• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.764-771
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• 2018

Domestic and foreign agricultural environments nowadays are undergoing various changes such as aging of agricultural population, increase of earned population, rapid climate change, diversification of agricultural product distribution structure, depletion of water resources and limited cultivation area. In order to respond to various environmental changes in recent agriculture, practical use of Smart Greenhouse to easily record, store and manage crop production information such as crop growing information, growth environment and agriculture work log, Interest is growing. In this paper, we propose a system that collects the situation information necessary for growth such as temperature, humidity, solar radiation, CO2 concentration, and monitor the collected data, which can be measured in the rhizosphere of the crop. We have developed a system that collects data such as temperature, humidity, radiation, and growth environment data, which are measured by data obtained from the rhizosphere measuring section of a growing crop and measured by a sensor, and transmitted to a wireless communication gateway of 400 MHz. We developed the integrated SW that can monitor the rhythm environment data and visualize the data by using cloud based data. We can monitor by graph format and data format for visualization of data. The existing smart farm managed crops and facilities using only the data within the farm, and this study suggested the most efficient growth environment by collecting and analyzing the weather and growth environment of the farms nationwide.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3962-3980
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• 2019

To deal with single sample face recognition, this paper presents a patch based semi-supervised linear regression (PSLR) algorithm, which draws facial variation information from unlabeled samples. Each facial image is divided into overlapped patches, and a regression model with mapping matrix will be constructed on each patch. Then, we adjust these matrices by mapping unlabeled patches to $[1,1,{\cdots},1]^T$. The solutions of all the mapping matrices are integrated into an overall objective function, which uses ${\ell}_{2,1}$-norm minimization constraints to improve discrimination ability of mapping matrices and reduce the impact of noise. After mapping matrices are computed, we adopt majority-voting strategy to classify the probe samples. To further learn the discrimination information between probe samples and obtain more robust mapping matrices, we also propose a multistage PSLR (MPSLR) algorithm, which iteratively updates the training dataset by adding those reliably labeled probe samples into it. The effectiveness of our approaches is evaluated using three public facial databases. Experimental results prove that our approaches are robust to illumination, expression and occlusion.

• Journal of Food Hygiene and Safety
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• v.34 no.1
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• pp.40-51
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• 2019

Ginseng has a unique production system that is different from those used for other crops. It is subject to the Ginseng Industry Act., requires a long-term cultivation period of 4-6 years, involves complicated cultivation characteristics whereby ginseng is not produced in a single location, and many ginseng farmers engage in mixed-farming. Therefore, to bring the production of Ginseng in line with GAP standards, it is necessary to better understand the on-site practices of Ginseng farmers according to established control points, and to provide a proper action plan for improving efficiency. Among ginseng farmers in Korea who applied for GAP certification, 77.6% obtained it, which is lower than the 94.1% of farmers who obtained certification for other products. 13.7% of the applicants were judged to be unsuitable during document review due to their use of unregistered pesticides and soil heavy metals. Another 8.7% of applicants failed to obtain certification due to inadequate management results. This is a considerably higher rate of failure than the 5.3% incompatibility of document inspection and 0.6% incompatibility of on-site inspection, which suggests that it is relatively more difficult to obtain GAP certification for ginseng farming than for other crops. Ginseng farmers were given an average of 2.65 points out of 10 essential control points and a total 72 control points, which was slightly lower than the 2.81 points obtained for other crops. In particular, ginseng farmers were given an average of 1.96 points in the evaluation of compliance with the safe use standards for pesticides, which was much lower than the average of 2.95 points for other crops. Therefore, it is necessary to train ginseng farmers to comply with the safe use of pesticides. In the other essential control points, the ginseng farmers were rated at an average of 2.33 points, lower than the 2.58 points given for other crops. Several other areas of compliance in which the ginseng farmers also rated low in comparison to other crops were found. These inclued record keeping over 1 year, record of pesticide use, pesticide storages, posts harvest storage management, hand washing before and after work, hygiene related to work clothing, training of workers safety and hygiene, and written plan of hazard management. Also, among the total 72 control points, there are 12 control points (10 required, 2 recommended) that do not apply to ginseng. Therefore, it is considered inappropriate to conduct an effective evaluation of the ginseng production process based on the existing certification standards. In conclusion, differentiated certification standards are needed to expand GAP certification for ginseng farmers, and it is also necessary to develop programs that can be implemented in a more systematic and field-oriented manner to provide the farmers with proper GAP management education.

• Journal of Information Processing Systems
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• v.14 no.3
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• pp.655-665
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• 2018

In efforts to increase its agricultural productivity, the Indonesian Center for Agricultural Biotechnology and Genetic Resources Research and Development has conducted a variety of genomic studies using high-throughput DNA genotyping and sequencing. The large quantity of data (big data) produced by these biotechnologies require high performance data management system to store, backup, and secure data. Additionally, these genetic studies are computationally demanding, requiring high performance processors and memory for data processing and analysis. Reliable network connectivity with large bandwidth to transfer data is essential as well as database applications and statistical tools that include cleaning, quality control, querying based on specific criteria, and exporting to various formats that are important for generating high yield varieties of crops and improving future agricultural strategies. This manuscript presents a reliable, secure, and scalable information technology infrastructure tailored to Indonesian agriculture genotyping studies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.287-288
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• 2021

There is a growing interest in plant factories around the world, and in recent years, research on an automated management system that can grow crops even in an urban environment is in progress. The development of this management system is based on the development of ICT (Information Communications Technology) technology, and research is being conducted focusing on facilities, light sources, temperature, humidity and automation to increase the productivity of plants. Research on standardization is ongoing. In this paper, by constructing a test bed that can grow hydroponic ginseng in a container environment, we propose a model that can monitor and manage the environment for the growth process on mobile.

• Korean journal of applied entomology
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• v.62 no.4
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• pp.221-225
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• 2023

A female specimen of Sternuchopsis (s. str.) waltoni (Boheman, 1844), belonging to the tribe Mecysolobini (Curculionidae: Molytinae), was collected by beating method from Gadeok-do in Busan, the southern part of the Korean Peninsula. This weevil pest is designated as a quarantine pest under the Plant Quarantine Act (2019) in Korea. It is considered unreasonable to determine whether this species is an invasive or native species in Korea, as damage to crops has not been confirmed and there is no other collection information. This study aims to provide accurate diagnosis information including illustration and ecological information to gain more domestic occurrence information on this weevil.

• Journal of Practical Agriculture & Fisheries Research
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• v.26 no.2
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• pp.14-24
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• 2024

To enhance the usability of smart agriculture, methods for utilizing smart farm data are required. Therefore, this study proposes a scheme for utilizing regional smart farm data by linking it to services. The current status of domestic and foreign smart farm data collection and linkage services is analyzed. To collect and link regional smart farm data, necessary data collection, data cleaning, data storage structure and schema, and data storage and linkage systems are proposed. Based on the standards currently being implemented for regional smart farm internal data storage, a farm schema, environmental information schema, facility control information schema, and growth information schema are designed by extending the crop schema and crop main environmental factor information database schema. A data collection and management system structure based on the Hadoop Ecosystem is designed for data collection and management at regional smart farm data centers. Strategies are proposed for utilizing regional smart farm data to provide smart farm productivity improvement and revenue optimization services, image-based crop analysis services, and virtual reality-based smart farm simulation services.

• Journal of Plant Biotechnology
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• v.44 no.4
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• pp.438-447
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• 2017

Flowering is one of the most important development traits related to the production of Brassica rapa crops. After planting, a sudden low temperature triggers premature flowering, which leads to a reduction in the yield and quality of harvested production. Therefore, understanding the mechanism of flowering control is important in the agricultural productivity for preventing Brassica rapa crops. Vernalization is generally known as the main factor of flowering in the Brassica plant. However, in the subspecies of Brassica rapa, some accession such as Yellow sarson and Komatsuna display the flowering phenotype without vernalization. Circadian genes, which diurnally regulate plant physiology, have a role for photoperiodic flowering but are related to the regulation of the vernalizarion mechanism. In this report, the 22 B. rapa accession were divided into two groups, vernalization and non-vernalization, and the sequenced circadian gene, BrPRR1s. Among them, the BrPRR1b gene was found to have deletion regions, which could classify the two groups. The PCR primer was designed to amplify a short band of 422bp in the vernalization type and a long band of 451bp in the non-vernalization type. This primer set was applied to distinguish the flowering types in the 43 B. rapa accession and 4 Brassica genus crop, Broccoli, cabbage, mustard, and rape. The PCR analysis results and flowering time information of each crop demonstrated that the primer set can be used as marker to discern the flowering type in Brassica crops. This marker system can be applied to the B. rapa breeding when selecting the flowering character of new progenies or introducing varieties at an early stage. In addition, these results displayed that the circadian clock genes can be a good strategy for the flowering control of B. rapa crops.

• Korean Journal of Remote Sensing
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• v.25 no.5
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• pp.411-421
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• 2009

This study refers to develop a semi-automatic extraction of agricultural land use and vegetation information using high resolution satellite images. Data of IKONOS-2 satellite images (May 25 of 2001, December 25 of 2001, and October 23 of 2003), QuickBird-2 satellite images (May 1 of 2006 and November 17 of 2004) and KOMPSAT-2 satellite image (September 17 of 2007) which resemble with the spatial resolution and spectral characteristics of KOMPSAT-3 were used. The precise agricultural land use classification was tried using ISODATA unsupervised classification technique, and the result was compared with on-screen digitizing land use accompanying with field investigation. For the extraction of crop growth information, three crops of paddy, com and red pepper were selected, and the spectral characteristics were collected during each growing period using ground spectroradiometer. The vegetation indices viz. RVI, NDVI, ARVI, and SAVI for the crops were evaluated. The evaluation process was developed using the ERDAS IMAGINE Spatial Modeler Tool.

• Journal of Plant Biotechnology
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• v.44 no.1
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• pp.97-106
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• 2017

Living modified crops are genetically modified living organisms and are widely used in biotechnical research and desired goods. As the reliance on LM products, concerns about safety of LMOs have been continuously increased in South Korea. We established the detection methods for unintentional released LMOs in environmental conditions. To detect six LM event genes of 1 canola, 1 maize and 4 soybeans, PCR conditions were based upon consideration of the Joint Research Centre information. Genomic DNAs were isolated from LM samples and PCR analysis were performed using each event-specific primer pair. Event-specific genes of all events were efficiently recognized by our methods. To investigate the insertion site of LM genes in each genome, we verified PCR product sequence by DNA sequencing. These results suggest that the LM event-specific gene amplification can be efficiently developed. In addition, our detection method is fit for monitoring and post-management of LM crops in the environment.