• Journal of the FoodService Safety
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• v.2 no.2
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• pp.91-96
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• 2021

This study was performed to provide fundamental data on hygiene and quality control of ready-to-eat sandwiches. Predictive models were developed to the kinetics of Staphylococcus aureus growth in these sandwiches as a function of temperature (10, 15, 25, and 35℃). The result of the primary model that used the Gompertz equation showed that the lag phase duration (LPD) and generation time (GT) decreased and the exponential growth rate (EGR) increased with increasing storage temperature. The secondary model showed an R² for M and B of 0.9967 and 09916, respectively. A predictive growth model of the growth degree as a function of temperature was developed. L(t)=A+Cexp(-exp(-B(t-M))) (A=Initial contamination level, C=MPD-A, B=0.473166-0.045040*Temp-0.001718*Temp*Temp, M=19.924824-0.627442*Temp-0.004493*Temp*Temp, t=time, Temp=temperature). This model showed an R² value of 0.9288. All the models developed in this study showed a good fit.

• Journal of Environmental Science International
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• v.31 no.9
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• pp.793-801
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• 2022

This study was carried out to provide basic data for logical forest management by developing a site index curve reflecting the current growth characteristics of Cryptomeria japonica stands in Korea. The height growth model was developed using the Chapman-Richards, Schumacher, Gompertz, and Weibull algebraic difference equations, which are widely used in growth estimation, for data collected from 119 plots through the 7th National Forest Inventory and stand survey. The Chapman-Richards equation, with the highest model fit, was selected as the best equation for the height growth model, and a site index curve was developed using the guide curve method. To compare the developed site index curve with that on the yield table, paired T-tests with a significance level of 5% were performed. The results indicated that there were no significant differences between the site index curve values at all ages, and the p-value was smaller after the reference age than before. Therefore, the site index curve developed through this study reflects the characteristics of the changing growth environment of C. japonica stands and can be used in accordance with the site index curve on the current yield table. Thus, this information can be considered valuable as basic data for reasonable forest management.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.25 no.1
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• pp.29-36
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• 1992

This paper deals with the estimation of population ecological parameters, including growth parameters, survival rates, instantaneous coefficient of natural mortality and age at first capture, of the small yellow-croaker, Pseudosciaena Polyactis in Korean waters, which determine fluctuations in stock abundance. For describing the growth of the small yellow croaker, von Bertalanffy growth equation was recommended for the purpose of stock assessment, although the Gompertz model yielded the closest fit. The survival rate (S) of the croaker was estimated to be 0.219 (variance=0.0000262), and the instantaneous coefficient of natural mortality (M) was 0.4 $year^{-1}$. From the estimates of S and M, the instantaneous coefficient of fishing mortality (F) was calculated to be 1.11$year^{-1}$ implying an impact from fishing three times that of natural mortality. Finally, the age at first capture $(t_{c})$ was estimated to be 0.602.

• Journal of People, Plants, and Environment
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• v.24 no.6
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• pp.629-638
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• 2021

Background and objective: This study was conducted to develop diameter growth models for thinned Quercus glauca Thunb. (QGT) stands to inform production goals for treatment and provide the information necessary for the systematic management of this stands. Methods: This study was conducted on QGT stands, of which initial thinning was completed in 2013 to develop a treatment system. To analyze the tree growth and trait response for each thinning treatment, forestry surveys were conducted in 2014 and 2021, and a one-way analysis of variance (ANOVA) was executed. In addition, non-linear least squares regression of the PROC NLIN procedure was used to develop an optimal diameter growth model. Results: Based on growth and trait analyses, the height and height-to-diameter (H/D) ratio were not different according to treatment plot (p > .05). For the diameter of basal height (DBH), the heavy thinning (HT) treatment plot was significantly larger than the control plot (p < .05). As a result of the development of diameter growth models by treatment plot, the mean squared error (MSE) of the Gompertz polymorphic equation (control: 2.2381, light thinning: 0.8478, and heavy thinning: 0.8679) was the lowest in all treatment plots, and the Shapiro-Wilk statistic was found to follow a normal distribution (p > .95), so it was selected as an equation fit for the diameter growth model. Conclusion: The findings of this study provide basic data for the systematic management of Quercus glauca Thunb. stands. It is necessary to construct permanent sample plots (PSP) that consider stand status, location conditions, and climatic environments.

• Food Science and Biotechnology
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• v.15 no.5
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• pp.715-720
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• 2006

This study was performed to develop a predictive model for the growth kinetics of Listeria monocytogenes in tryptic soy broth (TSB) using a response surface model with a combination of potassium lactate (PL), temperature, and pH. The growth parameters, specific growth rate (SGR), and lag time (LT) were obtained by fitting the data into the Gompertz equation and showed high fitness with a correlation coefficient of $R^2{\geq}0.9192$. The polynomial model was identified as an appropriate secondary model for SGR and LT based on the coefficient of determination for the developed model ($R^2\;=\;0.97$ for SGR and $R^2\;=\;0.86$ for LT). The induced values that were calculated using the developed secondary model indicated that the growth kinetics of L. monocytogenes were dependent on storage temperature, pH, and PL. Finally, the predicted model was validated using statistical indicators, such as coefficient of determination, mean square error, bias factor, and accuracy factor. Validation of the model demonstrates that the overall prediction agreed well with the observed data. However, the model developed for SGR showed better predictive ability than the model developed for LT, which can be seen from its statistical validation indices, with the exception of the bias factor ($B_f$ was 0.6 for SGR and 0.97 for LT).

• Journal of Food Hygiene and Safety
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• v.31 no.5
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• pp.342-348
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• 2016

The objective of this study was to compare the change of S. Enteritidis with S. Typhimurium populations in liquid egg products. S. Enteritidis or S. Typhimurium was inoculated into egg white and egg yolk and stored at 8, 10, 15, 25, and $35^{\circ}C$, respectively. In egg white, no growth of S. Enteritidis and S. Typhimurium was observed at 8, 10, 15, and $35^{\circ}C$, while both S. Enteritidis and S. Typhimurium in egg white stored grew more than 1 log CFU/ml after 50 hours storage at $25^{\circ}C$. In egg yolk, there was no growth of S. Enteritidis and S. Typhimurium at $8^{\circ}C$ but growth of both strains was observed at 10, 15, 25, and $35^{\circ}C$. Since growth of S. Enteritidis and S. Typhimurium was only observed in egg yolk, primary growth models for both strains were developed using modified Gompertz equation and then secondary models for lag time (LT), specific growth rate (SGR), and maximum population density (MPD) were developed as a function of temperature. At all temperatures, more rapid growth of S. Enteritidis than S. Typhimurium was observed in egg yolk, indicating the greater risk of S. Enteritidis than S. Typhimurium in egg products. In conclusion, the results indicate that temperature control less than $8^{\circ}C$ is very important to ensure safety of liquid egg products, especially liquid egg yolk.

• Journal of the Korea Organic Resources Recycling Association
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• v.24 no.3
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• pp.75-82
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• 2016

Objective of this experiment was to predict the potential methane production with crop residues at different loading rates. Anaerobic digestion of barley and rapeseed straw substrates for biogas production was performed in Duran bottles at various biomass loading rates with crop residues. Through kinetic model of surface methodology, the methane production was fitted to a Gompertz equation. For the biogas production at mesophilic digestion with crop residues, it was observed that maximum yield was 37.2 and 28.0 mL/g at 6.8 and 7.5 days after digestion with 1% biomass loading rates of barley and rapeseed straws, respectively. For the methane content of mesophilic digestion, there were highest at 61.7% after 5.5 days and 75.0% after 3.4 days of digestion with barley and rapeseed straw on both 5% biomass loading rates, respectively. The maximum methane production potentials were 159.59 mL/g for 1% barley straw and 156.62 mL/g for 3% rapeseed straw at mesophilic digestion. Overall, it would be strongly recommended that biomass loading rate was an optimum rate at mesophilic digestion for using 1% barley and 3% rapeseed straws for feed stocks.

• Journal of Microbiology and Biotechnology
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• v.17 no.4
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• pp.644-649
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• 2007

Response surface model was developed for predicting the growth rates of Salmonella enterica sv. Typhimurium in tryptic soy broth (TSB) medium as a function of combined effects of temperature, pH, and NaCl. The TSB containing six different concentrations of NaCl (0, 2, 4, 6, 8, and 10%) was adjusted to an initial of six different pH levels (pH 4, 5, 6, 7, 8, 9, and 10) and incubated at 10 or $20^{\circ}C$. In all experimental variables, the primary growth curves were well $(r^2=0.900\;to\;0.996)$ fitted to a Gompertz equation to obtain growth rates. The secondary response surface model for natural logarithm transformations of growth rates as a function of combined effects of temperature, pH, and NaCl was obtained by SAS's general linear analysis. The predicted growth rates of the S. Typhimurium were generally decreased by basic (9, 10) or acidic (5, 6) pH levels or increase of NaCl concentrations (0-8%). Response surface model was identified as an appropriate secondary model for growth rates on the basis of coefficient determination $(r^2=0.960)$, mean square error (MSE=0.022), bias factor $(B_f=1.023)$, and accuracy factor $(A_f=1.164)$. Therefore, the developed secondary model proved reliable predictions of the combined effect of temperature, NaCl, and pH on growth rates for S. Typhimurium in TSB medium.

• Journal of Applied Biological Chemistry
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• v.57 no.1
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• pp.83-87
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• 2014

The effects of combined treatment of aqueous chlorine dioxide ($ClO_2$) and fumaric acid on the microbial growth in fresh-cut paprika were investigated. After the combined treatment, the populations of total aerobic bacteria and inoculated Listeria monocytogenes in the paprika sample were reduced by 0.82 and 1.21 log CFU/g, respectively, compared to those of the control. In addition, after 10 d of storage at $10^{\circ}C$, the populations were decreased by 1.21 and 2.10 log CFU/g, respectively. The predictive model for the populations of total aerobic bacteria and L. monocytogenes in the paprika was applied during storage. The prediction equation using Gompertz model was appropriate, based on the statistical analysis such as accuracy factor and bias factor. These results suggest that the combined treatment of aqueous $ClO_2$ and fumaric acid can be an effective technology for microbial decontamination and it can improve microbial safety by decreasing maximum growth rate and increasing lag time of bacteria in the fresh-cut paprika.

• Food Science and Biotechnology
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• v.17 no.3
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• pp.642-650
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• 2008

A mathematical model was developed for predicting the growth rate of Enterobacter sakazakii in tryptic soy broth medium as a function of the combined effects of temperature (5, 10, 20, 30, and $40^{\circ}C$), pH (4, 5, 6, 7, 8, 9, and 10), and the NaCl concentration (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10%). With all experimental variables, the primary models showed a good fit ($R^2=0.8965$ to 0.9994) to a modified Gompertz equation to obtain growth rates. The secondary model was 'In specific growth $rate=-0.38116+(0.01281^*Temp)+(0.07993^*pH)+(0.00618^*NaCl)+(-0.00018^*Temp^2)+(-0.00551^*pH^2)+(-0.00093^*NaCl^2)+(0.00013^*Temp*pH)+(-0.00038^*Temp*NaCl)+(-0.00023^*pH^*NaCl)$'. This model is thought to be appropriate for predicting growth rates on the basis of a correlation coefficient (r) 0.9579, a coefficient of determination ($R^2$) 0.91, a mean square error 0.026, a bias factor 1.03, and an accuracy factor 1.13. Our secondary model provided reliable predictions of growth rates for E. sakazakii in broth with the combined effects of temperature, NaCl concentration, and pH.