• Journal of Biosystems Engineering
• /
• v.37 no.4
• /
• pp.233-244
• /
• 2012

Purpose: The kinetic evaluation was performed for swine manure (SM) degradation and biogas generation. Methods: The SM was anaerobically digested using batch digesters at feed to inoculum ratio (F/I) of 1.0 under mesophilic conditions ($36.5^{\circ}C$). The specific gas yield was expressed in terms of gram total chemical oxygen demand (mL/g TCOD added) and gram volatile solids added (mL/g VS added) and their effectiveness was discussed. The biogas and methane production were predicted using first order kinetic model and the modified Gompertz model. The critical hydraulic retention time for biomass washout was determined using Chen and Hashimoto model. Results: The biogas and methane yield from SM was 346 and 274 mL/ TCOD added, respectively after 100 days of digestion. The average methane content in the biogas produced from SM was 79% and $H_2S$ concentration was in the range of 3000-4108 ppm. It took around 32-47 days for 80-90% of biogas recovery and the TCOD removal from SM was calculated to be 85%. When the specific biogas and methane yield from SM (with very high TVFA concentration) was expressed in terms of oven dried volatile solids (VS) basis, the gas yield was found to be over estimated. The difference in the measured and predicted gas yield was in the range of 1.2-1.5% when using first order kinetic model and 0.1% when using modified Gompertz model. The effective time for biogas production ($T_{Ef}$) from SM was calculated to be in the range of 30-45 days and the critical hydraulic retention time ($HRT_{Critical}$) for biomass wash out was found to be 9.5 days. Conclusions: The modified Gompertz model could be better in predicting biogas and methane production from SM. The HRT greater than 10 days is recommended for continuous digesters using SM as feedstock.

• Journal of Biosystems Engineering
• /
• v.37 no.5
• /
• pp.302-313
• /
• 2012

Purpose: The biogas productivity potential of fish waste (FW) was evaluated. Methods: Batch trials were carried out in 1.3 L glass digesters kept in a temperature controlled chambers at $36.5^{\circ}C$. The first order kinetic model and the modified Gompertz model were evaluated for biogas production. The Chen and Hashimoto model was used to determine the critical hydraulic retention time (HRT $_{Critical}$) for FW under mesophilic conditions. The feasibility of co-digestion of FW with animal manure was studied. Results: The biogas and methane potential of FW was found to be 757 and 554 mL/g VS, respectively. The methane content in the biogas produced from FW was found to be 73% and VS removal was found to be 77%. There was smaller difference between measured and predicted biogas production when using the modified Gompertz model (16.5%) than using first order kinetic model (31%). The time period for 80%-90% of biogas production ($T_{80-90}$) from FW was calculated to be 50.3-53.5 days. Similarly, the HRT $_{Critical}$ for FW was calculated to be 13 days under mesophilic conditions. The methane production from swine manure (SM) and cow manure (CM) digesters could be enhanced by 13%-115% and 17%-152% by mixing 10%-90% of FW with SM and CM, respectively. Conclusions: The FW was found to be highly potential substrate for anaerobic digestion for biogas production. The modified Gompertz model could be more appropriate in describing anaerobic digestion process of FW. It could be promising for co-digestion of FW with animal manure.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.32 no.5
• /
• pp.550-555
• /
• 1999

The growth and spawning time of juvenile Ammodytes personatus were analyzed based on the daily growth increment in otolith reading of the sample caught in the coastal waters of Shinsudo, Sacheon from March 20 to May 1, 1988. Daily growth increment in otolith was formed once a day. The estimated spawning time ranged from November, 1987 to March, 1988. The von Bertalanffy growth model and the Gompertz growth model were expressed as, $TL=87.80(1-e^{-0.0074(t+10.79)})$ and $TL=72.59 e^{-1.8417\;e-0.0152t}$ respectively, where TL is total length in mm, t is age in day.

• Journal of Animal Science and Technology
• /
• v.45 no.4
• /
• pp.509-516
• /
• 2003

Growth curves were estimated for 1083 female Korean cattle raised in Daekwanryeong branch, National Livestock Research Institute (NLRI). Comparisons were made among various growth curve models for goodness of fit for the growth of the cows. Estimated growth curve functions were $W_t=370.2e^{-2.208e^{-0.00327t}$ for Gompertz model, for von Bertalanffy model, and $W_t=341.2(1+5.652e^{-0.00524t})^{-1}$ for Logistic model. Ages at inflection estimated from Gompertz model, von Bertalanffy model and Logistic model were 242.2 days, 191.5 days, and 330.5 days respectively, body weight at inflection were 136kg, 115kg, and 170kg, and daily gain at inflection were 0.445kg, 0.451kg, and 0.446kg. The predicted weights by ages from Gompertz model, von Bertalanffy model, and Logistic model were onsistently overestimated at birth weight and underestimated at 36 month weight. The von Bertalanffy model which had a variable point of inflection fit the data best.

• Journal of the Korean Data and Information Science Society
• /
• v.8 no.2
• /
• pp.153-161
• /
• 1997

A Korean exporience life table(male) is constructed by using a mixture of weighted moving average(WMA) model and Gompertz' parametric survival model based on 25,000,000 insured of major 6 life insurance companies from 1988 to 1992. The graduated values are taken as those which minimize the composite measure of fittness and smoothness. Moreover, we propose closed form estimators for three parameters of Gompertz' model.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.2
• /
• pp.329-335
• /
• 2019

Reliability growth analysis was conducted for a guided weapons system. In the development phase, reliability management activities were continuously carried out by identifying failure modes and causes and analyzing faults found during the testing. The missile system consists of an all-up-round missile and a launcher, and the analysis was carried out according to the test results of each system. The test results for the all-up-round missile were obtained with discrete data, which were success and failure as a one-shot-device. The test results for the launcher were obtained with continuous data by operating the equipment continuously in the test. For each test result, the reliability growth model was applied to the Standard Gompertz model and the Crow-Extended model. The models were used to identify the growth analysis results of the test so far. It was also possible to predict the reliability growth results by assuming the future test results. The study results could be useful in achieving the desired reliability goal and in determining the number of tests. Then, the planned test will be confirmed and the growth analysis of the missile system will continuously be conducted.

• Korean Journal of Weed Science
• /
• v.30 no.1
• /
• pp.50-57
• /
• 2010

This experiment was conducted to investigate seedling emergence of Humulus japonicus in Seoul and Suwon and to predict its seedling emergence in various locations in Korea. Non-linear regression analysis to fit Gompertz model to accumulated seedling emergence of H. japonicus was performed to describe its seedling emergence. Parameter estimates from the non-linear regression and estimated effective accumulated temperature required for its seedling emergence were further used to predict seedling emergence of H. japonicus in 8 major geographical regions of Korea. Seedling emergence of H. japonicus versus effective accumulated temperature was well described by Gompertz model in both Seoul and Suwon. Effective accumulated temperatures required for the first seedling emergence and 50% of the maximum seedling emergence were estimated to be $56.7^{\circ}C$ and $76.3^{\circ}C$, respectively. Therefore, the dates for the first seedling emergence of H. japonicus were predicted to be 21 and 30 March in Daegu and Daejeon, while 4 and 6 April in Suwon and Chuncheon, respectively. The dates reaching 50% of maximum seedling emergence were also predicted to be 25 March in Daegu, while 3, 8 and 9 April in Daejeon, Suwon and Chuncheon, respectively.

• Korean Journal Plant Pathology
• /
• v.14 no.4
• /
• pp.331-338
• /
• 1998

To develop the model for prediction of potato late blight progress, the relationship between severity index of potato late blight transformed by the logit and Gompit transformation function and cumulative severity value (CSV) processing weather data during growing period in Taegwallyeong alpine area, 1975 to 1992 were examined. When logistic model and Gompertz model were compared by determining goodness of fit for progressive degree of late blight using CSV as independent variable, the coefficients of determination were higher as 0.742 in the logistic model than 0.680 in the Gompertz model. Parameters in logistic model were composed of progressive rate and initial value of logistic model. Initial value was calculated in -3.664. The progressive rate of potato late blight was 0.137 in cv. Superior, 0.136 in cv. Irish Cobbler, and 0.070 in cv. Jopung without fungicide sprays. According to in crease of the number of spray times the progressive rate was lowered, was 0.020 in cv. Superior under the conventional program of fungicide sprays, 10 times sprays during cropping season. Equation of progressive rate, b1=0.0088 ACSV-0.033 (R2=0.976), was written by examining the relationship between the parameters of progressive rate of late blight and the average CSV (ACSV) quantifing weather information. By estimating parameters of logistic function, model able to describe the late blight progress of potato, cv. Superior was formulated in Y=4/(1+39.0·exp((0.0088 ACSV-0.033)·CSV).

• Korean Journal Plant Pathology
• /
• v.14 no.2
• /
• pp.150-156
• /
• 1998

To develop a model for prediction of turnip mosaic virus(TuMV) disease progress of Chinese cabbage based on weather information and number of TuMV vector aphids trapped in Taegwallyeong alpine area, data were statistically processed together. As the variables influenced on TuMV disease progress, cumulative portion(CPT) above 13$^{\circ}C$ in daily average temperature was the most significant, and solar radiation, duration of sunshine, vector aphids and cumulative temperature above $0^{\circ}C$ were significant. When logistic model and Gompertz model were compared by detemining goodness of fit for TuMV disease progress using CPT as independent variable, regression coefficient was higher in the logistic model than in the Gompertz model. Epidemic parameters, apparent infection rate and initial value of logistic model, were estimated by examining the relationship between disease proportion linearized by logit transformation equation, In(Y/Yf-Y) and CPT. Models able to describe the progression of TuMV disease were formulated in Y=100/(1+128.4 exp(-0.013.CPT.(-1(1/(1+66.7.exp(-0.11.day). Calculated disease progress from the model was in good agreement with investigated actual disease progress showing high significance of the coefficient of determination with 0.710.

• Journal of the Korean Data Analysis Society
• /
• v.20 no.6
• /
• pp.2721-2731
• /
• 2018

This study purposes to derive the predictive model for the cold tolerance of Brassica napus, using the data collected in the Tree Breeding Lab of Gyeongsang National University during July and August of 2016. Three Brassica napus samples were treated at each of low temperatures from $4^{\circ}C$ to $-12^{\circ}C$ by decrement of $4^{\circ}C$, step by step, and electrolyte leakage levels were measured at each stage. Electrolyte leakages were observed tangibly from $-4^{\circ}C$. We tried to fit the six nonlinear regression models to the electrolyte leakage data of Brassica napus: 3-parameter logistic model, baseline logistic model, 4-parameter logistic model, (4-1)-parameter logistic model, 3-parameter Gompertz model, and (3-1)-parameter Gompertz model. The baseline levels of the electrolyte leakage estimated by these models were 4.81%, 4.07%, 4.19%, 4.07%, 4.55%, and 0%, respectively. The estimated median lethal temperature, LT50, were $-5.87^{\circ}C$, $-6.31^{\circ}C$, $-6.05^{\circ}C$, $-6.35^{\circ}C$, $-4.98^{\circ}C$, and $-5.15^{\circ}C$, respectively. We compared and discussed the measures of goodness of fit to select the appropriate nonlinear regression model.