Korean Journal of Agricultural and Forest Meteorology
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v.8
no.3
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pp.190-198
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2006
Radiation use efficiency (RUE), the amount of biomass produced per unit intercepted photosynthetically active radiation (PAR), constitutes a main part of crop growth simulation models. The objective of the present study was to evaluate the variation of RUE of rice plants under various nitrogen nutritive conditions. from 1998 to 2000, shoot dry weight (DW), intercepted PAR of rice canopies, and nitrogen nutritive status were measured in various nitrogen fertilization regimes using japonica and Tongil-type varieties. These data were used for estimating the average RUEs before heading and the relationship between RUE and the nitrogen nutritive status. The canopy extinction coefficient (K) increased with the growth of rice until maximum tillering stage and maintained constant at about 0.4 from maximum tillering to heading stage, rapidly increasing again after heading stage. The DW growth revealed significant linear correlation with the cumulative PAR interception of the canopy, enabling the estimation of the average RUE before heading with the slopes of the regression lines. Average RUE tended to increase with the increased level of nitrogen fertilization. RUE increased approaching maximum as the nitrogen nutrition index (NNI) calculated by the ratio of actual shoot N concentration to the critical N concentration for the maximum growth at any growth stage and the specific leaf nitrogen $(SLN;\;g/m^2\;leaf\;area)$ increased. This relationship between RUE (g/MJ of PAR) and N nutritive status was expressed well by the following exponential functions: $$RUE=3.13\{1-exp(-4.33NNNI+1.26)\}$$$$RUE=3.17\{1-exp(-1.33SLN+0.04)\}$$ The above equations explained, respectively, about 80% and 75% of the average RUE variation due to varying nitrogen nutritive status of rice plants. However, these equations would have some limitations if incorporated as a component model to simulate the rice growth as they are based on relationships averaged over the entire growth period before heading.
Korean Journal of Agricultural and Forest Meteorology
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v.11
no.2
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pp.72-78
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2009
The demand for rainfall data in gridded digital formats has increased in recent years due to the close linkage between hydrological models and decision support systems using the geographic information system. One of the most widely used tools for digital rainfall mapping is the PRISM (parameter-elevation regressions on independent slopes model) which uses point data (rain gauge stations), a digital elevation model (DEM), and other spatial datasets to generate repeatable estimates of monthly and annual precipitation. In the PRISM, rain gauge stations are assigned with weights that account for other climatically important factors besides elevation, and aspects and the topographic exposure are simulated by dividing the terrain into topographic facets. The size of facet or grid cell resolution is determined by the density of rain gauge stations and a $5{\times}5km$ grid cell is considered as the lowest limit under the situation in Korea. The PRISM algorithms using a 270m DEM for South Korea were implemented in a script language environment (Python) and relevant weights for each 270m grid cell were derived from the monthly data from 432 official rain gauge stations. Weighted monthly precipitation data from at least 5 nearby stations for each grid cell were regressed to the elevation and the selected linear regression equations with the 270m DEM were used to generate a digital precipitation map of South Korea at 270m resolution. Among 1.25 million grid cells, precipitation estimates at 166 cells, where the measurements were made by the Korea Water Corporation rain gauge network, were extracted and the monthly estimation errors were evaluated. An average of 10% reduction in the root mean square error (RMSE) was found for any months with more than 100mm monthly precipitation compared to the RMSE associated with the original 5km PRISM estimates. This modified PRISM may be used for rainfall mapping in rainy season (May to September) at much higher spatial resolution than the original PRISM without losing the data accuracy.
Cho, Wonhee;Lim, Wontaek;Kim, Eun-Sook;Lim, Jong-Hwan;Ko, Dongwook W.
Korean Journal of Agricultural and Forest Meteorology
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v.22
no.3
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pp.215-231
/
2020
Forest landscape models (FLMs) can be used to investigate the complex interactions of various ecological processes and patterns, which makes them useful tools to evaluate how environmental and anthropogenic variables can influence forest ecosystems. However, due to the large spatio-temporal scales in FLMs studies, parameterization and validation can be extremely challenging when applying to new study areas. To address this issue, we focused on the parameterization and application of a spatially explicit forest landscape model, LANDIS-II, to Mt. Gyebang, South Korea, with the use of the National Forest Inventory (NFI) and long-term ecological research (LTER) site data. In this study, we present the followings for the biomass succession extension of LANDIS-II: 1) species-specific and spatial parameters estimation for the biomass succession extension of LANDIS-II, 2) calibration, and 3) application and validation for Mt. Gyebang. For the biomass succession extension, we selected 14 tree species, and parameterized ecoregion map, initial community map, species growth characteristics. We produced ecoregion map using elevation, aspect, and topographic wetness index based on digital elevation model. Initial community map was produced based on NFI and sub-alpine survey data. Tree species growth parameters, such as aboveground net primary production and maximum aboveground biomass, were estimated from PnET-II model based on species physiological factors and environmental variables. Literature data were used to estimate species physiological factors, such as FolN, SLWmax, HalfSat, growing temperature, and shade tolerance. For calibration and validation purposes, we compared species-specific aboveground biomass of model outputs and NFI and sub-alpine survey data and calculated coefficient of determination (R2) and root mean square error (RMSE). The final model performed very well, with 0. 98 R2 and 8. 9 RMSE. This study can serve as a foundation for the use of FLMs to other applications such as comparing alternative forest management scenarios and natural disturbance effects.
The objective of this study is to estimate the shelf-life of Tteokgalbi containing dietary fiber extracted from rice bran by using the predictive microbiology. This Tteokgalbi was made with 0%, 1%, 2%, and 3% dietary fiber. The number of total viable cells, anaerobic, psychrotrophic, and heat-stable bacteria and coliforms was calculated during 15 days of storage under $4{\pm}1^{\circ}C$ and the obtained data was applied to Baranyi function. The evaluation of fitness between predicted and observed data showed that these were matched in a satisfactory way. Heat-stable bacteria was detected lower than <1 log CFU/g and coliforms were not detected during the storage. The changes of total viable cells and psychrotrophic bacteria in Tteokgalbi were increased gradually, but dramatically increased after 3 days of storage. The models of total viable cells and anaerobic bacteria showed very similar growth trends and values of growth parameters each other. The estimated shelf-life of each Tteokgalbi was calculated from the predictive model of total viable cells and the estimated shelf-life was 1.7, 2.3, 2.3, and 2.4 days, respectively. The results suggested that the prediction of bacteria growth could be used to evaluate the microbiological safety and determine the shelf-life of Tteokgalbi as ready-to-eat food in the local market.
Jung, Jin Kyo;Kim, Eun Young;Kim, I Hyeon;Seo, Bo Yoon
Korean journal of applied entomology
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v.59
no.2
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pp.93-107
/
2020
Adults of seven noctuid potential pests (Spodoptera frugiperda, S. litura, S. exigua, Ctenoplusia agnata, Mythimna loreyi, Athetis dissimilis, and A. lepigone) of soybean and maize in Suwon, Korea were identified by their morphological characteristics in the wing pattern and male genitalia and partial mitochondrial DNA sequences of cytochrome c oxidase subunit 1 gene. The generation number of adults that emerge annually in six species (except A. lepigone) was estimated from the data on density fluctuations of adults caught in sex pheromone traps in 2019 and the forecasted data using temperature-associated development and reproduction models for those species. S. frugiperda adults were caught from July 27th to October 31st in 2019, and hence were initially estimated to emerge three times per year. But, it was finally expected that S. frugiperda adults could possibly emerge a total of four times per year in Suwon, considering larval emergence observed during mid- and late June in other areas. Adult emergence of S. litura, S. exigua, C. agnata, and M. loreyi in 2019 was observed from May 29th to November 6th, from May 14th to November 6th, from May 26th to October 25th, and from May 31st to November 23rd, respectively. Annual adult emergence of these four species was estimated as at least four times. Adults of A. dissimilis were caught from May 26th to September 11th in 2019, and adult emergence was estimated at only twice per annum. It was postulated that the first adult populations of five species except the two Athetis species were probably migrated from other areas.
Park, Hyoung-Su;Kim, Min-Young;Jeong, Hyun-Suk;Park, Ki-Hwan;Ryu, Kyung
Journal of the Korean Society of Food Science and Nutrition
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v.38
no.11
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pp.1618-1624
/
2009
This study was conducted to estimate the shelf-life of cooked mung bean sprouts contaminated with Staphylococcus aureus according to storage temperatures after cooking in school foodservice operations. A predictive growth model of S. aureus in cooked mung bean sprouts prepared using a standard recipe was developed at 4 storage temperatures (5, 15, 25, and 35${^{\circ}C}$). To determine the effect of vinegar on the shelf-life of cooked mung bean sprouts, the growth of S. aureus in sprouts prepared using vinegar and the standard recipe were compared. The $R^2$ values of the specific growth rate (SGR) and lag time (LT) determined using the Gompertz model were greater than 0.90 at all temperatures except 5${^{\circ}C}$, which confirmed that it would be appropriate to use these parameters for a secondary model. The secondary model, which indicates changes in LT and SGR values according to storage temperatures, was calculated using response surface models. The compatibility of the developed model was confirmed by calculating $R^2$, Bf, Af and MSE values as statistic parameters. The $R^2$ values of LT and SGR were 0.94 or higher, and the MSE, Bf and Af values were 0.02 and 0.002, 0.97 and 1.03, and 1.31 and 1.10, respectively, with high statistical compatibility. The growth rate of S. aureus was higher when the standard recipe was used than when vinegar was used at all temperatures. Indeed, no growth of S. aureus was observed in mung bean sprouts prepared using vinegar. Based on the model developed, cooked mung bean sprouts prepared using the standard recipe for school foodservice should be stored at 10${^{\circ}C}$ or less. Additionally, sprouts stored at 25 or 35${^{\circ}C}$ should be consumed within 6 or 12 hours after cooking. Finally, the addition of vinegar will prevent the growth of S. aureus in cooked mung bean sprouts.
Kim, Tae-Ho;Rho, Jeong-Hyun;Kim, Young-Il;Oh, Young-Taek
International Journal of Highway Engineering
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v.12
no.4
/
pp.93-100
/
2010
Trip generation is the first step in the conventional four-step model and has great effects on overall demand forecasting, so accuracy really matters at this stage. A linear regression model is widely used as a current trip generation model for such plans as urban transportation and SOC facilities, assuming that the relationship between each socio-economic index and trip generation stays linear. But when rapid urban development or an urban planning structure has changed, socio-economic index data for trip estimation may be lacking to bring many errors in estimated trip. Hence, instead of assuming that a socio-economic index widely used for a general purpose, this study aims to develop a new trip generation model by type based on the market separation for the variables to reflect the characteristics of various zones. The study considered the various characteristics (land use, socio-economic) of zones to enhance the forecasting accuracy of a trip generation model, the first-step in forecasting transportation demands. For a market separation methodology to improve forecasting accuracy, data mining (CART) on the basis of trip generation was used along with a regression analysis. Findings of the study indicated as follows : First, the analysis of zone characteristics using the CART analysis showed that trip production was under the influence of socio-economic factors (men-women relative proportion, age group (22 to 29)), while trip attraction was affected by land use factors (the relative proportion of business facilities) and the socio-economic factor (the relative proportion of third industry workers). Second, model development by type showed as a result that trip generation coefficients revealed 0.977 to 0.987 (trip/person) for "production" 0.692 to 3.256 (trip/person) for "attraction", which brought the necessity for type classifications. Third, a measured verification was conducted, where "production" and "attraction" showed a higher suitability than the existing model. The trip generation model by type developed in this study, therefore, turned out to be superior to the existing one.
The exact estimation of crop evapotranspiration containing reference or potential evapotranspiration is necessary for decision of crop water requirements. This study was carried out for the evaluation and application of various meteorological elements used for the calculation of reference evapotranspiration (RET) by FAO Penman-Monteith (PM) model. Meteorological elements including temperature, net radiation, soil heat flux, albedo, relative humidity, wind speed measured by meteorological instruments are required for RET calculation by FAO PM model. The average of albedo measured for crop growing period was 0.20, ranging from 0.12 to 0.23, and was slightly lower than 0.23. Determinant coefficients by measured albedo and green grass albedo were 0.97, 0.95 and standard errors were 0.74, 0.80 respectively. Usefulness of deductive regression models was admitted. To assess an influence of soil heat flux (G) on FAO PM, RET with G=0 was compared with RETs using G at 5cm soil depth ($G_{5cm}$) and G at surface ($G_{0cm}$). As the results, RET estimated by G=0 was well agreed with RET calculated by measured G. Therefore, estimated net radiation, G=0 and albedo of green grass could be used for RET calculation by FAO PM.
This study was conducted to estimate genetic parameters for reproductive traits using multivariate animal models in Yorkshire breed. For the study, 4,989 records for litter traits collected between the year 2001 and 2005 from Yorkshire pigs in K GGP were used. The effects of environmental factors such as farrowing year, parity, weaning to estrus interval (WEI), and suckling period were statistically significant (p<0.05), but farrowing season was not significant, for reproductive traits. The estimates genetic correlations and phenotypic correlations in total number of born and number of suckling, was shown to highly correlated. The genetic correlations were higher than phenotypic correlation. The estimates of heritabilities for reproductive traits, considering permanent environment effects (PE) were much lower than those obtained when permanent environment effects were not considered (NPE) in the model. The estimates of heritabilities were 0.240 and 0.076 for total number of born and 0.187 and 0.096 for number of suckling in NPE, and PE, respectively. These results itivcate that PE should be considered in the statistical mode to estimate more acco ate breeding values.
Environmental flows in the downstream sections of Yongdam Dam, Wonju Stream Dam, and Hongcheon River were estimated with selected target fish species such as Nigra for the site of Yongdam Dam, Splendidus for the site of Wonju Stream Dam, and Signifer for the site of Hongcheon River by considering endangered and domestic species. Physical habitat analysis was performed to estimate environmental flows for the study sites by applying the Physical Habitat Simulation (PHABSIM) and RIVER2D which combined hydraulic and habitat models. Based on the monitored data for ecological environment, the Habitat Suitability Index (HSI) for the target species was estimated by applying the Instream Flow and Aquatic Systems Group (IFASG). In particular, based on the result of fish monitoring, the HSI for each stage of the growth for target species was analyzed. As a result, the Weighted Usable Area (WUA) was maximized at $4.9m^3/s$ of flow discharge during spawning, $5.8m^3/s$ during the period of juvenile, and $8.9m^3/s$ during the adult fish season at the downstream section of Yongdam Dam. The result of the Wonju Stream Dam showed an optimal environmental flow of $0.4m^3/s$, $1.0m^3/s$, and $1.5m^3/s$ during the period of spawning, juvenile, and adult. The habitat analysis for the site of Hongcheon River, which is a non-regulated stream, produced an optimum environmental flow of $5m^3/s$ in the spawning period, $4m^3/s$ in the juvenile stage and $6m^3/s$ in the adult stage.
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