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http://dx.doi.org/10.9723/jksiis.2020.25.5.083

Implementing a Web-based Seed Phenotype Trait Visualization Support System  

Yang, OhSeok (군산대학교 컴퓨터정보공학과)
Choi, SangMin (군산대학교 컴퓨터정보공학과)
Seo, DongWoo (군산대학교 컴퓨터정보공학과)
Choi, SeungHo (군산대학교 컴퓨터정보공학과)
Kim, YoungUk (군산대학교 컴퓨터정보공학과)
Lee, ChangWoo (군산대학교 컴퓨터정보공학과)
Lee, EunGyeong (국립농업과학원 유전자공학과)
Baek, JeongHo (국립농업과학원 유전자공학과)
Kim, KyungHwan (국립농업과학원 유전자공학과)
Lee, HongRo (군산대학교 컴퓨터정보공학과)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.25, no.5, 2020 , pp. 83-90 More about this Journal
Abstract
In this paper, a web-based seed phenotype visualization support system is proposed to extract and visualize data such as the surface color, length, area, perimeter and compactness of seed, which is phenotype information from the image of soybean/rice seeds. This system systematically stores data extracted from seeds in databases, and provides a web-based user interface that facilitates the analysis of data by researchers using data tables and charts. Conventional seed characteristic studies have been manually measured by humans, but the system developed in this paper allows researchers to simply upload seed images for analysis and obtain seed's numerical data after image processing. It is expected that the proposed system will be able to obtain time efficiency and remove spatial restriction, if it is used in seed characterization research, and it will be easy to analyze through systematic management of research results and visualization of the phenotype characteristics.
Keywords
Seed; Phenotype; Web; User interface; Visualization;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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1 Baek, J. H., Lee, E. Y., Kim, N. H., Lee, H. S., Kim, S. L., Choi, I. C., Ji, H. S., and Kim, K. H. (2019). Development of Seed Traits Information Extraction Program, The 46th Annual Conference of the Korean Association of Information and Communication, Oct, 24-26, Busan, Korea, 23(2), pp. 569-571
2 Baek, J. H., Lee, E. Y., Kim, N. H., Kim, S. L., Choi, I. C. Ji, H. S., Chung, Y. S., Choi, M. S., Moon, J. K., and Kim, K. H. (2020). Development of Seed Traits Information Extraction Program, Sensors, 20(248), https://doi.org/10.3390/s20010248
3 Herridge, R.P., Day, R.C., Baldwin, S., and Macknight, R. C. (2011). Rapid Analysis of Seed Size in Arabidopsis for Mutant and QTL Discovery, Plant Methods, 7(3), https://plantmethods.biomedcentral.com/articles/10.1186/1746-4811-7-3
4 Jo, J, W., Lee, M. H., Lee, H. R., Chung, Y. S., Baek, J. H., Kim, K. H., and Lee, C. W. (2019). LeafNet: Plants Segmentation using CNN, Journal of the Korea Industrial Information Systems Research, 24(4), 1-8   DOI
5 Joo J. Y. (2020). Potentiality in Plant (seed), Pohang, BRIC.
6 Kim, D. S., Lee, T. Y., and Kim, J. W. (2015). Improving Crop Breeding Efficiency using Plant Expression Technology, 2015 Joint Symposium on the Korea Seed Society, Next Generation BG21 Project Group and Golden Seed Project Group, Jul, 1-3, Gwangju, Korea,
7 Kim, S. L., Kim N. H., Lee, H. S., Lee. E. Y., Cheon, K. S., Kim. M. S., Baek J. H., Choi, I. C., Ji, H. S., Yoon, I. S., Jung, K. H., Kwon, T. R., and Kim, K. H. (2020). High‑Throughput Phenotyping Platform for Analyzing Drought Tolerance in Rice, Planta 252(38), https://doi.org/10.1007/s00425-020-03436-9
8 Lee, S. W. (2020). An Image Analysis-based Study of Soybean Seed Expressions. News of the Korea Soybean Society, 345(0), 5-7.
9 Sagendorf, J. M., Markarian, N., Berman, H. M., and Rohs, R. (2020). DNAproDB: An Expanded Database and Web-based Tool for Structural Analysis of DNA-protein Complexes, Nucleic Acids Research, 48(D1), D277-D287.
10 Rose, A. S., and Hildebrand, P. W. (2015) NGL Viewer: A Web Application for Molecular Visualization, Nucleic Acids Res, 43, W576-W579.   DOI
11 Shin, H. J., Lee, S, I., Chung, H. W., and Park, J. W. (2020). Indoor Plants Image Classification using Deep Learning and Web Application for Providing Information of Plants, Journal of the Korean Association of Knowledge Information Technology, 15(2), 167-175
12 Vollmann, J., Walter, H., Sato, T., and Schweiger, P. (2011). Digital Image Analysis and Chlorophyll Metering for Phenotyping the Effects of Nodulation in Soybean, Computers and Electronics in Agriculture, 75(1), 190-195.   DOI