• Korean journal of applied entomology
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• v.44 no.3 s.140
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• pp.231-235
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• 2005

This study was conducted to obtain the optimal spray time for Pseudaulacaspis prunicota (Maskell) (Homoptera: Diaspididae) in early seaon in Jeju. Oviposition time of overwintered females and activity of hatched nymphs of P. prunicola were monitored, and the phenology data were compared with the outputs estimated by a degree-days model of P. pentagona (Targioni-Tozzetti)). Overwintered females of P. prunicola began to lay eggs from mid to late April, and the eggs started to hatch from early May followed by the active migration of the hatched nymphs during mid May. The phenological events of P. prunicola in early season were likely comparable with those of P. pentagona reported in southern Korea and in central Japan. A degree-day model, which predicts the proportion of >50% hatched egg batches of P. pentagona (y=1[exp(-(-a+bx))]; y, proportion; x, degree-days based on $10.5^{\circ}C$ from 1 January; a=-18.80 and b=0.073), accurately described the migration time of P. prunicola hatched nymphs. Thus, it is considered that the degree-day model can be used for predicting the optimal spray time for P. prunicola in early season.

• Korean Journal of Remote Sensing
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• v.20 no.3
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• pp.175-188
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• 2004

The objectives of this study were to estimate leaf area index (LAI) as a function of image-derived vegetation indices, and to compare measured and estimated LAI to the results of crop model simulation. Soil moisture, crop phenology, and LAI data were obtained several times during the 2001 growing season at monitoring sites established in two central Missouri experimental fields, one planted to com (Zea mays L.) and the other planted to soybean (Glycine max L.). Hyper- and multi-spectral images at varying spatial. and spectral resolutions were acquired from both airborne and satellite platforms, and data were extracted to calculate standard vegetative indices (normalized difference vegetative index, NDVI; ratio vegetative index, RVI; and soil-adjusted vegetative index, SAVI). When comparing these three indices, regressions for measured LAI were of similar quality $(r^2$ =0.59 to 0.61 for com; $r^2$ =0.66 to 0.68 for soybean) in this single-year dataset. CERES(Crop Environment Resource Synthesis)-Maize and CROPGRO-Soybean models were calibrated to measured soil moisture and yield data and used to simulate LAI over the growing season. The CERES-Maize model over-predicted LAI at all corn monitoring sites. Simulated LAI from CROPGRO-Soybean was similar to observed and image-estimated LA! for most soybean monitoring sites. These results suggest crop growth model predictions might be improved by incorporating image-estimated LAI. Greater improvements might be expected with com than with soybean.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.199-199
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• 2017

Sustainable wheat production is of paramount importance for attaining/maintaining the food self-sufficiency status of the rapidly growing nation of Pakistan. However, the average wheat yield per unit area has been dwindling in recent years and the climate-induced variations in rainfall patterns and temperature regimes, during the wheat growth period, are believed to be the reason behind this decline. Crop growth simulation models are powerful tools capable of playing pivotal role in evaluating the climate change impacts on crop yield or productivity. This study was aimed to predict the plausible variations in the wheat yield for future climatic trends so that possible mitigation strategies could be explored. For this purpose, Aquacrop model v. 4.0 was employed to simulate the wheat yield under present and future climatology of the largest agricultural province of Punjab in Pakistan. The data related to crop phenology, management and yield were collected from the experimental plots to calibrate and validate the model. The future climate projections were statistically downscaled from five general circulation models (GCMs) and compared with the base line climate from 1980 to 2010. The model was fed with the projected climate to simulate the wheat yield based on the RCP (representative concentration pathways) 4.5 and 8.5. Under the worst, most likely future scenario of temperature rise and rainfall reduction, the crop yield decreased and water footprint, especially blue, increased, owing to the elevated irrigation demands due to accelerated evapotranspiration rates. The modeling results provided in this study are expected to provide a basic framework for devising policy responses to minimize the climate change impacts on wheat production in the area.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.4
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• pp.282-290
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• 2013

Biophysical and biochemical processes through which crops interact with the atmosphere have been simulated using land surface models and crop growth models. The Noah Multi Physics (MP) model and the CERES-Rice model, which are a land surface model, and a crop growth model, respectively, were used to simulate and compare rice growth and evapotranspiration (ET) in the areas near Haenam flux tower in Korea. Simulations using these models were performed from 2003 to 2012 during which flux measurements were obtained at the Haenam site. The Noah MP model failed to simulate the pattern of temporal change in leaf area index (LAI) after heading. The simulated aboveground biomass with the Noah MP model was underestimated by about 10% of the actual biomass. The ET simulated with the Noah MP model was as low as 21% of those with the CERES-Rice model. In comparison with actual ET measured at Haenam flux site, the root mean square error (RMSE) of the Noah MP model was 1.8 times larger than that of the CERES-Rice model. The Noah MP model seems to show less reliable simulation of crop growth and ET due to simplified phenology processes and assimilates partitioning compared with the CERES-Rice model. When ET was adjusted by the ratio between leaf biomass simulated using CERES-Rice model and Noah MP model, however, the RMSE of ET was reduced by 30%. This suggests that an improvement of the Noah MP model in representing rice growth in paddy fields would allow more reliable simulation of matter and energy fluxes.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.277-283
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• 2018

The crop growth model has been widely used for climate change impact assessment. Crop growth model require genetic coefficients for simulating growth and yield. In order to determine the genetic coefficients, regional growth monitoring data or yield trial data of crops has been used to calibrate crop growth model. The aim of this study is to verify that yield trial data of corn is appropriate to calibrate genetic coefficients of CERES-MAIZE. Field experiment sites were Suwon, Jinju, Daegu and Changwon. The distance from the weather station to the experimental field were from 1.3km to 27km. Genetic coefficients calibrated by yield trial data showed good performance in silking day. The genetic coefficients associated with silking are determined only by temperature. In CERES-MAIZE model, precipitation or irrigation does not have a significant effect on phenology related genetic coefficients. Although the effective distance of the temperature could vary depending on the terrain, reliable genetic coefficients were obtained in this study even when a weather observation site was within a maximum of 27 km. Therefore, it is possible to estimate the genetic coefficients by yield trial data in study area. However, the yield-related genetic coefficients did not show good results. These results were caused by simulating the water stress without accurate information on irrigation or rainfall. The yield trial reports have not had accurate information on irrigation timing and volume. In order to obtain significant precipitation data, the distance between experimental field and weather station should be closer to that of the temperature measurement. However, the experimental fields in this study was not close enough to the weather station. Therefore, When determining the genetic coefficients of regional corn yield trial data, it may be appropriate to calibrate only genetic coefficients related to phenology.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.2
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• pp.61-71
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• 2009

Most deciduous trees in temperate zone are dormant during the winter to overcome cold and dry environment. Dormancy of deciduous fruit trees is usually separated into a period of rest by physiological conditions and a period of quiescence by unfavorable environmental conditions. Inconsistent and fewer budburst in pear orchards has been reported recently in South Korea and Japan and the insufficient chilling due to warmer winters is suspected to play a role. An accurate prediction of the flowering time under the climate change scenarios may be critical to the planning of adaptation strategy for the pear industry in the future. However, existing methods for the prediction of budburst depend on the spring temperature, neglecting potential effects of warmer winters on the rest release and subsequent budburst. We adapted a dormancy clock model which uses daily temperature data to calculate the thermal time for simulating winter phenology of deciduous trees and tested the feasibility of this model in predicting budburst and flowering of Niitaka pear, one of the favorite cultivars in Korea. In order to derive the model parameter values suitable for Niitaka, the mean time for the rest release was estimated by observing budburst of field collected twigs in a controlled environment. The thermal time (in chill-days) was calculated and accumulated by a predefined temperature range from fall harvest until the chilling requirement (maximum accumulated chill-days in a negative number) is met. The chilling requirement is then offset by anti-chill days (in positive numbers) until the accumulated chill-days become null, which is assumed to be the budburst date. Calculations were repeated with arbitrary threshold temperatures from $4^{\circ}C$ to $10^{\circ}C$ (at an interval of 0.1), and a set of threshold temperature and chilling requirement was selected when the estimated budburst date coincides with the field observation. A heating requirement (in accumulation of anti-chill days since budburst) for flowering was also determined from an experiment based on historical observations. The dormancy clock model optimized with the selected parameter values was used to predict flowering of Niitaka pear grown in Suwon for the recent 9 years. The predicted dates for full bloom were within the range of the observed dates with 1.9 days of root mean square error.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.4
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• pp.246-251
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• 2017

Crop models have been used to predict a heading date for efficient management of fertilizer application. Recently, the ORYZA (v3) model was developed to improve the ORYZA2000 model, which has been used for simulation of rice growth in Korea. Still, little effort has been made to assess applicability of the ORYZA (v3) model to rice farms in Korea. The objective of this study was to evaluate reliability of heading dates predicted using the the ORYZA (v3) model, which would indicate applicability of the model to a decision support system for fertilizer application. Field experiments were conducted from 2015-2016 at the Rural Development Administration (RDA) to obtain rice phenology data. Shindongjin cultivar which is mid-late maturity type was grown under a conventional fertilizer management, e.g., application of fertilizer at the rate of 11 Kg N/10a. Another set of heading dates was obtained from annual reports at experiment farms operated by the National Institute of Crop Science and Agricultural Technology Centers in each province. The input files for the ORYZA (v3) model were prepared using weather and soil data collected from the Korean Meteorology Administration (KMA) and the Korean Soil Information System, respectively. Input parameters for crop management, e.g., transplanting date and planting density, were set to represent management used for the field experiment. The ORYZA (v3) model predicted heading date within 1 day for two seasons. The crop model also had a relatively small error in prediction of heading date for three ecotypes of rice cultivars at experiment farms where weather input data were obtained from a near-by weather station. Those results suggested that the ORYZA (v3) model would be useful for development of a decision support system for fertilizer application when reliable input data for weather variables become available.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.343-348
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• 2014

We developed a simple model to predict emergence time and emergence rate of southern type garlic using the daily mean temperature. Emergence rate of garlic was decreased and emergence time was delayed on higher temperature than optimum temperature of $12.7^{\circ}C$. In the model, firstly daily emergence rate was calculated using a beta function to input daily mean temperature, then the percentage of garlic emergence was calculated using a nonlinear model with accumulated emergence rate. The model was good to describe the experimental data of growth cabinet. Also it can explain well the experimental data using temperature gradient tunnel, designed for verification of model performance. But there are 5 days of deviation between estimated and measured time of garlic emergence on the field experiment. More research is needed to develop an advanced model considering other factors, such as soil moisture.

• Korean Journal of Agricultural and Forest Meteorology
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• v.1 no.1
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• pp.12-19
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• 1999

CERES-rice, a rice growth simulation model, was used in conjunction with daily weather data to figure out the spatial variation of the phenology and yields of paddy rice at 168 rice cultivation zone units(CZU) of Kyunggi Province in 1997. Two sets of cultivar specific coefficients, which represent early and mid-season maturing varieties, were derived from field experiments conducted at two crop experiment stations. The minimum data set to run the model for each CZU (daily maximum and minimum temperature, solar irradiance, and rainfall) was obtained by spatial averaging of existing 'Digital Map of Korean Climate'(Shin et al., 1999). Soil characteristics and management information at each CZU were available from the Rural Development Administration. According to a preliminary test using 5 to 9 years field data, trends of the phasic development(heading and physiological maturity), which were obtained from the model adjusted for these coefficients, were in good agreement with the observed data. However, the simulated inter-annual variation was somewhat greater than the reported variation. Rough rice yields of the early maturing cultivar calculated by the model were comparable with the reported data in terms of both absolute value and inter -annual variation. But those of the mid season cultivar showed overestimation. After running the simulation model runs with 1997 weather data for 168 CZU's, rough rice yields of the 168 CZU's calculated by the model were aggregated into corresponding 33 counties by acreage-weighting to facilitate direct comparison with the reported statistics from the Ministry of Agriculture and Forestry. The simulation results were good at 22 out of the 26 counties with reportedly increasing yield trend with respect to the past 9 years average.

• Korean journal of applied entomology
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• v.35 no.2
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• pp.119-125
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• 1996

Temperature-dependent development study for overwintered eggs of Pseudococcus comstocki (Kuwana) wasconducted to develop a forecasting model for egg hatch date. Hatch times of overwintered eggs were comparedat five constant temperatures (10, 15, 20, 25, 27$^{\circ}$C) and different collection dates. A nonlinear, four-parameterdevelopmental model with high temperature inhibition accurately described (R2=0.9948) mean developmentalrates of all temperatures. Variation in developmental times was modeled(~~=0.972w9)it h a cumulative Weibullfunction. Least-squares linear regression (rate=O.O06358[Temp.]-0.07566)d escribed development in the linearregion (15-25$^{\circ}$C) of the development curve. The low development threshold temperature was estimated 11.9"Cand 154.14 degree-days were required for complete development. The linear degree-day model (thermal summation)and rate summation model (Wagner et al. 1985) were validated using field phenology data. In degreedaymodels, mean-minus-base method, sine wave method, and rectangle method were used in estimation of dailythermal units. Mean-minus-base method was 18 to 28d late, sine wave method was 11 to 14d late, rectanglemethod was 3 to 5d late, and rate summation model was 2 to 3d late in predicting 50% hatch of overwinteredeggs. hatch of overwintered eggs.