• Title/Summary/Keyword: Weather Information System

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Environmental impact of hydroponic nutrient wastewater, used hydroponic growing media, and crop wastes from acyclic hydroponic farming system (비순환식 양액재배에서 발생하는 폐양액, 폐배지, 폐작물이 환경에 미치는 영향)

  • Park, Bounglog;Cho, Hongmok;Kim, Minsang
    • Journal of the Korea Organic Resources Recycling Association
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    • v.29 no.1
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    • pp.19-27
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    • 2021
  • Hydroponic farming is a method to grow a plant without soil. Plants can be grown on water or hydroponic growing media, and they are fed with mineral nutrient solutions, which are fertilizers dissolved into water. Hydroponic farming has the advantage of increasing plant productivity over conventional greenhouse farming. Previous studies of hydroponic nutrient wastewater from acyclic hydroponic farms pointed out that hydroponic nutrient wastewater contained residual nutrients, and they were drained to a nearby river bank which causes several environmental issues. Also, previous studies suggest that excessive use of the nutrient solution and disposal of used hydroponic growing media and crop wastes in hydroponic farms are major problems to hydroponic farming. This study was conducted to determine the impact of hydroponic nutrient wastewater, used hydroponic growing media, and crop wastes from acyclic hydroponic farms on the surrounding environment by analyzing water quality and soil analysis of the above three factors. Three soil cultivation farms and several hydroponic farms in the Gangwon C region were selected for this study. Samples of water and soils were collected from both inside and outside of each farm. Also, a sample of soil and leachate from crop waste piles stacked near the farm was collected for analysis. Hydroponic nutrient wastewater from acyclic hydroponic farm contained an average of 402 mg/L of total nitrogen (TN) concentration, and 77.4 mg/L of total phosphate (TP) concentration. The result of TP in hydroponic nutrient wastewater exceeds the living environmental standard of the river in enforcement decree of the framework act on environmental policy by 993.7 times. Also, it exceeds the standard of industrial wastewater discharge standards under the water environment conservation act by 6~19 times in TN, and 2~27 times in TP. Leachate from crop waste piles contained 11,828 times higher COD and 395~2662 times higher TP than the standard set by the living environmental standard of the river in enforcement decree of the framework act on environmental policy and exceeds 778 times higher TN and 5 times higher TP than the standard of industrial wastewater discharge standards under the water environment conservation act. For more precise studies of the impact of hydroponic nutrient wastewater, used hydroponic growing media, and crop wastes from acyclic hydroponic farms on the surrounding environment, additional information regarding a number of hydroponic farms, arable area(ha), hydroponic farming area, seasonal, weather, climate factor around the river, and the property of the area and farm is needed. Analysis of these factors and additional water and soil samples are needed for future studies.

Analysis of Rice Blast Outbreaks in Korea through Text Mining (텍스트 마이닝을 통한 우리나라의 벼 도열병 발생 개황 분석)

  • Song, Sungmin;Chung, Hyunjung;Kim, Kwang-Hyung;Kim, Ki-Tae
    • Research in Plant Disease
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    • v.28 no.3
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    • pp.113-121
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    • 2022
  • Rice blast is a major plant disease that occurs worldwide and significantly reduces rice yields. Rice blast disease occurs periodically in Korea, causing significant socio-economic damage due to the unique status of rice as a major staple crop. A disease outbreak prediction system is required for preventing rice blast disease. Epidemiological investigations of disease outbreaks can aid in decision-making for plant disease management. Currently, plant disease prediction and epidemiological investigations are mainly based on quantitatively measurable, structured data such as crop growth and damage, weather, and other environmental factors. On the other hand, text data related to the occurrence of plant diseases are accumulated along with the structured data. However, epidemiological investigations using these unstructured data have not been conducted. The useful information extracted using unstructured data can be used for more effective plant disease management. This study analyzed news articles related to the rice blast disease through text mining to investigate the years and provinces where rice blast disease occurred most in Korea. Moreover, the average temperature, total precipitation, sunshine hours, and supplied rice varieties in the regions were also analyzed. Through these data, it was estimated that the primary causes of the nationwide outbreak in 2020 and the major outbreak in Jeonbuk region in 2021 were meteorological factors. These results obtained through text mining can be combined with deep learning technology to be used as a tool to investigate the epidemiology of rice blast disease in the future.

A study on the Greeting's Types of Ganchal in Joseon Dynasty (간찰(簡札)의 안부인사(安否人事)에 대한 유형(類型) 연구(硏究))

  • Jeon, Byeong-yong
    • (The)Study of the Eastern Classic
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    • no.57
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    • pp.467-505
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    • 2014
  • I am working on a series of Korean linguistic studies targeting Ganchal(old typed letters in Korea) for many years and this study is for the typology of the [Safety Expression] as the part. For this purpose, [Safety Expression] were divided into a formal types and semantic types, targeting the Chinese Ganchal and Hangul Ganchal of modern Korean Language time(16th century-19th century). Formal types can be divided based on whether Normal position or not, whether Omission or not, whether the Sending letter or not, whether the relationship of the high and the low or not. Normal position form and completion were made the first type which reveal well the typicality of the [Safety Expression]. Original position while [Own Safety] omitted as the second type, while Original position while [Opposite Safety] omitted as the third type, Original position while [Safety Expression] omitted as the fourth type. Inversion type were made as the fifth type which is the most severe solecism in [Safety Expression]. The first type is refers to Original position type that [Opposite Safety] precede the [Own Safety] and the completion type that is full of semantic element. This type can be referred to most typical and normative in that it equipped all components of [Safety Expression]. A second type is that [Safety Expression] is composed of only the [Opposite Safety]. This type is inferior to the first type in terms of set pattern, it is never outdone when it comes to the appearance frequency. Because asking [Opposite Safety] faithfully, omitting [Own Safety] dose not greatly deviate politeness and easy to write Ganchal, it is utilized. The third type is the Original position type showing the configuration of the [Opposite Safety]+Own Safety], but [Opposite Safety] is omitted. The fourth type is a Original position type showing configuration of the [Opposite Safety+Own Safety], but [Safety Expression] is omitted. This type is divided into A ; [Safety Expression] is entirely omitted and B ; such as 'saving trouble', the conventional expression, replace [Safety Expression]. The fifth type is inversion type that shown to structure of the [Own Safety+Opposite Safety], unlike the Original position type. This type is the most severe solecism type and real example is very rare. It is because let leading [Own Safety] and ask later [Opposite Safety] for face save is offend against common decency. In addition, it can be divided into the direct type that [Opposite Safety] and [Own Safety] is directly connected and indirect type that separate into the [story]. The semantic types of [Safety Expression] can be classified based on whether Sending letter or not, fast or slow, whether intimate or not, and isolation or not. For Sending letter, [Safety Expression] consists [Opposite Safety(Climate+Inquiry after health+Mental state)+Own safety(status+Inquiry after health+Mental state)]. At [Opposite safety], [Climate] could be subdivided as [Season] information and [Climate(weather)] information. Also, [Mental state] is divided as receiver's [Family Safety Mental state] and [Individual Safety Mental state]. In [Own Safety], [Status] is divided as receiver's traditional situation; [Recent condition] and receiver's ongoing situation; [Present condition]. [Inquiry after health] is also subdivided as receiver's [Family Safety] and [Individual Safety], [Safety] is as [Family Safety] and [Individual Safety]. Likewise, [Inquiry after health] or [Safety] is usually used as pairs, in dimension of [Family] and [Individual]. This phenomenon seems to have occurred from a big family system, which is defined as taking care of one's parents or grand parents. As for the Written Reply, [Safety Expression] consists [Opposite Safety (Reception+Inquiry after health+Mental state)+Own safety(status+Inquiry after health+Mental state)], and only in [Opposite safety], a difference in semantic structure happens with Sending letter. In [Opposite Safety], [Reception] is divided as [Letter] which is Ganchal that is directly received and [Message], which is news that is received indirectly from people. [Safety] is as [Family Safety] and [Individual Safety], [Mental state] also as [Family Safety Mental state] and [Individual Safety Mental state].