Jeyamkondan Subbiah

Mathematical modeling of growth of Salmonella in raw ground beef under isothermal conditions from 10 to 45 °C

The objective of this study was to develop primary and secondary models to describe the growth of Salmonella in raw ground beef. Primary and secondary models can be integrated into a dynamic model that can predict the microbial growth under varying environmental conditions. Growth data of Salmonella at nine different isothermal conditions--10, 15, 20, 25, 28, 32, 35, 42, and 45 degrees C were first fitted into primary models, namely the logistic, modified Gompertz, Baranyi, and Huang models. Performances of these models were evaluated by using various statistical criteria, namely mean square error (MSE), pseudo-R(2), -2 log likelihood, Akaikes and Bayesians information criteria. All the chosen models fitted well to the growth data of Salmonella based on these criteria. The results of statistical analysis showed that there was no significant difference in the performances of the four primary models, suggesting that the models were equally suitable for describing isothermal bacterial growth. The specific growth rates derived from each model was fitted to the Modified Ratkowsky equation, relating the specific growth rate to growth temperatures. It was also observed that the lag phase duration was an inverse function of specific growth rates. These models, if validated, can be used to construct dynamic models to predict potential Salmonella growth in raw ground beef.

Enhanced Anthocyanin Extraction from Red Cabbage Using Pulsed Electric Field Processing

This study was conducted to evaluate the effect of pulsed electric field (PEF) treatment on anthocyanin extraction from red cabbage using water as a solvent. Mashed cabbage was placed in a batch treatment chamber and subjected to PEF (2.5 kV/cm electric field strength; 15 micros pulse width and 50 pulses, specific energy 15.63 J/g). Extracted anthocyanin concentrations (16 to 889 microg/mL) were determined using HPLC. Heat and light stabilities of the control and PEF-treated samples, having approximately the same initial concentrations, were studied. PEF treatments enhanced total anthocyanin extraction in water from red cabbage by 2.15 times with a higher proportion of nonacylated forms than the control (P < 0.05). The heat and light stabilities of the PEF-treated samples and control samples were not significantly different (P > 0.05). Practical Application: An innovative pretreatment technology, pulsed electric field processing, enhanced total anthocyanin extraction in water from red cabbage by 2.15 times. Manufacturers of natural colors can use this technology to extract anthocyanins from red cabbage efficiently.

Ultraviolet and Pulsed Electric Field Treatments Have Additive Effect on Inactivation of E. coli in Apple Juice

Apple juice inoculated with Escherichia coli ATCC 23472 was processed continuously using either ultraviolet (UV), high-voltage pulsed electric field (PEF), or a combination of the PEF and UV treatment systems. Apple juice was pumped through either of the systems at 3 flow rates (8, 14, and 20 mL/min). E. coli was reduced by 3.46 log CFU/mL when exposed in a 50 cm length of UV treatment chamber at 8 mL/min (2.94 s treatment time with a product temperature increase of 13 degrees C). E. coli inactivation of 4.87 log CFU/mL was achieved with a peak electric field strength of 60 kV/cm and 11.3 pulses (average pulse width of 3.5 mus, product temperature increased to 52 degrees C). E. coli reductions resulting from a combination treatment of UV and PEF applied sequentially were evaluated. A maximum E. coli reduction of 5.35 log CFU/mL was achieved using PEF (electrical field strength of 60 kV/cm, specific energy of 162 J/mL, and 11.3 pulses) and UV treatments (length of 50 cm, treatment time of 2.94 s, and flow rate of 8 mL/min). An additive effect was observed for the combination treatments (PEF and UV), regardless of the order of treatment (P > 0.05). E. coli reductions of 5.35 and 5.30 log CFU/mL with PEF treatment (electrical field strength of 60 kV/cm, specific energy of 162 J/mL, and 11.3 pulses) followed by UV (length of 30 cm, treatment time of 1.8 s, and flow rate of 8 mL/min) and UV treatment followed by PEF (same treatment conditions), respectively. No synergistic effect was observed.

Dynamic model for predicting growth of Salmonella spp. in ground sterile pork.

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.

Heat and Mass Transport during Microwave Heating of Mashed Potato in Domestic Oven—Model Development, Validation, and Sensitivity Analysis

UNLABELLED A 3-dimensional finite-element model coupling electromagnetics and heat and mass transfer was developed to understand the interactions between the microwaves and fresh mashed potato in a 500 mL tray. The model was validated by performing heating of mashed potato from 25 °C on a rotating turntable in a microwave oven, rated at 1200 W, for 3 min. The simulated spatial temperature profiles on the top and bottom layer of the mashed potato showed similar hot and cold spots when compared to the thermal images acquired by an infrared camera. Transient temperature profiles at 6 locations collected by fiber-optic sensors showed good agreement with predicted results, with the root mean square error ranging from 1.6 to 11.7 °C. The predicted total moisture loss matched well with the observed result. Several input parameters, such as the evaporation rate constant, the intrinsic permeability of water and gas, and the diffusion coefficient of water and gas, are not readily available for mashed potato, and they cannot be easily measured experimentally. Reported values for raw potato were used as baseline values. A sensitivity analysis of these input parameters on the temperature profiles and the total moisture loss was evaluated by changing the baseline values to their 10% and 1000%. The sensitivity analysis showed that the gas diffusion coefficient, intrinsic water permeability, and the evaporation rate constant greatly influenced the predicted temperature and total moisture loss, while the intrinsic gas permeability and the water diffusion coefficient had little influence. PRACTICAL APPLICATION This model can be used by the food product developers to understand microwave heating of food products spatially and temporally. This tool will allow food product developers to design food package systems that would heat more uniformly in various microwave ovens. The sensitivity analysis of this study will help us determine the most significant parameters that need to be measured accurately for reliable model prediction.

Optical scattering with hyperspectral imaging to classify longissimus dorsi muscle based on beef tenderness using multivariate modeling

The objective of this study was to develop a non-destructive method for classifying cooked-beef tenderness using hyperspectral imaging of optical scattering on fresh beef muscle tissue. A hyperspectral imaging system (λ=922-1739 nm) was used to collect hyperspectral scattering images of the longissimus dorsi muscle (n=472). A modified Lorentzian function was used to fit optical scattering profiles at each wavelength. After removing highly correlated parameters extracted from the Lorentzian function, principal component analysis was performed. Four principal component scores were used in a linear discriminant model to classify beef tenderness. In a validation data set (n=118 samples), the model was able to successfully classify tough and tender samples with 83.3% and 75.0% accuracies, respectively. Presence of fat flecks did not have a significant effect on beef tenderness classification accuracy. The results demonstrate that hyperspectral imaging of optical scattering is a viable technology for beef tenderness classification.

Morphometric analysis of gastrocnemius muscle biopsies from patients with peripheral arterial disease: objective grading of muscle degeneration

Peripheral arterial disease (PAD), which affects ~10 million Americans, is characterized by atherosclerosis of the noncoronary arteries. PAD produces a progressive accumulation of ischemic injury to the legs, manifested as a gradual degradation of gastrocnemius histology. In this study, we evaluated the hypothesis that quantitative morphological parameters of gastrocnemius myofibers change in a consistent manner during the progression of PAD, provide an objective grading of muscle degeneration in the ischemic limb, and correlate to a clinical stage of PAD. Biopsies were collected with a Bergström needle from PAD patients with claudication (n = 18) and critical limb ischemia (CLI; n = 19) and control patients (n = 19). Myofiber sarcolemmas and myosin heavy chains were labeled for fluorescence detection and quantitative analysis of morphometric variables, including area, roundness, perimeter, equivalent diameter, major and minor axes, solidity, and fiber density. The muscle specimens were separated into training and validation data sets for development of a discriminant model for categorizing muscle samples on the basis of disease severity. The parameters for this model included standard deviation of roundness, standard deviation of solidity of myofibers, and fiber density. For the validation data set, the discriminant model accurately identified control (80.0% accuracy), claudicating (77.7% accuracy), and CLI (88.8% accuracy) patients, with an overall classification accuracy of 82.1%. Myofiber morphometry provided a discriminant model that establishes a correlation between PAD progression and advancing muscle degeneration. This model effectively separated PAD and control patients and provided a grading of muscle degeneration within clinical stages of PAD.

Assessment of Heating Rate and Non-uniform Heating in Domestic Microwave Ovens

Abstract Due to the inherent nature of standing wave patterns of microwaves inside a domestic microwave oven cavity and varying dielectric properties of different food components, microwave heating produces non-uniform distribution of energy inside the food. Non-uniform heating is a major food safety concern in not-ready-to-eat (NRTE) microwaveable foods. In this study, we present a method for assessing heating rate and non-uniform heating in domestic microwave ovens. In this study a custom designed container was used to assess heating rate and non-uniform heating of a range of microwave ovens using a hedgehog of 30 T-type thermocouples. The mean and standard deviation of heating rate along the radial distance and sector of the container were measured and analyzed. The effect of the location of rings and sectors was analyzed using ANOVA to identify the best location for placing food on the turntable. The study suggested that the best location to place food in a microwave oven is not at the center but near the edge of the turntable assuming uniform heating is desired. The effect of rated power and cavity size on heating rate and non-uniform heating was also studied for a range of microwave ovens. As the rated power and cavity size increases, heating rate increases while non-uniform heating decreases. Sectors in the container also influenced heating rate (p < 0.0001), even though it did not have clear trend on heating rate. In general, sectors close to the magnetron tend to heat slightly faster than sectors away from the magnetron. However, the variation in heating rate among sectors was only 2 °C/min and considered not practically important. Overall heating performance such as mean heating rate and non-uniform heating did not significantly vary between the two replications that were performed 4 h apart. However, microwave ovens were inconsistent in producing the same heating patterns between the two replications that were performed 4 h apart.

Dynamic Predictive Model for the Growth of Salmonella spp. in Liquid Whole Egg

UNLABELLED A dynamic model for the growth of Salmonella spp. in liquid whole egg (LWE) (approximately pH 7.8) under continuously varying temperature was developed. The model was validated using 2 (5 to 15 °C; 600 h and 10 to 40 °C; 52 h) sinusoidal, continuously varying temperature profiles. LWE adjusted to pH 7.8 was inoculated with approximately 2.5-3.0 log CFU/mL of Salmonella spp., and the growth data at several isothermal conditions (5, 7, 10, 15, 20, 25, 30, 35, 37, 39, 41, 43, 45, and 47 °C) was collected. A primary model (Baranyi model) was fitted for each temperature growth data and corresponding maximum growth rates were estimated. Pseudo-R2 values were greater than 0.97 for primary models. Modified Ratkowsky model was used to fit the secondary model. The pseudo-R2 and root mean square error were 0.99 and 0.06 log CFU/mL, respectively, for the secondary model. A dynamic model for the prediction of Salmonella spp. growth under varying temperature conditions was developed using 4th-order Runge-Kutta method. The developed dynamic model was validated for 2 sinusoidal temperature profiles, 5 to 15 °C (for 600 h) and 10 to 40 °C (for 52 h) with corresponding root mean squared error values of 0.28 and 0.23 log CFU/mL, respectively, between predicted and observed Salmonella spp. populations. The developed dynamic model can be used to predict the growth of Salmonella spp. in LWE under varying temperature conditions. PRACTICAL APPLICATION   Liquid egg and egg products are widely used in food processing and in restaurant operations. These products can be contaminated with Salmonella spp. during breaking and other unit operations during processing. The raw, liquid egg products are stored under refrigeration prior to pasteurization. However, process deviations can occur such as refrigeration failure, leading to temperature fluctuations above the required temperatures as specified in the critical limits within hazard analysis and critical control point plans for the operations. The processors are required to evaluate the potential growth of Salmonella spp. in such products before the product can be used, or further processed. Dynamic predictive models are excellent tools for regulators as well as the processing plant personnel to evaluate the microbiological safety of the product under such conditions.

Novel Radiofrequency-Assisted Thermal Processing Improves the Gelling Properties of Standard Egg White Powder

Effect of radiofrequency (RF)-assisted thermal processing on quality and functional properties of high-foaming standard egg white powder (std. EWP, pH approximately 7.0) was investigated and compared with traditional processing (heat treatment in a hot room at 58 °C for at least 14 d). The RF-assisted thermal treatments were selected to meet the pasteurization requirements and to improve the functional properties of the std. EWP. The treatment conditions were: RF heating to 60, 70, 80, and 90 °C followed by holding in a hot air oven at those temperatures for different periods ranging from 4 h at 90 °C to 72 h at 60 °C. The quality (color and solubility) and functional properties (foaming properties: foaming capacity and foam stability; and gelling properties: water holding capacity and gel-firmness) of the std. EWP were investigated. RF-assisted thermal processing did not affect the color and solubility of std. EWP at any of the treatment conditions. In general, the foaming and gelling properties of RF-assisted thermally processed std. EWP increased with an increase in temperature and treatment duration. The optimal RF-assisted treatment conditions to produce std. EWP with similar functional properties as the traditionally processed (hot room processed) std. EWP were 90 °C for ≥8 h. These optimal conditions were similar to those for high gel egg white powder (HG-EWP, pH approximately 9.5). The RF-assisted thermal pasteurization improved the gelling properties of std. EWP to the levels of HG-EWP, leading to newer applications of this functionally improved safe product. The RF-assisted thermal processing allows the processor to produce a HG-EWP from std. EWP subsequent to processing while simultaneously pasteurizing the product, thus assuring the product safety.