• Korean Journal of Environmental Agriculture
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• v.5 no.1
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• pp.35-42
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• 1986

This study was carried out to investigate the distribution of arsenic (As) fractions in paddy soils in relation to some soil characteristics and to find out the relationship between As fractions in soil and As content in brown rice. Soils and rice samples were collected from paddy field adjacent to arsenic mining and refinery sites. Sequential extraction procedures were used to fractionate As in soils into the designated forms of water soluble-As, Al-As, Fe-As, Ca-As, and residual-As. The results obtained were as follows: 1. The percent distribution of As fractions in soil showed a wide difference depending on some soil properties. The relative abundance of the extractable inorganic As fractions was in the order of Fe-As>Al-As>Ca-As>Water soluble-As regardless of mining and refinery sites. Residual-As fraction was more abundant in mining site than in refinery site. 2. With increasing soil pH, the percent distribution of Fe-As and Al-As fractions were decreased, but that of Ca-As and Residual-As fractions increased. The percent distribution of Al-As fraction in soil was negatively correlated with soil CEC, but others showed positive relationships. 3. Active Al and Fe content, and exchangeable Ca content in soil were positively correlated with the percent distribution of Al-As, Fe-As, and Ca-As fractions in soil respectively, and higher correlation between them was shown in mining site than in refinery site. 4. Soil As fractions, except for water soluble-As, showed significant correlation with among each others and also with 1N HCl extration method using as the common soil As extractant in Korea. 5. Arsenic content in brown rice had highly significant correlation with Al-As fraction in soil and it also showed significant correlation with Fe-As and Ca-As fractions, Total-As, and 1N-HCl extractable As.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.64 no.4
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• pp.459-468
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• 2019

Changes in growing periods and productivities of crops under double cropping of potato-rice, potato-soybean and potato-maize, were investigated at the Paddy Experimental Fields in Miryang City from 2015 to 2018. Spring potatoes planted in early March showed a yield of 2.1-2.3 ton/10a and a period of 90 days. In double cropping, growing period of rice, soybean, and maize was about 130, 125 and 115 days, respectively. The potato yield obtained was as much as 616, 330 and 815 kg/10a under double cropping with rice, soybean and maize, respectively. It is beneficial to sow the spring potatoes as early as possible to increase the yield and to secure the growing period of sequential crops. The introduction of summer medium-late variety grain crops into double cropping of spring potato and rice as well as into double cropping of spring potato and soybean/maize, was possible because of no sowing in the fall and plants were able to reach the heading growth stage before the safe heading limit of rice in particular. In the case of maize, the growth period was different according to the change in temperature over the year. The introduction of upland crops such as soybeans and maize instead of rice improved soil physicochemical properties in a short period of time, contributing to the increase of spring potato yields, but there was also a risk of damage by successive cropping for more than three years. Spring potato-maize showed higher yield in terms of starch production, and spring potato-soybean was found to be advantageous for net income.

• Journal of Soil and Groundwater Environment
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• v.11 no.3
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• pp.43-51
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• 2006

Generally abandoned mine soils have serious problems for introducing vegetation such as nutrient deficiency, poor physical properties, and phytotoxicity due to high levels of heavy metals. It is required to improve soil amenity for revegetation. One of its strategies is using organic materials such as compost manure and sludge. The pot experiments was conducted to evaluate the effects of pig manure and municipal sewage sludge on revegetation of mining area soil surface with Artemisia princeps and Zoysia japonica. Application rate of pig manure and municipal sewage sludge was $75{\sim}225$ Mg/ha and $150{\sim}450$ Mg/ha, respectively. The results showed that the application of manure and sludge increased organic matter about two-fold and total nitrogen contents about five-fold of mine soil and improved the growth of plants in all treatments compared to the control. The result of plant tissue analysis showed that both plants accumulate Cd, Cu and Zn in root tissue rather than shoot tissues. Increased sludge application reduced Zn accumulation in both plant tissue. Sequential extraction results indicated that addition of soil amendment induced increment of organically bound fractions of Cu and Zn. Organically bound fraction of Zn was significantly increased from 7.84% to 13.58% in Artemisia princeps planted soil and from 7.84% to 14.16% in Zoysia japonica planted soil, thereby bioavailability of heavy metals was reduced. The results suggested that application of organic materials to mine soil can reduce phytotoxicity of heavy metals and be helpful in introducing successful revegetation.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.49-71
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• 2021

Users who intend to utilize knowledge to actively solve given problems proceed their jobs with cross- and sequential exploration of associated knowledge related each other in terms of certain criteria, such as content relevance. A knowledge map is the diagram or taxonomy overviewing status of currently managed knowledge in a knowledge-base, and supports users' knowledge exploration based on certain relationships between knowledge. A knowledge map, therefore, must be expressed in a networked form by linking related knowledge based on certain types of relationships, and should be implemented by deploying proper technologies or tools specialized in defining and inferring them. To meet this end, this study suggests a methodology for developing the knowledge graph-based knowledge map using the Graph DB known to exhibit proper functionality in expressing and inferring relationships between entities and their relationships stored in a knowledge-base. Procedures of the proposed methodology are modeling graph data, creating nodes, properties, relationships, and composing knowledge networks by combining identified links between knowledge. Among various Graph DBs, the Neo4j is used in this study for its high credibility and applicability through wide and various application cases. To examine the validity of the proposed methodology, a knowledge graph-based knowledge map is implemented deploying the Graph DB, and a performance comparison test is performed, by applying previous research's data to check whether this study's knowledge map can yield the same level of performance as the previous one did. Previous research's case is concerned with building a process-based knowledge map using the ontology technology, which identifies links between related knowledge based on the sequences of tasks producing or being activated by knowledge. In other words, since a task not only is activated by knowledge as an input but also produces knowledge as an output, input and output knowledge are linked as a flow by the task. Also since a business process is composed of affiliated tasks to fulfill the purpose of the process, the knowledge networks within a business process can be concluded by the sequences of the tasks composing the process. Therefore, using the Neo4j, considered process, task, and knowledge as well as the relationships among them are defined as nodes and relationships so that knowledge links can be identified based on the sequences of tasks. The resultant knowledge network by aggregating identified knowledge links is the knowledge map equipping functionality as a knowledge graph, and therefore its performance needs to be tested whether it meets the level of previous research's validation results. The performance test examines two aspects, the correctness of knowledge links and the possibility of inferring new types of knowledge: the former is examined using 7 questions, and the latter is checked by extracting two new-typed knowledge. As a result, the knowledge map constructed through the proposed methodology has showed the same level of performance as the previous one, and processed knowledge definition as well as knowledge relationship inference in a more efficient manner. Furthermore, comparing to the previous research's ontology-based approach, this study's Graph DB-based approach has also showed more beneficial functionality in intensively managing only the knowledge of interest, dynamically defining knowledge and relationships by reflecting various meanings from situations to purposes, agilely inferring knowledge and relationships through Cypher-based query, and easily creating a new relationship by aggregating existing ones, etc. This study's artifacts can be applied to implement the user-friendly function of knowledge exploration reflecting user's cognitive process toward associated knowledge, and can further underpin the development of an intelligent knowledge-base expanding autonomously through the discovery of new knowledge and their relationships by inference. This study, moreover than these, has an instant effect on implementing the networked knowledge map essential to satisfying contemporary users eagerly excavating the way to find proper knowledge to use.