• Food Science and Preservation
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• v.30 no.4
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• pp.573-588
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• 2023

The purpose of this study was to monitor changes in the quality of ginseng and predict its shelf-life. As the storage period of ginseng increased, some quality indicators, such as water-soluble pectin (WSP), CDTA-soluble pectin (CSP), cellulose, weight loss, and microbial growth increased, while others (Na₂CO₃-soluble pectin/NSP, hemicellulose, starch, and firmness) decreased. Principal component analysis (PCA) was performed using the quality attribute data and the principal component 1 (PC1) scores extracted from the PCA results were applied to the multivariate analysis. The reaction rate at different temperatures and the temperature dependence of the reaction rate were determined using kinetic and Arrhenius models, respectively. Among the kinetic models, zeroth-order models with cellulose and a PC1 score provided an adequate fit for reaction rate estimation. Hence, the prediction model was constructed by applying the cellulose and PC1 scores to the zeroth-order kinetic and Arrhenius models. The prediction model with PC1 score showed higher R² values (0.877-0.919) than those of cellulose (0.797-0.863), indicating that multivariate analysis using PC1 score is more accurate for the shelf-life prediction of ginseng. The predicted shelf-life using the multivariate accelerated shelf-life test at 5, 20, and 35℃ was 40, 16, and 7 days, respectively.

• Journal of the Korea Safety Management & Science
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• v.26 no.1
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• pp.39-44
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• 2024

In order to prevent accidents via defective ammunition, this paper analyzes recent research on ammunition life prediction methodology. This workanalyzes current shelf-life prediction approaches by comparing the pros and cons of physical modeling, accelerated testing, and statistical analysis-based prediction techniques. Physical modeling-based prediction demonstrates its usefulness in understanding the physical properties and interactions of ammunition. Accelerated testing-based prediction is useful in quickly verifying the reliability and safety of ammunition. Additionally, statistical analysis-based prediction is emphasized for its ability to make decisions based on data. This paper aims to contribute to the early detection of defective ammunition by analyzing ammunition life prediction methodology hereby reducing defective ammunition accidents. In order to prepare not only Korean domestic war situation but also the international affairs from Eastern Europe and Mid East countries, it is very important to enhance the stability of organizations using ammunition and reduce costs of potential accidents.

• Journal of Korean Society for Quality Management
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• v.35 no.2
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• pp.45-52
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• 2007

The danger of self-ignition of single base propellants will increase with time. Therefore, a good prediction of the safe storage time is very important. In order to determine the remaining shelf-life of the propellants, the content of stabilizer is determined. The propellants stored under normal storage conditions about 10 to 18 years were investigated and accelerated aging test was carried out by storing propellant sample at higher temperature. Finally, we analyzed the results by various methods in order to show the best way to predict the realistic shelf-life. The safe storage life of the propellants will be 24 years, at least 15 years. In case of applying Arrhenius's law, using the reaction rate constant at 28$^{\circ}C$ to 30$^{\circ}C$ to predict the shelf-life by accelerated aging test is reasonable for a good prediction.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.5
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• pp.832-836
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• 2013

To develop a predictive model for the shelf-life of fish cake, fish cake was stored at 30, 35, or $40^{\circ}C$ and populations of total aerobic bacteria were determined during storage. Gompertz model parameters were determined and their dependence on temperature formulated as a quadratic equation for applications toward shelf-life prediction. The predicted shelf-life values for fish cake used in this study were 6.9, 5.5, and 3.8 days at 0, 4, and $10^{\circ}C$, respectively. The shelf-life prediction equation was appropriate based on statistical analyses that reveal accuracy and bias factors. These results suggest that our prediction model is applicable for estimating the shelf-life of fish cake.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.4 no.1
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• pp.23-32
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• 1997

The change in moisture content of moisture sensitive products in moisture-semipermeable packages was investigated for the purpose of predicting the shelf life of a product-package combination. A mathematical model, and a computer program based on the physiochemical properties of the product and the moisture permeability of the package was developed. The moisture content for products in moisture-semipermeable packages was determined under various environmental conditions and the results were compared with the predicted values by means of the simulation model. These experimental studies demonstrated that the prediction of the change in moisture content of packaged products over time by the simulation model is accurate, within a practical range of temperature and relative humidity values. The developed semi-empirical model is considered to have applications in industry, since it provides product shelf life information for a range of temperature and relative humidity conditions, with a limited number of experimentally obtained data points.

• Journal of Food Hygiene and Safety
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• v.11 no.3
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• pp.189-196
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• 1996

Based on microbiological-chemical test results under simulated time-temperature conditions, total plate count, coliform, and volatile basic nitrogen were selected as effective quality indicators for estimating probable shelf-life on Kim Pab dosirak marketed in convenience stores, and shelf-life at each storage temperature was calculated from regression equation between effective quality indicator standard limit and storage time. Estimated shelf lives of Kim Pab Dosirak were 17, 3 and 2 hours respectively under 1$0^{\circ}C$, 2$0^{\circ}C$ and 3$0^{\circ}C$. Because shelf-life was especially affected by intial values, regression analysis between initial effective quality indicator values and storage hours was performed for the estimation of probable shelf-life on Kim Pab during storage at 10, 20, or 3$0^{\circ}C$.

• Food Science of Animal Resources
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• v.39 no.6
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• pp.903-917
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• 2019

This study aimed to extend the shelf-life of coffee-containing milk beverage by adding Theobroma cacao (cacao nibs) extract. To prepare the beverage sample containing cacao nibs extract, 0.8% cacao nibs hydrothermal extract was aseptically injected. Qualitative changes in the beverage samples, including antioxidant effect, peroxide value (POV), caffeine content, and sensory parameters were monitored regularly during storage at 10℃, 20℃, and 30℃ for 4 wk. The inclusion of cacao nibs extract produced higher antioxidant activity compared to the control. As the storage temperature increased, the POV of all samples increased. Samples with cacao nibs extract generally displayed lower POV than the control. The caffeine content of all samples tended to decrease during storage, with the decrease accentuated by higher storage temperatures. In the shelf-life prediction using the Arrhenius model, the kinetic regressions of the cacao nibs extract-added sample and control were Y_POV=1.2212X-2.1141 (r²=0.9713) and Y_POV=1.8075X-2.0189 (r²=0.9883), respectively. Finally, the predicted shelf-life of cacao nibs-added group and control to reach the quality limit (20 meq/kg POV) were approximately 18.11 and 12.18 wk, respectively. The results collectively indicate that the addition of cacao nibs extract extends the shelf-life of the coffee-containing milk beverage and heightened the antioxidant effect.

• Journal of the military operations research society of Korea
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• v.37 no.1
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• pp.39-48
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• 2011

To predict the shelf-life of ammunition stockpiled in intermediate have practical meaning as a core value of combat support. This research is to Predict the shelf-life of ammunition by applying time series analysis based on report from ASRP of the 155mm, KD541 performed for 6 years. This study applied time series analysis using 'Mini-tab program' to measure the amount of stabilizer as time passes by is different from the other one that uses regression analysis. The average shelf-life of KD541 drawn by time series analysis was 43 years and the lowest shelf-life assessed on the 95% confidence level was 35 years.

• Korean Journal of Food Science and Technology
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• v.24 no.2
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• pp.122-126
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• 1992

The shelf-life of wrapped chewing gum(7 sticks) under the climate condition of Seoul was predicted by using moisture gain equation to reach safe moisture limits of 3.16% (dry basis). The overall water vapor permeability of multilayer packaging material was about 0.00045g water/pack day mmHg. The water activity of chewing gum at any temperature was predictable using Clausius-Clapeyron equation. The most significant loss of shelf-life was occurred between June and July, and most products reached the end of shelf-life at July and August. The product which were made in October and November had the longest shelf-life as seven months.

• Journal of the Korea Safety Management & Science
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• v.26 no.3
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• pp.1-9
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• 2024

This study aims to develop a regression model using data from the Ammunition Stockpile Reliability Program (ASRP) to predict the shelf life of 81mm mortar high-explosive shells. Ammunition is a single-use item that is discarded after use, and its quality is managed through sampling inspections. In particular, shelf life is closely related to the performance of the propellant. This research seeks to predict the shelf life of ammunition using a regression model. The experiment was conducted using 107 ASRP data points. The dependent variable was 'Storage Period', while the independent variables were 'Mean Ammunition Velocity,' 'Standard Deviation of Mean Ammunition Velocity,' and 'Stabilizer'. The explanatory power of the regression model was an R-squared value of 0.662. The results indicated that it takes approximately 55 years for the storage grade to change from A to C and about 62 years to change from C to D. The proposed model enhances the reliability of ammunition management, prevents unnecessary disposal, and contributes to the efficient use of defense resources. However, the model's explanatory power is somewhat limited due to the small dataset. Future research is expected to improve the model with additional data collection. Expanding the research to other types of ammunition may further aid in improving the military's ammunition management system.