to explore the potential application of high pressure processing (HPP) treatment to reduce or eliminate STECs in fresh strawberry puree (FSP). FSP, inoculated with a six-strain cocktail of the “Big Six” non-O157 STEC strains or a five-strain cocktail of E. coli O157:H7 in vacuum-sealed packages, were pressure-treated at 150, 250, 350, 450, 550, and 650 MPa (1 MPa = 106 N/m2) for 5, 15, and 30 min. HPP treatment, at 350 MPa for ≥5 min, significantly reduced STECs in FSP by about 6-log CFU/g from the initial cell population of ca. 8-log CFU/g. Cell rupture, observed by scanning electron microscopy (SEM), demonstrated that the HPP treatments can be potentially used to control both non-O157 and O157:H7 STECs in heat sensitive products.
    Food Microbiology 01/2014; 40:25–30. · 3.41 Impact Factor
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    ABSTRACT: Raw whole strawberries, if contaminated with pathogens, such as Escherichia coli O157:H7, must be pasteurized prior to consumption. Therefore, the objective of this research was to investigate the thermal inactivation kinetics of E. coli O157:H7 in strawberry puree (SP), and evaluate the changes in anthocyanins and color, and the survival of yeasts and molds (YM) after thermal processing. Inoculated with a 5-strain cocktail, fresh SP, with or without added sugar (20 and 40 °Brix), was heated at 50, 52, 54, 57.5, 60, and 62.5 °C to determine the thermal resistance of E. coli O157:H7. In raw SP, the average D-values of E. coli O157:H7 were 909.1, 454.6, 212.8, 46.1, and 20.2 s at 50, 52, 54, 57.5, and 60 °C, respectively, with a z-value of 5.9 °C. While linearly decreasing with temperature, the log D-values of E. coli O157:H7 increased slightly with sugar concentration. The log degradation rates of anthocyanins increased linearly with temperature, but decreased slightly with sugar concentrations. These results suggest that sugar may provide some protection to both E. coli O157: H7 and anthocyanins in SP. The browning index was not affected by heating at 50 and 52 °C at low sugar concentrations, but increased by an average of 1.28%, 2.21%, and 10.1% per min when SP was exposed to heating at 54, 57.5, and 60 °C, respectively. YM was also inactivated by heating. This study demonstrated that properly designed thermal processes can effectively inactivate E. coli O157:H7 and YM in contaminated SP, while minimizing the changes in anthocyanins and color.
    Journal of Food Science 01/2014; 79(1):M74-80. · 1.78 Impact Factor
  • ChangCheng Li, Lihan Huang, Jinquan Chen
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    ABSTRACT: Peanut butter has been implicated in multi-state outbreaks of salmonellosis in recent years. Studies have shown that Salmonella exhibited increased thermal resistance in peanut butter. However, little is known about the effect of product formulation on the kinetics of survival of Salmonella during thermal treatment. Therefore, the objective of this research was to compare the thermal resistance of Salmonella in four commercially available peanut butter and spread products, and evaluate the effect of product formulation on the survival of this pathogen during heating. Four peanut butter and spread samples, including Omega 3 (A), regular fat (B), reduced sugar (C), and reduced fat (D), inoculated with a 6-strain cocktail of Salmonella spp., were heated at 70, 75, 80, 85, and 90 °C. Experimental results showed that the highest thermal resistance of Salmonella was found in the samples with reduced fat, while the least in the samples with Omega 3 formulation. No significant difference in the bacterial thermal resistance was observed in the regular fat and reduced sugar formulations. The Weibull survival model was used to describe the survival curves. Results showed that the average exponent (shape factor) of the model ranged from 0.38 to 0.662, suggesting progressively decreased rate of inactivation during heating. The scale (rate) coefficients of the model increased linearly with temperature. The calculated minimum lethal temperature for Salmonella was 54.8, 59.8, 59.5, and 63.9 °C in samples A, B, C, and D, respectively. No tail effect was observed. The results of this study suggest that proper formulation of peanut butter and spread may enhance thermal inactivation of Salmonella.
    Food Control. 01/2014; 45:143–149.
  • Lihan Huang
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    ABSTRACT: Predictive microbiology is an area of applied research in food science that uses mathematical models to predict the changes in the population of pathogenic or spoilage microorganisms in foods exposed to complex environmental changes during processing, transportation, distribution, and storage. It finds applications in shelf-life prediction and risk assessments of foods. The objective of this research was to describe the performance of a new user-friendly comprehensive data analysis tool, the Integrated Pathogen Modeling Model (IPMP 2013), recently developed by the USDA Agricultural Research Service. This tool allows users, without detailed programming knowledge, to analyze experimental kinetic data and fit the data to known mathematical models commonly used in predictive microbiology. Data curves previously published in literature were used to test the models in IPMP 2013. The accuracies of the data analysis and models derived from IPMP 2013 were compared in parallel to commercial or open-source statistical packages, such as SAS® or R. Several models were analyzed and compared, including a three-parameter logistic model for growth curves without lag phases, reduced Huang and Baranyi models for growth curves without stationary phases, growth models for complete growth curves (Huang, Baranyi, and re-parameterized Gompertz models), survival models (linear, re-parameterized Gompertz, and Weibull models), and secondary models (Ratkowsky square-root, Huang square-root, Cardinal, and Arrhenius-type models). The comparative analysis suggests that the results from IPMP 2013 were equivalent to those obtained from SAS® or R. This work suggested that the IPMP 2013 could be used as a free alternative to SAS®, R, or other more sophisticated statistical packages for model development in predictive microbiology.
    International journal of food microbiology 11/2013; 171C:100-107. · 3.01 Impact Factor
  • Lihan Huang
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    ABSTRACT: The objective of this research is to determine the thermal inactivation kinetics of Listeria monocytogenes in chicken breast meat under both isothermal and dynamic conditions. A four-strain cocktail of L. monocytogenes was inoculated to chicken breast meat. Isothermal studies were performed by submerging samples under hot water maintained at constant temperatures ranging from 54 to 66 °C. The D values at each temperature were determined and used to calculate the z value, using log(D) = log(D0) − T/z. Dynamic studies were conducted by submerging samples in a water bath with its temperature programmed to increase linearly from 30 to 65 °C at 1.25 °C/min or 1.73 °C/min. A method was developed to determine the kinetic parameters from linear heating temperature profiles.The thermal inactivation of L. monocytogenes in chicken breast meat followed the first-order kinetics. The z value determined from the isothermal studies was 4.95 °C, which is very close to the values reported in the literature. The dynamic method can also be used to determine the thermal inactivation kinetics of L. monocytogenes. The average z value (4.10 °C) determined by the dynamic method was slightly lower than that determined by the isothermal method. However, the parameters (D0 and z) determined from both isothermal and dynamic methods can be used to estimate the survival of L. monocytogenes exposed to linear heating temperature profiles, with statistically equal accuracies.The dynamic method explored in this study can be used to determine the D0 and z values of microorganisms that exhibit first-order kinetics and are exposed to linear heating temperature profiles. Compared to the isothermal method, the dynamic method requires few data points and is equally accurate.
    Food Control. 10/2013; 33(2):484–488.
  • Lihan Huang
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    ABSTRACT: The objective of this work was to optimize a mathematical equation for use as a primary kinetic model that employed a new approach to describe the three-phase growth of bacteria under constant temperature conditions. This research adopted an optimization algorithm in combination with the Runge–Kutta method to solve the differential form of the new growth model in search of an optimized lag phase transition coefficient (LPTC), which is used to define the adaption and duration of lag phases of bacteria prior to exponential growth. Growth curves of Listeria monocytogenes, Escherichia coli O157:H7, and Clostridium perfringens, selected from previously published data, were analyzed to obtain an optimized LPTC for each growth curve and a global LPTC for all growth curves. With the new optimized LPTC, the new growth model could be used to accurately describe the bacterial growth curves with three distinctive phases (lag, exponential, and stationary). The new optimized LPTC significantly improved the performance and applicability of the new model. The results of statistical analysis (ANOVA) suggested that the new growth model performed equally well with the Baranyi model. It can be used as an alternative primary model for bacterial growth if the bacterial adaption is more significant in controlling the lag phase development.
    Food Control. 07/2013; 32(1):283–288.
  • Ting Fang, Yanhong Liu, Lihan Huang
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    ABSTRACT: The main objective of this study was to investigate the growth kinetics of Listeria monocytogenes and background microorganisms in fresh-cut cantaloupe. Fresh-cut cantaloupe samples, inoculated with three main serotypes (1/2a, 1/2b, and 4b) of L. monocytogenes, were incubated at different temperatures, ranging from 4 to 43 °C, to develop kinetic growth models. During storage studies, the population of both background microorganisms and L. monocytogenes began to increase almost immediately, with little or no lag phase for most growth curves. All growth curves, except for two growth curves of L. monocytogenes 1/2a at 4 °C, developed to full curves (containing exponential and stationary phases), and can be described by a 3-parameter logistic model. There was no significant difference (P = 0.28) in the growth behaviors and the specific growth rates of three different serotypes of L. monocytogenes inoculated to fresh-cut cantaloupe. The effect of temperature on the growth of L. monocytogenes and spoilage microorganisms was evaluated using three secondary models. For L. monocytogenes, the minimum and maximum growth temperatures were estimated by both the Ratkowsky square-root and Cardinal parameter models, and the optimum temperature and the optimum specific growth rate by the Cardinal parameter model. An Arrhenius-type model provided more accurate estimation of the specific growth rate of L. monocytogenes at temperatures <4 °C. The kinetic models developed in this study can be used by regulatory agencies and food processors for conducting risk assessment of L. monocytogenes in fresh-cut cantaloupe, and for estimating the shelf-life of fresh-cut products.
    Food Microbiology 05/2013; 34(1):174-81. · 3.41 Impact Factor
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    ABSTRACT: Listeria monocytogenes is a food-borne pathogen of significant threat to public health. Nisin is the only bacteriocin that can be used as a food preservative. Due to its antimicrobial activity, it can be used to control L. monocytogenes in food; however, the antimicrobial mechanism of nisin activity against L. monocytogenes is not fully understood. The CtsR (class III stress gene repressor) protein negatively regulates the expression of class III heat shock genes. A spontaneous pressure-tolerant ctsR deletion mutant that showed increased sensitivity to nisin has been identified. Microarray technology was used to monitor the gene expression profiles of the ctsR mutant under treatments with nisin. Compared to the nisin-treated wild type, 113 genes were up-regulated (>2-fold increase) in the ctsR deletion mutant whereas four genes were down-regulated (<-2-fold decrease). The up-regulated genes included genes that encode for ribosomal proteins, membrane proteins, cold-shock domain proteins, translation initiation and elongation factors, cell division, an ATP-dependent ClpC protease, a putative accessory gene regulator protein D, transport and binding proteins, a beta-glucoside-specific phosphotransferase system IIABC component, as well as hypothetical proteins. The down-regulated genes consisted of genes that encode for virulence, a transcriptional regulator, a stress protein, and a hypothetical protein. The gene expression changes determined by microarray assays were confirmed by quantitative real-time PCR analyses. Moreover, an in-frame deletion mutant for one of the induced genes (LMOf2365_1877) was constructed in the wild-type L. monocytogenes F2365 background. ΔLMOf2365_1877 had increased nisin sensitivity compared to the wild-type strain. This study enhances our understanding of how nisin interacts with the ctsR gene product in L. monocytogenes and may contribute to the understanding of the antibacterial mechanisms of nisin.
    Journal of Industrial Microbiology 03/2013; · 1.80 Impact Factor
  • Lihan Huang
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    ABSTRACT: The objective of this work was to develop a numerical simulation method to study the heat transfer process and inactivation of Escherichia coli O157:H7 during gas grilling of non-intact beef steaks (NIBS). A finite difference and optimization algorithm was developed to determine the effective heat transfer parameters during grilling. After validation, these parameters were used in a finite element method to simulate the temperature profiles at various locations of NIBS (2.54 cm in thickness). The computer simulation results showed that E. coli O157:H7 may survive the heating processes if normal grilling conditions for intact beef steaks were used. Computer simulation results also suggested that E. coli O157:H7 might be effectively inactivated if NIBS (2.54 cm) were evenly flipped (every 4 min) and cooked for 16 min during cooking. The result of this study may help the food service industry to develop more adequate grilling methods and conditions to cook NIBS.
    Journal of Food Engineering. 12/2012; 113(3):380–388.
  • Lihan Huang
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    ABSTRACT: This study was conducted to investigate the growth of non-O157 Shiga toxin-producing Escherichia coli (STEC) in spinach leaves and to develop kinetic models to describe the bacterial growth. Six serogroups of non-O157 STEC, including O26, O45, O103, O111, O121, and O145, were used in the growth studies conducted isothermally at 4, 8, 15, 20, 25, 30, and 35°C. Both STEC and background microflora were enumerated to develop kinetic models. Growth of STEC in spinach leaves was observed at elevated temperatures (15-35°C), but not at 4 and 8°C. This study considered the dynamic interactions between the STEC cells and the background microflora. A modified Lotka-Volterra and logistic equation was used to simulate the bacterial growth. In combination with an unconstrained optimization procedure, the differential growth equations were solved numerically to evaluate the dynamic interactions between the STEC cells and the background microflora, and to determine the kinetic parameters by fitting each growth curve to the growth equations. A close agreement between the experimental growth curves and the numerical analysis results was obtained. The analytical results showed that the growth of STEC in spinach leaves was unhindered when the population was low, but the growth was suppressed by the background microflora as the STEC population approached the maximum population density. The effect of temperature on the growth of both STEC and background microflora was also evaluated. Secondary models, evaluating the effect of temperature on growth rates, were also developed. The estimated apparent minimum growth temperature for STEC was 11°C in commercial spinach leaves. The methodology and results of this study can be used to examine the dynamic interactions and growth between different bacteria in foods, and to conduct risk assessments of STEC in spinach leaves.
    International journal of food microbiology 11/2012; 160(1):32-41. · 3.01 Impact Factor
  • Ting Fang, Joshua B Gurtler, Lihan Huang
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    ABSTRACT: Cronobacter sakazakii is a life-threatening bacterium, infrequently implicated in illnesses associated with the consumption of powdered infant formula (PIF). It can cause rare but invasive infections in neonatal infants who consume contaminated PIF. The objective of this research was to investigate the growth kinetics and develop mathematical models to predict the growth of heat-injured C. sakazakii in reconstituted PIF (RPIF). RPIF, inoculated with a 6-strain cocktail of non-heat-treated (uninjured) or heat-injured C. sakazakii, was incubated at different temperatures to develop growth models. Except for storage at 6 °C, C. sakazakii grew well at all test temperatures (10 to 48 °C). Uninjured C. sakazakii exhibited no observable lag phase, while a lag phase was apparent in heat-treated cells. A simple 3-parameter logistic equation was used to fit growth curves for non-heat-treated cells, while both Baranyi and Huang models were suitable for heat-treated C. sakazakii. Calculated minimum and maximum growth temperatures were 6.5 and 51.4 °C for non-heat-treated cells, and 6.9 and 50.1 °C for heat-treated cells of C. sakazakii in RPIF, respectively. There was no significant difference between growth rates of non-heat-treated and heat-injured cells in RPIF. For heat-treated cells of C. sakazakii, the lag phase was temperature-dependent and very short (between 25 °C and 48 °C). These results suggest that both non-heat-treated and heat-injured C. sakazakii cells may present a risk to infants if the pathogens are not completely destroyed by heat in RPIF and then exposed to subsequent temperature abuse. Practical Application:  C. sakazakii is a life-threatening bacterium found in powdered infant formula (PIF). This study shows that the uninjured bacterium exhibits very short or no lag phase if not refrigerated and can grow well in reconstituted PIF (RPIF), while the heat-injured cells can multiply at an equivalent rate following metabolic recovery. Temperature abuse may allow C. sakazakii to grow and endanger infants fed with RPIF. Predictive models developed in this study can be used to estimate the growth and conduct risk assessments of this pathogen.
    Journal of Food Science 08/2012; 77(9):E247-55. · 1.78 Impact Factor
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    ABSTRACT: The surfaces of ready-to-eat meats are susceptible to postprocessing contamination by Listeria monocytogenes. This study examined and modeled the growth characteristics of L. monocytogenes on cooked ham treated with lactic acid solutions (LA). Cooked ham was inoculated with L. monocytogenes (ca. 10(3) CFU/g), immersed in 0, 0.5, 0.75, 1.0, 1.25, 1.5, and 2.0% LA for 30 min, vacuum packaged, and stored at 4, 8, 12, and 16°C. LA immersion resulted in <0.7 log CFU/g immediate reduction of L. monocytogenes on ham surfaces, indicating the immersion alone was not sufficient for reducing L. monocytogenes. During storage, no growth of L. monocytogenes occurred on ham treated with 1.5% LA at 4 and 8°C and with 2% LA at all storage temperatures. LA treatments extended the lag-phase duration (LPD) of L. monocytogenes and reduced the growth rate (GR) from 0.21 log CFU/day in untreated ham to 0.13 to 0.06 log CFU/day on ham treated with 0.5 to 1.25% LA at 4°C, whereas the GR was reduced from 0.57 log CFU/day to 0.40 to 0.12 log CFU/day at 8°C. A significant extension of the LPD and reduction of the GR of L. monocytogenes occurred on ham treated with >1.25% LA. The LPD and GR as a function of LA concentration and storage temperature can be satisfactorily described by a polynomial or expanded square-root model. Results from this study indicate that immersion treatments with >1.5% LA for 30 min may be used to control the growth of L. monocytogenes on cooked meat, and the models would be useful for selecting LA immersion treatments for meat products to achieve desired product safety.
    Journal of food protection 08/2012; 75(8):1404-10. · 1.83 Impact Factor
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    ABSTRACT: Microwave (MW) heating using continuous power output with feedback control and a modified ingredient formulation may provide better and consistent cooking of foods. Currently, household units with build-in inverter power supply units are available. These new generation MW ovens provide continuous, adjustable output and cooking, in contrast to the traditional rectifier-based ovens that rely on the on-off mechanism for control. This study attempted to apply a feedback power control (termed as modified or "smart" MW oven) and phosphate treatment to further improve heating uniformity and enhance food quality and safety. Listeria monocytogenes (Lm, 4-strain cocktail), Escherichia coli O157:H7 (Ec, 5-strain cocktail), and Salmonella spp. (Sal, 6-strain cocktail), surface inoculated onto catfish fillets (75 × 100 × 15 mm; weight 110 g), were heated using the modified MW oven to study the inactivation of the pathogens. The sensitivity of these 3 bacteria to MW heating was in the order of Ec (most), Lm, and Sal (least). Greater than 4 to 5 log CFU reductions of Ec, Lm, or Sal counts on catfish fillet surfaces were inactivated within 2 min of 1250 W MW heating, where the fillet surface temperature increased from 10 to 20 °C to 80 to 90 °C. MW heating caused degradation of catfish fillet texture, which was noticeable as early as 10 to 15 s after the heating started, as evidenced by bumping sounds. Bumping can be significantly reduced by soaking fillets in phosphate solution. However, the results may need verification if applied in different MW ovens and/or with foods positioned away the geometric oven center. This study successfully demonstrated the feasibility of applying MW energy to eliminate foodborne pathogens on fish fillets. PRACTICAL APPLICATION: The results demonstrated in this report with the "smart" microwave oven design may enhance microwaveable food safety and quality, and therefore promote the microwaveable food business.
    Journal of Food Science 08/2012; 77(8):E209-14. · 1.78 Impact Factor
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    ABSTRACT: The objective of this study was to investigate the growth of Shiga toxin-producing Escherichia coli (STEC, including serogroups O45, O103, O111, O121, and O145) in raw ground beef and to develop mathematical models to describe the bacterial growth under different temperature conditions. Three primary growth models were evaluated, including the Baranyi model, the Huang 2008 model, and a new growth model that is based on the communication of messenger signals during bacterial growth. A 5 strain cocktail of freshly prepared STEC was inoculated to raw ground beef samples and incubated at temperatures ranging from 10 to 35 °C at 5 °C increments. Minimum relative growth (<1 log₁₀ cfu/g) was observed at 10 °C, whereas at other temperatures, all 3 phases of growth were observed. Analytical results showed that all 3 models were equally suitable for describing the bacterial growth under constant temperatures. The maximum cell density of STEC in raw ground beef increased exponentially with temperature, but reached a maximum of 8.53 log₁₀ cfu/g of ground beef. The specific growth rates estimated by the 3 primary models were practically identical and can be evaluated by either the Ratkowsky square-root model or a Bělehrádek-type model. The temperature dependence of lag phase development for all 3 primary models was also developed. The results of this study can be used to estimate the growth of STEC in raw ground beef at temperatures between 10 and 35 °C. PRACTICAL APPLICATION: Incidents of foodborne infections caused by non-O157 Shiga toxin-producing Escherichia coli (STEC) have increased in recent years. This study reports the growth kinetics and mathematical modeling of STEC in ground beef. The mathematical models can be used in risk assessment of STEC in ground beef.
    Journal of Food Science 04/2012; 77(4):M217-25. · 1.78 Impact Factor
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    ABSTRACT: The objective of this paper to conduct a parallel comparison of a new Bělehrádek-type growth rate (with an exponent of 1.5, or the Huang model), Ratkowsky square-root, and Ratkowsky square equations as secondary models for evaluating the effect of temperature on the growth of microorganisms. Growth rates of psychrotrophs and mesophiles were selected from the literature, and independently analyzed with the 3 models using nonlinear regression. Analysis of variance (ANOVA) was used to compare the means of growth rate (μ), estimated minimum temperature (T(min) ), approximate standard errors (SE) of T(min) , model mean square errors (MSE), accuracy factor (A(f) ), bias factor (B(f) ), relative residual errors (δ), Akaike information criterion (AICc), and Bayesian information criterion (BIC). Based on the estimated T(min) values, the Huang model distinctively classified the bacteria into 2 groups (psychrotrophs and mesophiles). No significant difference (P > 0.05) was observed among the means of the μ values reported in the literature or estimated by the 3 models, suggesting that all 3 models were suitable for curve fitting. Nor was there any significant difference in MSE, SE, δ, A(f) , B(f) , AICc, and BIC. The T(min) values estimated by the Huang model were significantly higher than those estimated by the Ratkowsky models, but were in closer agreement with the biological minimum temperatures for both psychrotrophs and mesophiles. The T(min) values estimated by the Ratkowsky models systematically underestimated the minimum growth temperatures. In addition, statistical estimation showed that the mean exponent for the new Bělehrádek-type growth rate model may indeed be 1.5, further supporting the validity of the Huang model.
    Journal of Food Science 10/2011; 76(8):M547-57. · 1.78 Impact Factor
  • Lihan Huang, Andy Hwang, John Phillips
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    ABSTRACT: The objective of this work is to develop a mathematical model for evaluating the effect of temperature on the rate of microbial growth. The new mathematical model is derived by combination and modification of the Arrhenius equation and the Eyring-Polanyi transition theory. The new model, suitable for both suboptimal and the entire growth temperature ranges, was validated using a collection of 23 selected temperature-growth rate curves belonging to 5 groups of microorganisms, including Pseudomonas spp., Listeria monocytogenes, Salmonella spp., Clostridium perfringens, and Escherichia coli, from the published literature. The curve fitting is accomplished by nonlinear regression using the Levenberg-Marquardt algorithm. The resulting estimated growth rate (μ) values are highly correlated to the data collected from the literature (R(2) = 0.985, slope = 1.0, intercept = 0.0). The bias factor (B(f) ) of the new model is very close to 1.0, while the accuracy factor (A(f) ) ranges from 1.0 to 1.22 for most data sets. The new model is compared favorably with the Ratkowsky square root model and the Eyring equation. Even with more parameters, the Akaike information criterion, Bayesian information criterion, and mean square errors of the new model are not statistically different from the square root model and the Eyring equation, suggesting that the model can be used to describe the inherent relationship between temperature and microbial growth rates. The results of this work show that the new growth rate model is suitable for describing the effect of temperature on microbial growth rate. Practical Application:  Temperature is one of the most significant factors affecting the growth of microorganisms in foods. This study attempts to develop and validate a mathematical model to describe the temperature dependence of microbial growth rate. The findings show that the new model is accurate and can be used to describe the effect of temperature on microbial growth rate in foods.
    Journal of Food Science 10/2011; 76(8):E553-60. · 1.78 Impact Factor
  • Lihan Huang
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    ABSTRACT: A new mechanistic growth model was developed to describe microbial growth under isothermal conditions. The new mathematical model was derived from the basic observation of bacterial growth that may include lag, exponential, and stationary phases. With this model, the lag phase duration and exponential growth rate of a growth curve were simultaneously determined by nonlinear regression. The new model was validated using Listeria monocytogenes and Escherichia coli O157:H7 in broth or meat. Statistical results suggested that both bias factor (B(f)) and accuracy factor (A(f)) of the new model were very close to 1.0. A new Bĕlehdrádek-type rate model and the Ratkowsky square-root model were used to describe the temperature dependence of bacterial growth rate. It was observed that the maximum and minimum temperatures were more accurately estimated by a new Bĕlehdrádek-type rate model. Further, the inverse of square-roots of lag phases was found proportional to temperature, making it possible to estimate the lag phase duration from the growth temperature.
    Food Microbiology 06/2011; 28(4):770-6. · 3.41 Impact Factor
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    ABSTRACT: A predictive model for Salmonella spp. growth in ground pork was developed and validated using kinetic growth data. Salmonella spp. kinetic growth data in ground pork were collected at several isothermal conditions (between 10 and 45°C) and Baranyi model was fitted to describe the growth at each temperature, separately. The maximum growth rates (μ(max)) estimated from the Baranyi model were modeled as a function of temperature using a modified Ratkowsky equation. To estimate bacterial growth under dynamic temperature conditions, the differential form of the Baranyi model, in combination with the modified Ratkowsky equation for rate constants, was solved numerically using fourth order Runge-Kutta method. The dynamic model was validated using five different dynamic temperature profiles (linear cooling, exponential cooling, linear heating, exponential heating, and sinusoidal). Performance measures, root mean squared error, accuracy factor, and bias factor were used to evaluate the model performance, and were observed to be satisfactory. The dynamic model can estimate the growth of Salmonella spp. in pork within a 0.5 log accuracy under both linear and exponential cooling profiles, although the model may overestimate or underestimate at some data points, which were generally<1 log. Under sinusoidal temperature profiles, the estimates from the dynamic model were also within 0.5 log of the observed values. However, underestimation could occur if the bacteria were exposed to temperatures below the minimum growth temperature of Salmonella spp., since low temperature conditions could alter the cell physiology. To obtain an accurate estimate of Salmonella spp. growth using the models reported in this work, it is suggested that the models be used at temperatures above 7°C, the minimum growth temperature for Salmonella spp. in pork.
    Food Microbiology 06/2011; 28(4):796-803. · 3.41 Impact Factor
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    ABSTRACT: Comparison of Clostridium perfringens spore germination and outgrowth in cooked uncured products during cooling for different meat species is presented. Cooked, uncured product was inoculated with C. perfringens spores and vacuum packaged. For the isothermal experiments, all samples were incubated in a water bath stabilized at selected temperatures between 10 and 51°C and sampled periodically. For dynamic experiments, the samples were cooled from 54.4 to 27°C and subsequently from 27 to 4°C for different time periods, designated as x and y hours, respectively. The growth models used were based on a model developed by Baranyi and Roberts (1994. A dynamic approach to predicting bacterial growth in food. Int. J. Food Micro. 23, 277-294), which incorporates a constant, referred to as the physiological state constant, q(0). The value of this constant captures the cells' history before the cooling begins. To estimate specific growth rates, data from isothermal experiments were used, from which a secondary model was developed, based on a form of Ratkowsky's 4-parameter equation. The estimated growth kinetics associated with pork and chicken were similar, but growth appeared to be slightly greater in beef; for beef, the maximum specific growth rates estimated from the Ratkowsky curve was about 2.7 log(10) cfu/h, while for the other two species, chicken and pork, the estimate was about 2.2 log(10) cfu/h. Physiological state constants were estimated by minimizing the mean square error of predictions of the log(10) of the relative increase versus the corresponding observed quantities for the dynamic experiments: for beef the estimate was 0.007, while those for pork and chicken the estimates were about 0.014 and 0.011, respectively. For a hypothetical 1.5h cooling from 54°C to 27° and 5h to 4°C, corresponding to USDA-FSIS cooling compliance guidelines, the predicted growth (log(10) of the relative increase) for each species was: 1.29 for beef; 1.07 for chicken and 0.95 log(10) for pork. However, it was noticed that for pork in particular, the model using the derived q(0) had a tendency to over-predict relative growth when the observed amount of relative growth was small, and under-predict the relative growth when the observed amount of relative growth was large. To provide more fail-safe estimate, rather than using the derived value of q(0), a value of 0.04 is recommended for pork.
    Food Microbiology 06/2011; 28(4):791-5. · 3.41 Impact Factor
  • Lihan Huang
    International journal of food microbiology 03/2011; · 3.01 Impact Factor

Publication Stats

144 Citations
72.80 Total Impact Points

Institutions

  • 2002–2014
    • Eastern Idaho Regional Medical Center
      Idaho Falls, Idaho, United States
  • 2012–2013
    • Fujian Agriculture and Forestry University
      Min-hou, Fujian, China
    • Agricultural Research Service
      Kerrville, Texas, United States
  • 2011
    • University of Nebraska at Lincoln
      • Department of Food Science and Technology
      Lincoln, NE, United States
    • Franklin and Marshall College
      Lancaster, California, United States
  • 2007–2011
    • United States Department of Agriculture
      • Agricultural Research Service (ARS)
      Washington, D. C., DC, United States