• Journal of The Korean Society of Grassland and Forage Science
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• v.16 no.4
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• pp.291-298
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• 1996

This study was carried out at Crop Experiment Station in 1993 and 1994. The objective of this study was finding out variation of growth and yield of corn according to maturity. Hybrids of corn used in this study were early maturing corn Comet80, Elite90, Royaldent IOOT, Royaldent T$\times$llO, P3525, P3394, medium maturing corn Royaldent 120T. and late maturing corn Jungbuok, P3144W. G4743. Stalk height, leaf number, ear weight, stover weight, and TDN yield of early maturing corn were linearly increased with prolonged maturity in 1993 growing season. Leaf number, and stover weight of early and late maturing corn were linearly increased with prolonged maturity in 1994 growing season. But ear weight of late manuring corn was not increased as much as that of early manuring corn with prolonged maturity. Increase of total DM and TDN yield of late maturing corn was due to stover weight increase compared with ear weight increase of early maturing corn. Leaf number and stover weight were highly correlated with silk (Growing Degree Days) GDD.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2001.06a
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• pp.101-104
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• 2001

작물 발육단계의 정확한 진단은 그 시기의 생리적 반응을 이해하고 정확하고 정밀한 생육관리를 위해서 절대적으로 필요한 요소이다. 지금까지 벼의 발육단계 예측을 위한 모델에는 GDD를 이용하는 방법(이, 1972), 한 단계의 발육을 완료하는데 걸리는 기간(t)과 이 기간중의 평균기온, 평균일장의 단순회귀 또는 중회귀를 구하는 방법(Gao et al, 1989; Yin et al, 1995; 임, 1982), 평균발육속도(1/t)를 이 기간중의 평균온도와 평균일장의 함수로 표현해서 이를 적산하여 1이 되었을 때를 발육완료일로 나타내는 방법(이, 1987; 신 등, 2000), 발육기간이 시계열자료를 모두 고려하여 함수를 이용하지 않는 non-parametric 방법(이, 1991) 등이 있다.(중략)

• KOREAN JOURNAL OF CROP SCIENCE
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• v.59 no.3
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• pp.299-306
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• 2014

Fresh edible sweet corns demand relatively short period to harvest fresh ears, which can allow farmers to make a choice sweet corns for various cropping systems. For this reason, we were to find the optimum planting date of late-planted sweet corns to sell fresh ears in the autumn linked to cropping system with winter crops, investigating yield and properties of marketable fresh ears and growth traits of sweet corns (cv. 'Godangok' and cv. 'Guseulok') depending on planting dates such as 10 July, 20 July, and 30 July in Suwon 2012 and 2013, respectively. The 20 July-planted sweet corns showed the most fresh ear yield. However, the 10 July-planted and the 30 July-planted had 32% less yield caused by consecutive rainfall from 10 July through 20 July, and 15% less yield due to low air temperature during ripening than the 20 July-planted, respectively. The 10 and 20 July-planted sweet corns had average 140g of a fresh ear weight and 15% heavier ear than the 30 July-planted. For the July-planted sweet corns, silking days after planting ($r=-0.80^{**}$), and harvesting days after silking ($r=-0.97^{**}$) and planting ($r=-0.91^{**}$) were highly negatively correlated with daily mean air temperature during the period, resulting in it takes 1,100 growing degree days (GDD) to harvest fresh ears from the July-planted sweet corns. The fresh ears of the 20 July-planted sweet corns are able to be harvested by early October. Therefore it will be a good choice for the cropping system based on winter vegetable cash crops such as temperate garlic and onion with medium or late maturity. Among three planting dates 20 July-planted sweet corns had the best field performance in every year considering fresh ear yield, ear size, and stability to grow.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.427-435
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• 2023

Changes in flowering time due to weather fluctuations impact plant growth and ecosystem dynamics. Accurate prediction of flowering timing is crucial for effective forest ecosystem management. This study uses a process-based model to predict flowering timing in 2023 for five major tree species in Korean forests. Models are developed based on nine years (2009-2017) of flowering data for Abeliophyllum distichum, Robinia pseudoacacia, Rhododendron schlippenbachii, Rhododendron yedoense f. poukhanense, and Sorbus commixta, distributed across 28 regions in the country, including mountains. Weather data from the Automatic Mountain Meteorology Observation System (AMOS) and the Korea Meteorological Administration (KMA) are utilized as inputs for the models. The Single Triangle Degree Days (STDD) and Growing Degree Days (GDD) models, known for their superior performance, are employed to predict flowering dates. Daily temperature readings at a 1 km spatial resolution are obtained by merging AMOS and KMA data. To improve prediction accuracy nationwide, random forest machine learning is used to generate region-specific correction coefficients. Applying these coefficients results in minimal prediction errors, particularly for Abeliophyllum distichum, Robinia pseudoacacia, and Rhododendron schlippenbachii, with root mean square errors (RMSEs) of 1.2, 0.6, and 1.2 days, respectively. Model performance is evaluated using ten random sampling tests per species, selecting the model with the highest R². The models with applied correction coefficients achieve R² values ranging from 0.07 to 0.7, except for Sorbus commixta, and exhibit a final explanatory power of 0.75-0.9. This study provides valuable insights into seasonal changes in plant phenology, aiding in identifying honey harvesting seasons affected by abnormal weather conditions, such as those of Robinia pseudoacacia. Detailed information on flowering timing for various plant species and regions enhances understanding of the climate-plant phenology relationship.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.3
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• pp.252-261
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• 2018

This study was conducted to develop a method to generate daily maximum and minimum temperatures using monthly data. We analyzed 30-year daily weather data of the 23 meteorological stations in South Korea and elucidated the parameters for predicting annual trend (center value ($\hat{U}$), amplitude (C), deviation (T)) and daily fluctuation (A, B) of daily maximum and minimum temperature. We use national average values for C, T, A and B parameters, but the center value is derived from the annual average data on each stations. First, daily weather data were generated according to the occurrence of rainfall, then calibrated using monthly data, and finally, daily maximum and minimum daily temperatures were generated. With this method, we could generate daily weather data with more than 95% similar distribution to recorded data for all 23 stations. In addition, this method was able to generate Growing Degree Day(GDD) similar to the past data, and it could be applied to areas not subject to survey. This method is useful for generating daily data in case of having monthly data such as climate change scenarios.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.273-277
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• 2010

This research was performed to examine changes in the timing of the growth of crops along with changes in temperatures due tochanges and to analyze the change of water-supply-reliability by adding an analysis of the change of agricultural water supply patterns in the basin area of Miryang dam in Korea. Had-CM3 model from U.K. was the tool adopted for the GCM model, a stochastic, daily-meteorology-generation-model called LARS-WG was alsoused for downscaling and for the climate change scenario (A1B) which represents Korea's circumstances best. First of all, to calculate changes in the timing of the growth of crops during this period, the theory of GDD was applied. Except for the period of transplanting and irrigation, there was no choice but to find the proper accumulated temperature by comparing actual temperature data and the supply pattern of agricultural use due to limited temperature data. As a result, proper temperatures were found for each period. $400^{\circ}C$ for the preparation period of a nursery bed, $704^{\circ}C$ for a nursery bed's period, $1,295^{\circ}C$ for the rice-transplanting period, $1,744^{\circ}C$ for starting irrigation, and $3,972^{\circ}C$ for finishing irrigation. To analyze future agricultural supply patter changes, the A1B scenario of Had-CM3 model was adopted, and then Downscaling was conducted adopting LARS-WG. To conduct a stochastical analysis of LARS-WG, climate scenarios were generated for the periods 2011~2030, 2046~2065, 2080~2099 using the data of precipitation andMax/Min temperatures collected from the Miryang gauging station. Upon reviewing the result of the analysis of accumulated temperatures from 2011~2030, the supply of agricultural water was 10 days earlier, and in the next periods-2046~2065, 2080~2099 it also was 10 days earlier. With these results, it is assumed that the supply of agricultural water should be about 1 month ahead of the existing schedule to meet the proper growth conditions of crops. From the results of the agricultural water supply patterns should be altered, but the reliability of water supply becomes more favorable, which is caused from the high precipitation change. Furthermore, since the unique characteristics of precipitation in Korea, which has high precipitation in the summer, water-supply-reliability has a pattern that the precipitation in September could significantly affect the chances of drought the following winter and spring. It could be more risky to make changes to the constant supply pattern under these conditions due to the high uncertainty of future precipitation. Although, several researches have been conducted concerning climate changes, in the field of water-industry, those researches have been solely dependent on precipitation. Even so, with the high uncertainty of precipitation, it is difficult for it to be reflected in government policy. Therefore, research in the field of water-supply-patterns or evapotranspiration according to the temperature or other diverse effects, which has higher reliability on anticipation, could obtain more reliable results in the future and that could result in water-resource maintenance to be safer and a more advantageous environment.

• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.1
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• pp.47-55
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• 2021

The objective of this study was to access the effect of climate and soil factors on alfalfa dry matter yield (DMY) by the contribution through constructing the yield prediction model in a general linear model considering climate and soil physical variables. The processes of constructing the yield prediction model for alfalfa was performed in sequence of data collection of alfalfa yield, meteorological and soil, preparation, statistical analysis, and model construction. The alfalfa yield prediction model used a multiple regression analysis to select the climate variables which are quantitative data and a general linear model considering the selected climate variables and soil physical variables which are qualitative data. As a result, the growth degree days(GDD) and growing days(GD), and the clay content(CC) were selected as the climate and soil physical variables that affect alfalfa DMY, respectively. The contributions of climate and soil factors affecting alfalfa DMY were 32% (GDD, 21%, GD 11%) and 63%, respectively. Therefore, this study indicates that the soil factor more contributes to alfalfa DMY than climate factor. However, for examming the correct contribution, the factors such as other climate and soil factors, and the cultivation technology factors which were not treated in this study should be considered as a factor in the model for future study.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.1
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• pp.1-12
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• 2022

Tilia amurensis is an important honey plant. As T. amurensis mainly distributes mountainous area with various elevations in Korea, accurate prediction of blooming time at the different elevation would benefit forest beekeepers. In this study, we measured time-dependent blooming progress of T. amurensis in Mt. Gariwang area ranging from 500-1500m. Additionally we collected blooming data from web and published literatures and estimated the variation of blooming time relative to the geographic locations. Flowers began to bloom from July 6 to July 22 with full blooming on July 14 in location where elevation is 638m in Mt. G ariwang area in 2021. Based on these databases, a growing degree day (G DD) model was developed for prediction of T. amurensis blooming progress using average daily temperatures. Using the starting date of G DD accumulation of January 1 and base temperature of 5 ℃, blooming period ranging from 10% to 90% of cumulative blooming rate was estimated as 860-1198 degree days (DD). This corresponded to the beginning to the end of July in Mt. Gariwaning area in 2021. This model could explain the phenological variations of T. amurensis flower blooming possibly affected by elevation within geographic area, latitude or year relative to the climate change, and aid forest beekeepers for better timing of nectar foraging by honey bees.

• BMB Reports
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• v.39 no.5
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• pp.571-577
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• 2006

Dendrolimus punctatus tetravirus (DpTV) has been identified as a new member of the genus Omegatetravirus of the family Tetraviridae that may be related serologically to Nudaurelia capensis virus ($N{\omega}V$). To establish the function of DpTV RNA genome and to better understand the mechanism of viral replication, the putative RNA-dependent RNA polymerase (RdRp) domain has been cloned and expressed in Escherichia coli. The recombinant protein was purified on a Ni-chelating HisTrap affinity column and demonstrated to initiate viral RNA synthesis in a primer-independent manner but not by terminal nucleotidyle transferase activity in the presence of $Mg^{2+}$ and RNA template. Mutation of the GDD to GAA interferes with the residues at the polymerase active site and metal ions, and thus renders the polymerase inactive.

• Journal of Plant Biology
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• v.39 no.4
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• pp.265-271
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• 1996

Full-length cDNA for RNA2 of cucumber mosaic virus strian Kor (Kor-CMV) was cloned downstream of synthetic T7 promoter by reverse transcriptase-polymerase chain reaction (RT-PCR). The clone could generate a full-length transcript corresponding to RNA1 in size when synthesized by T7 RNA polymerase. The complete nucleotide sequence has shown that the RNA2 is composed of 3,049 nucleotides and contains one functional open reading frame (ORF) of 2,574 nucleotides encoding 2a protein. The deduced translation product of the 2,574 nucleotides contains GDD motif which is a characteristic of RNA-dependent RNA polymerase (RdRp). The amino acid sequence analysis of the 2a protein has shown that the homology is found in decreasing order with O-CMV (98.8%), Y-CMV (98.7%), Fny-CMV (98.3%), KCMV (94.9%), Ix-CMV (91.9%), and Q-CMV (74.9%). Kor-CMV is suggested to belong to subgroup Ⅰ in the aspect of nucleotide sequence homology of RNA2.