• 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.

• 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.

• Journal of Animal Science and Technology
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• v.65 no.4
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• pp.792-803
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• 2023

This study aimed to assess the impact of weather events on the sorghum-sudangrass hybrid (Sorghum bicolor L.) cultivar production trend in the central inland region of Korea during the monsoon season, using time series analysis. The sorghum-sudangrass production data collected between 1988 and 2013 were compiled along with the production year's weather data. The growing degree days (GDD), accumulated rainfall, and sunshine duration were used to assess their impacts on forage production (kg/ha) trend. Conversely, GDD and accumulated rainfall had positive and negative effects on the trend of forage production, respectively. Meanwhile, weather events such as heavy rainfall and typhoon were also collected based on weather warnings as weather events in the Korean monsoon season. The impact of weather events did not affect forage production, even with the increasing frequency and intensity of heavy rainfall. Therefore, the trend of forage production for the sorghum-sudangrass hybrid was forecasted to slightly increase until 2045. The predicted forage production in 2045 will be 14,926 ± 6,657 kg/ha. It is likely that the damage by heavy rainfall and typhoons can be reduced through more frequent harvest against short-term single damage and a deeper extension of the root system against soil erosion and lodging. Therefore, in an environment that is rapidly changing due to climate change and extreme/abnormal weather, the cultivation of the sorghum-sudangrass hybrid would be advantageous in securing stable and robust forage production. Through this study, we propose the cultivation of sorghum-sudangrass hybrid as one of the alternative summer forage options to achieve stable forage production during the dynamically changing monsoon, in spite of rather lower nutrient value than that of maize (Zea mays L.).

• 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.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.62 no.3
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• pp.214-223
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• 2017

A total of 15 different corn hybrids, Kwangpyeongok, Gangdaok, Yanganok, Singwangok, Jangdaok, Cheonganok, Cheongdaok, Andaok, Dapyeongok, Pyeongkangok, Pyeonganok, Daanok, Sunwon 184, Gangilok, and P3394 was used to investigate the growth and yield depending on the sowing date. The sowing dates were April 5, June 25, and July 5 and each experiments was performed in triplicste. The growth of Gangdaok was the highest. However, although the growth of Kwangpyeongok, was lower thanthar of Gangdaok, its stem height to ear height ratio was lower than that of Gangdaok, thus, Kwangpyeongok may be more suitable for stable cultivation. Both growth and yield of Daanok were low, regardless of planting date, but yield and ear shape of Pyeongkangok and Dapyeongok were for fresh corn. Growth and yield of the 15 different corn hybrids varied depending on the planting date, However, the growth degree days (GDD) was the most important factor governing the maturity of corn. More than $1500^{\circ}C$ of GDD was sufficient to harvest mature corn hybrids in the central region of Korea. Besides yield and growth, other characteristics, such as sweetness and taste of the hybrids, should be investigated further the selection of the best corn hybrid.

• 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.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.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.448-454
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• 2021

This study was conducted to the effect of low air temperature and light intensity conditions on yield and quality of tomato at the early stage of growth in Korea. Inplastic greenhouses, low temperature and low temperature with shade treatments were performed from 17 to 42 days after plant. Tomato growing degree days were decreased 5.5% due to cold treatment during the treatment period. Light intensity decreased 74.7% of growing degree days due to shade. After commencing treatments, the plant growth decreased by low temperature and low radiation except for height. Analysis of the yield showed that the first harvest date was the same, but the yield of the control was 3.3 times higher than low temperature with shade treatment. The cumulative yields at 87 days after transplanting were 1734, 1131, and 854 g per plant for control, low temperature, and low temperature with shade, respectively. The sugar and acidity of tomatoes did not differ between treatment and harvesting season. To investigate the photosynthetic characteristics according to the treatment, the carbon dioxide reaction curve was analyzed using the biochemical model of the photosynthetic rate. The results showed that the maximum photosynthetic rate, J (electric transportation rate), TPU (triose phosphate utilization), and R_d (dark respiration rate) did not show any difference with temperature, but were reduced by shading. Vcmax (maximum carboxylation rate) was decreased depending on the low temperature and the shade. Results indicated that low temperature and light intensity at the early growth stage can be inhibited the growth in the early stage but this phenomenon might be recovered afterward. The yield was reduced by low temperature and low intensity and there was no difference in quality.

• 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.

• Journal of Bio-Environment Control
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• v.26 no.4
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• pp.346-352
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• 2017

In this study, we analyzed environmental factors including annual fruit growth and meteorological conditions in Suwon area from 2000 to 2014 to develop and verify a fruit width prediction model in 'Fuji' apple. The 15-year average of full bloom data was April 28 and that of fruit development period was 181 days. The fruit growth until 36 days after full bloom followed single sigmoid curve. The environmental factors affecting fruit width were BIO2, precipitation in September, the average of daily maximum and minimum temperature in April, minimum temperature in August, and growing degree days (GDD) in April. Among them, the model was constructed by combining BIO2 and precipitation in September, which are not cross-correlated with each other or, with other factors. And then, the final model was selected as 19.33095 + (5.76242 ${\times}$ BIO2) - (0.01891 ${\times}$ September precipitation) + (2.63046 ${\times}$ minimum temperature in April) which was the most suitable model with AICc of 92.61 and the adjusted $R^2$ value of 0.53. The model was compared with the observed values f rom 2000 to 2014. As a result, the mean difference between the measured and predicted values of 'Fuji' apple fruit width was ${\pm}2.9mm$ and the standard deviation was 3.54.