• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.4
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• pp.189-195
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• 2012

To predict the blooming date of 'Yumyeong' peach trees, the models for flower bud developmental rate (DVR) were constructed. The DVRs were calculated from the demanded times at controlled air temperatures. The branches of 'Yumyeong' peach trees were incubated at three different temperatures of 9.7, 15.2, and $18.9^{\circ}C$. The DVRs were also constructed with blooming dates and air temperatures in the field, collected from 1979 to 2008 at the experimental orchard of National Institute of Horticultural and Herbal Science, Suwon, Korea. All the DVRs increased linearly or exponentially with air temperature. The DVR equations evaluated under controlled air temperatures were y=0.0018x+0.0051 and y=$0.0125e^{0.0603x}$. The DVR equations under field conditions were calculated as y=0.0039x-0.0112 and y=$0.0062e^{0.1512x}$. These DVR equations offer developmental indices and predict the date for blooming with air temperature data. These DVR equations were validated against the blooming data observed in the field. When the blooming dates were calculated with exponential DVR equations and daily air temperature data, the root mean squared errors between the observed and predicted dates were around 2 days. These results suggest that the DVR models are useful to predict the blooming date of 'Yumyeong' peach trees.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.2
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• pp.148-155
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• 2005

An accurate prediction of blooming date is crucial for many authorities to schedule and organize successful spring flower festivals in Korea. The Korea Meteorological Administration (KMA) has been using regression models combined with a subjective correction by forecasters to issue blooming date forecasts for major cities. Using mean monthly temperature data for February (observed) and March (predicted), they issue blooming date forecasts in late February to early March each year. The method has been proved accurate enough for the purpose of scheduling spring festivals in the relevant cities, but cannot be used in areas where no official climate and phenology data are available. We suggest a thermal time-based two-step phenological model for predicting the blooming dates of spring flowers, which can be applied to any geographic location regardless of data availability. The model consists of two sequential periods: the rest period described by chilling requirement and the forcing period described by heating requirement. It requires daily maximum and minimum temperature as an input and calculates daily chill units until a pre-determined chilling requirement for rest release. After the projected rest release date, it accumulates daily heat units (growing degree days) until a pre- determined heating requirement for flowering. Model parameters were derived from the observed bud-burst and flowering dates of cherry tree (Prunus serrulata var. spontanea) at KMA Seoul station along with daily temperature data for 1923-1950. The model was applied to the 1955-2004 daily temperature data to estimate the cherry blooming dates and the deviations from the observed dates were compared with those predicted by the KMA method. Our model performed better than the KMA method in predicting the cherry blooming dates during the last 50 years (MAE = 2.31 vs. 1.58, RMSE = 2.96 vs. 2.09), showing a strong feasibility of operational application.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.1
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• pp.50-58
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• 2013

This study was carried out to evaluate the geospatial characteristics of blooming date migration in three major spring flowers across North and South Korea as influenced by climate change. A thermal time-based phenology model driven by daily maximum and minimum temperature was adjusted for the key parameters (i.e., reference temperature, chilling requirement, heating requirement) used for predicting blooming of forsythia, azaleas, and Japanese cherry. The model was run by the RCP 8.5 projected temperature outlook over the Korean Peninsula and produced the mean booming dates for the three climatological normal years in the future (2011-2040, 2041-2070, and 2071-2100) at a 12.5 km grid spacing. Comparison against the observed blooming date patterns in the baseline climate (1971-2000) showed that there will be a substantial acceleration in blooming dates of the three species, resulting in cherry booming in February and flowers of azaleas and forsythia found at the top of mountain Baikdu by the 2071-2100 period. Flowering dates of the three species in the near future (2011-2040) may be accelerated by 3-5 days at minimum and 10-11 days at maximum compared with that in the baseline period (1971-2000). Those values corresponding to the middle future (2041-2070) can be from a minimum of 9-11 days to a maximum of 23-24 days. Blooming date of Japanese cherry can be accelerated by 26 days on average for the far future (2071-2100). The acceleration seems more prominent at islands and coastal plain areas than over inland mountainous areas.

• Korean Journal of Agricultural Science
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• v.46 no.3
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• pp.529-538
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• 2019

This study examined the changes in plant phenology of 12 woody species in Daegu University Forest, Gyeongsan-si, Gyeongsanbuk-do in 2007 and 2018. The Hobo was installed at a height of 1.2 meters to measure the microclimate such as air temperature and relative humidity to identify its effects on the changes in plant phenology. The number of trees surveyed were 42 individuals that included 12 species in 9 families, all of which are deciduous broad-leaved trees. The trends in temperature change in 2018 were similar to that in 2007, except for the temperatures in the warmest and coldest month. Compared to 2007, the average temperature of the warmest month in 2018 was $2.5^{\circ}C$ higher, and the coldest month was $3.3^{\circ}C$ lower. The lowest temperature from February to April in 2018 had the highest correlation with the blooming dates of the trees (r = 0.692) in 2018, and the highest temperature showed the lowest correlation (r = 0.392). The blooming date by species was significantly different (p < 0.05). The blooming date of 8 species (75%), including Prunus padus, was earlier by 1 to 16 days, while 4 species, such as Prunus armeniaca var. ansu, was later by 1 to 7 days in 2018 than that in 2007. However, the flowering duration did not have a significant effect on the plant phenology. The results can be used as basic data for long-term monitoring of plant phenology in the future, and follow-up studies on other environmental factors and physiological factors are needed.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.1
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• pp.40-49
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• 2013

Current service system of the Korea Meteorological Administration (KMA) for blooming date forecasting in spring depends on regression equations derived from long term observations in both temperature and phenology at a given station. This regression based system does not allow a timely correction or update of forecasts that are highly sensitive to fluctuating weather conditions. Furthermore, the system cannot afford plant responses to climate extremes which were not observed before. Most of all, this method may not be applicable to locations other than that which the regression equations were derived from. This note suggests a way to replace the location restricted regression equations with a thermal time based phenology model to complement the KMA blooming forecast system. Necessary parameters such as reference temperature, chilling requirement and heating requirement were derived from phenology data for forsythia, azaleas and Japanese cherry at 29 KMA stations for the 1951-1980 period to optimize spring phenology prediction model for each species. Best fit models for each species were used to predict blooming dates and the results were compared with the observed dates to produce a correction grid across the whole nation. The models were driven by the KMA's daily temperature data at a 5km grid spacing and subsequently adjusted by the correction grid to produce the blooming date maps. Validation with the 1971-2012 period data showed the RMSE of 2-3 days for Japanese cherry, showing a feasibility of operational service; whereas higher RMSE values were observed with forsythia and azaleas.

• 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 Bio-Environment Control
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• v.31 no.3
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• pp.230-236
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• 2022

This study was carried out to produce two-flowered seedlings, harvest them early in a greenhouse, and extend the harvest period. This study was carried out to effectively produce the second truss blooming seedlings to harvest tomatoes early and extend the harvest period. For production of the second truss blooming seedlings (one stem), the nutrient solution EC was supplied at 1.5, 2.0, 2.5 dS·m^-1, and dynamic management (3.0 → 3.5 → 4.5 dS·m^-1). The seedling period was 60 days, which was 20-40 days longer than conventional seedlings, and 10 days longer than the first truss blooming seedlings (cube seedlings). The plant height was 78 and 77 cm in EC 2.5 dS·m^-1 and dynamic management respectively, which was shorter than EC 1.5 dS·m^-1 with 88 cm. As for the EC in the cube before formulation, dynamic management had the highest EC 5.5 dS·m^-1, and the cube supplied with EC 1.5 dS·m^-1 had the lowest. The production yield by treatment did not a difference among in the second truss blooming seedlings, but the first truss blooming seedlings showed lower productivity than second truss blooming seedlings. The second truss blooming seedling were harvested 35 days after planting on June 4, the first harvest date, and the first truss blooming were harvested in 42 days on June 11th. There was no difference in plant height and root growth due to bending at frequency planting. In the study on the production of the second truss blooming seedlings (two stem), the nutrient solution EC was supplied under 2.0, 2.5, 3.0 dS·m^-1, and dynamic management (3.0 → 3.5 → 4.5 dS·m^-1). The seedling period was 90 days, which was 40-50 days longer than conventional seedlings and 10 days longer than the first truss blooming seedlings (cube seedlings). Plant height was 80 and 81 cm in EC 2.0 dS·m^-1 and 2.5 dS·m^-1 respectively, but was the shortest at 73 cm in dynamic management. EC in the medium increased as the seeding period increased in all treatments. The dynamic management was the highest with EC 5.1 dS·m^-1. There was no difference in yield among EC treatments in the second truss blooming seedlings, which had a longer seeding period of about 10 days, produced 15% more than the first truss blooming seedlings. In order to shorten the plant height of the second truss blooming seedlings, it is judged that the most efficient method is increasing the concentration of nutrient solution.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.396-402
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• 2014

The spring season in Korea features a dynamic landscape with a variety of flowers such as magnolias, azaleas, forsythias, cherry blossoms and royal azaleas flowering sequentially one after another. However, the narrowing of south-north differences in flowering dates and those among the flower species was observed in 2014, taking a toll on economic and shared communal values of seasonal landscape. This study was carried out to determine whether the 2014 incidence is an outlier or a mega trend in spring phenology. Data on flowering dates of forsythias and cherry blossoms, two typical spring flower species, as observed for the recent 60 years in 6 weather stations of Korea Meteorological Administration (KMA) indicate that the difference spanning the flowering date of forsythias, the flower blooming earlier in spring, and that of cherry blossoms that flower later than forsythias was 30 days at the longest and 14 days on an average in the climatological normal year for the period 1951-1980, comparing with the period 1981-2010 when the difference narrowed to 21 days at the longest and 11 days on an average. The year 2014 in particular saw the gap further narrowing down to 7 days, making it possible to see forsythias and cherry blossoms blooming at the same time in the same location. 'Cherry blossom front' took 20 days in traveling from Busan, the earliest flowering station, to Incheon, the latest flowering station, in the case of the 1951-1980 normal year, while 16 days for the 1981-2010 and 6 days for 2014 were observed. The delay in flowering date of forsythias for each time period was 20, 17, and 12 days, respectively. It is presumed that the recent climate change pattern in the Korean Peninsula as indicated by rapid temperature hikes in late spring contrastive to slow temperature rise in early spring immediately after dormancy release brought forward the flowering date of cherry blossoms which comes later than forsythias which flowers early in spring. Thermal time based heating requirements for flowering of 2 species were estimated by analyzing the 60 year data at the 6 locations and used to predict flowering date in 2014. The root mean square error for the prediction was within 2 days from the observed flowering dates in both species at all 6 locations, showing a feasibility of thermal time as a prognostic tool.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.26 no.3
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• pp.243-250
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• 1981

Soybean, azuki-bean and mungbean were cultivated at different growing conditions, May 10, June 9, July 9 seeding, and May 10 seeding-short day treatment, to investigate the distribution of flowering date and the variation of pod/flower ratio. The growth habit type of the soybean variety used was determinate, but the azuki-bean and mungbean varieties used showed indeterminate growth habit. The pod/flower ratio ranged 38 to 48% for soybean, 23 to 34% for azuki-bean and 46 to 60% for mungbean along with growing conditions. Flower abscission for soybean and mungbean, and pod abscission for azuki-bean affected more on the number of matured pods. Soybean showed once full blooming period, but azuki-bean and mungbean showed two or three times full blooming period except July 9 seeding plot through the whole growing period. Flowers bloomed just after every full blooming period showed lower value of pod/flower ratio and higher pod/flower ratio was obtained from flowers bloomed before or far after full blooming at plots seeded May 10 and June 9 in three pulse crops. Most full blooming period of soybean coincided within 5 days near the terminal leaf appearance date, and number of flowers bloomed before terminal leaf expansion and matured pods from these flowers were major in every soybean plant at all growing codition plots. No relations were found between terminal leaf appearance and flowering or pod setting patterns of azuki-bean and mungbean.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.500-519
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• 2019

The blooming of social media has simulated interest in sentiment analysis. Sentiment analysis aims to determine from a specific piece of content the overall attitude of its author in relation to a specific item, product, brand, or service. In sentiment analysis, the focus is on the subjective sentences. Hence, in order to discover and extract the subjective information from a given text, researchers have applied various methods in computational linguistics, natural language processing, and text analysis. The aim of this paper is to provide an in-depth up-to-date study of the sentiment analysis algorithms in order to familiarize with other works done in the subject. The paper focuses on the main tasks and applications of sentiment analysis. State-of-the-art algorithms, methodologies and techniques have been categorized and summarized to facilitate future research in this field.