• ETRI Journal
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• v.44 no.4
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• pp.573-587
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• 2022

The agricultural sector is completely different from other sectors since it completely relies on various natural and climatic factors. Climate changes have many effects, including lack of annual rainfall and pests, heat waves, changes in sea level, and global ozone/atmospheric CO₂ fluctuation, on land and agriculture in similar ways. Climate change also affects the environment. Based on these factors, farmers chose their crops to increase productivity in their fields. Many existing agricultural ontologies are either domain-specific or have been created with minimal vocabulary and no proper evaluation framework has been implemented. A new agricultural ontology focused on subdomains is designed to assist farmers using Jaccard relative extractor (JRE) and Naïve Bayes algorithm. The JRE is used to find the similarity between two sentences and words in the agricultural documents and the relationship between two terms is identified via the Naïve Bayes algorithm. In the proposed method, the preprocessing of data is carried out through natural language processing techniques and the tags whose dimensions are reduced are subjected to rule-based formal concept analysis and mapping. The subdomain ontologies of weather, pest, and soil are built separately, and the overall agricultural ontology are built around them. The gold standard for the lexical layer is used to evaluate the proposed technique, and its performance is analyzed by comparing it with different state-of-the-art systems. Precision, recall, F-measure, Matthews correlation coefficient, receiver operating characteristic curve area, and precision-recall curve area are the performance metrics used to analyze the performance. The proposed methodology gives a precision score of 94.40% when compared with the decision tree(83.94%) and K-nearest neighbor algorithm(86.89%) for agricultural ontology construction.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.355-360
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• 2022

As the increase cost of domestic red pepper and the increase of imported red pepper, damage cases such as false labeling of the origin of red pepper powder are issued. Accordingly we need to determine quickly and accurately for the origin of red pepper powder. The used method for presently determining the origin has the limitation in that it requires a lot of cost and time by experimentally comparing and analyzing the components of red pepper powder. To resolve the issues, this study proposes machine learning algorithm to classifiy domestic and imported red pepper powder. We have built machine learning model with 53 components contained in red pepper powder and validated. Through the proposed model, it was possible to identify which ingredients are importantly used in determining the origin. In the near future, it is expected that the cost of determining the origin can be further reduced by expanding to various foods as well as red pepper powder.

• Journal of Environmental Science International
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• v.31 no.11
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• pp.941-950
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• 2022

This study was conducted to provide data and stem information to establish a local volume table of Cryptomeria japonica in Jeju Island. Stem analysis was performed on 26 trees by selecting two average trees from each site of the 13 plots of C. japonica stands in 2021 and 2022. During the analysis stage, one outlier tree was rejected, and a total of 260 observations of the specific stem height of 25 trees were used. Of the seven major taper equation models applied for parameter estimation and statistical verification, the Muhairwe 1999 model was found to be the best fit and selected as the optimal model. Stem shape-related estimates were acquired through the selected model, and sectional measurements according to the Smalian formula applied at an interval of 10 cm from the height of the stem were used to develop a volume table. A paired t-test comparison between the C. japonica volume obtained from the present study and those selected from the current yield table by NIFoS(2020), revealed significant differences (p<0.05), highlighting the necessity of a local volume table for C. japonica in Jeju Island.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.155-164
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• 2023

Machine learning with its high precision algorithms, Precision agriculture (PA) is a new emerging concept nowadays. Many researchers have worked on the quality and quantity of PA by using sensors, networking, machine learning (ML) techniques, and big data. However, there has been no attempt to work on trends of artificial intelligence (AI) techniques, dataset and crop type on precision agriculture using internet of things (IoT). This research aims to systematically analyze the domains of AI techniques and datasets that have been used in IoT based prediction in the area of PA. A systematic literature review is performed on AI based techniques and datasets for crop management, weather, irrigation, plant, soil and pest prediction. We took the papers on precision agriculture published in the last six years (2013-2019). We considered 42 primary studies related to the research objectives. After critical analysis of the studies, we found that crop management; soil and temperature areas of PA have been commonly used with the help of IoT devices and AI techniques. Moreover, different artificial intelligence techniques like ANN, CNN, SVM, Decision Tree, RF, etc. have been utilized in different fields of Precision agriculture. Image processing with supervised and unsupervised learning practice for prediction and monitoring the PA are also used. In addition, most of the studies are forfaiting sensory dataset to measure different properties of soil, weather, irrigation and crop. To this end, at the end, we provide future directions for researchers and guidelines for practitioners based on the findings of this review.

• The Plant Pathology Journal
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• v.39 no.6
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• pp.548-565
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• 2023

Armillaria root disease affects forests around the world. It occurs in many habitats and causes losses in the infested stands. Weather conditions are important factors for growth and development of Armillaria species. Yet, the relation between occurrence of damage caused by Armillaria disease and weather variables are still poorly understood. Thus, we used generalized linear mixed models to determine the relationship between weather conditions of current and previous year (temperature, precipitation and their deviation from long-term averages, air humidity and soil temperature) and the incidence of Armillaria-induced damage in young (up to 20 years old) and older (over 20 years old) coniferous stands in selected forest districts across Poland. We used unique data, gathered over the course of 23 years (1987-2009) on tree damage incidence from Armillaria root disease and meteorological parameters from the 24-year period (1986-2009) to reflect the dynamics of damage occurrence and weather conditions. Weather parameters were better predictors of damage caused by Armillaria disease in younger stands than in older ones. The strongest predictor was soil temperature, especially that of the previous year growing season and the current year spring. We found that temperature and precipitation of different seasons in previous year had more pronounced effect on the young stand area affected by Armillaria. Each stand's age class was characterized by a different set of meteorological parameters that explained the area of disease occurrence. Moreover, forest district was included in all models and thus, was an important variable in explaining the stand area affected by Armillaria.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2020.08a
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• pp.45-45
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• 2020

A large number of expressed sequence tags (ESTs) in public databases have provided an opportunity for the systematic development of simple sequence repeat (SSR) markers. EST-SSRs derived from conserved coding sequences show considerable cross-species transferability in related species. In the present study, we assessed the utility of foxtail millet EST-SSRs in barnyard millet. A total of 312 EST-SSRs of foxtail millet were tested using 84 Echinochloa crus-galli germplasm accessions; a high rate of transferability (62%) and 46 primer sets (13%) were shown the polymorphism in barnyard millet. The 13% of functional EST-SSRs) was demonstrated between cereals and barnyard millet. SSR marker profile data were scored for the computation of pairwise distances as well as a Neighbor Joining (NJ) tree of all the genotypes. The averaged values of gene diversity (H_E) and polymorphism information content (PIC) were 0.213 and 0.179 within populations, respectively. The 84 barnyard millet germplasm accessions were divided into five different groups, which agreed well with their geographical origins. The exotic 12 accessions of India type barnyard millet (E. frumentacea) were all separated form Korean local collection genotype. The present results provide evidence of divergence between cultured and wild type barnyard, as a millet and grass. The polymorphic SSR markers indicated in this study were of great value in analysis of genetic diversity that can be further used for crop improvement through breeding.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.1348-1351
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• 2008

최근 인터넷 사용자들의 요구는 멀티미디어로 집중되고 있으며 그중 라이브 미디어 스트리밍 서비스에 대한 요구가 증가하고 있다. 라이브 서비스에서는 적절한 시간에 사용자에게 데이터가 도착하는 것이 중요하다. 따라서 라이브의 시간적절성을 충족시켜 줄 효율적이고 신속한 데이터 전달구조와 전송기법이 요구된다. 이에 본 논문에서는 트리와 메시 구조를 혼합한 하이브리드 방식으로 네트워크 자원을 효율적으로 사용하면서 빠른 데이터 전송으로 라이브의 시간적절성을 충족시킬 수 있는 데이터 분할 전송 방식의 P2P(Peer-to-Peer) 오버레이 구조를 제안한다. 제안하는 ToG(Tree of Groups)는 n개의 피어들이 메시로 그룹을 형성하고, 그렇게 형성된 그룹들이 트리를 이루는 구조이다. ToG에서 그룹 내의 각 피어들은 상위그룹의 피어 한 개와 부모-자식으로 연결되어 있어서 그룹 사이에 여러 개의 연결이 존재하게 된다. 따라서 그룹 내에서 어느 한 피어가 그룹을 빠져 나가더라도 상위그룹과의 여러 연결에 의해서 서비스 지속성을 보장 할 수 있다. ToG는 그룹단위로 트리가 형성되기 때문에 피어의 개수가 같을 때 피어단위로 트리를 형성하는 구조보다 트리의 깊이가 줄어든다. 그에 따라 말단에 있는 피어들에게까지 빠른 시간에 데이터가 전달 될 수 있다. ToG의 데이터 전달은 소스로부터 세그먼트가 일정한 값 n으로 나뉘어져 각 피어들에게 전달된다. 세그먼트 조각은 소스로부터 나뉘어져 전송 될 때 책임적으로 전달해야할 피어와 전달 순서가 정해져있고, 데이터 전송 스케줄링을 위한 버퍼 맵 교환은 필요하지 않다.

• Fisheries and Aquatic Sciences
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• v.26 no.12
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• pp.752-761
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• 2023

Genetic diversity serves as the basis for selecting and genetically enhancing any culturable species in aquaculture. Here, two different strains of wild (River Ravi and River Kabul) and six captive-bred strains of Labeo rohita from various provinces were se- lected, and genetic diversity among them was evaluated using three different microsatellite markers, i.e., Lr-28, Lr-29, and Lr-37, and one mitochondrial CO1 (Cytochrome c oxidase subunit 1) gene. Different strains of L. rohita were collected, and part of their caudal fin was cut and preserved in ethanol for DNA extraction and determination of genetic diversity among them. Results in- dicated that selected markers were polymorphic with polymorphic information content (PIC) content values above 0.5 with the highest in Lr-28 followed by Lr-29 and then Lr-37. The observed heterozygosity (Ho) of all strains was higher (Avg: 0.731) but less than the expected heterozygosity (He). Moreover, TMs and WRs showed the highest He, while TKs showed the lowest, He. Over- all, inbreeding coefficient (FIS) values observed for all strains with selected markers were positive. The DNA barcoding with the CO1 gene revealed genetic variation among various strains, as demonstrated by the clades in the phylogenetic tree separating the strains into two distinct clusters that then divided into sub-clusters. In conclusion, TMs showed the highest heterozygosity as compared to other strains. Overall results provide the baseline data for the initiation of the genetic improvement program.

• Journal of Environmental Science International
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• v.33 no.7
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• pp.453-462
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• 2024

This study was carried out for the purpose of selecting the most appropriate taper equation for the actual stands of Pinus thunbergii in the southern coastal region of Korea and then developing a stem volume table to provide basic data for rational management. To develop a volume table of Pinus thunbergii in this region of Korea, 59 sample trees with various diameter distributions were selected and stem analysis was performed. As a result of stem analysis, two trees with abnormal diameter and height growth as the age increased were rejected, and 57 trees were analyzed. To develop the taper equation, seven major variable exponential equations were used, including Kozak 1988, 1994, 2001, 2002, Bi 2000, Muhairwe 1999, and Sharma and Parton 2009. As a result of parameter estimation and statistical verification, the Kozak 1988 model showed the highest goodness of fit with Fit I (Fit Index), RMSE 1.5620, Bias 0.0031, and MAD 1.0784. The diameter of each 10cm stem ridge for the selected model was estimated, and a stem volume table was produced using the mensuration of division (end area formula) using the Smalian equation. As a result of two-sample T-test for volume table of this study and current yield table, the volume for this study was found to be significantly larger at all observation points (p < 0.001). Even for the same tree species, it is judged that differentiated volume tables are needed for each growth environment characteristic.

• Journal of Environmental Science International
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• v.33 no.7
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• pp.477-487
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• 2024

This study aimed to identify the growth environment of Cudrania tricuspidata by analyzing the site environment, soil characteristics, and vegetation structure of the species habitats and to provide basic data for identifying suitable cultivation sites for mass production. The study was conducted on 17 sites in five cities/counties of Gyeongnam and Jeonnam province. It was found that C. tricuspidata habitats were mainly distributed on gentle slopes in the southeast and southwest, with an average altitude of approximately 290 m. The soil of the C. tricuspidata habitats was sandy loam with a high proportion of sand, averaging 73.9%, 4.6%, and 21.5% sand, silt, and clay, respectively. The soil had a pH value of 5.41 (5.20-5.79), organic matter content of 8.2% (3.6-12.6%), total nitrogen content of 0.36% (0.19-0.54%), available phosphorus content of 3.50 ppm (0.95-7.61 ppm), and cation exchange capacity of 15.9 cmol⁺/kg (10.0-20.7 cmol⁺/kg) on average. The vegetation structure analysis showed that C. tricuspidata appeared in the tree layers of regions A (Jinju) and E (Yeosu), but the importance of C. tricuspidata was found to be high in the subtree and shrub layers in all regions. The ecological niche breadth was widest (0.874) in region B (Hadong) and narrowest (0.480) in region E (Yeosu).