DOI QR코드

DOI QR Code

A Study on the Image Analysis Technique for the Precision Exploration of Chili Anthracnose

고추 탄저병 정밀 탐색을 위한 영상분석 기술에 대한 연구

  • 백정호 (국립농업과학원 유전자공학과) ;
  • 김년희 (국립농업과학원 유전자공학과) ;
  • 이은경 (국립농업과학원 유전자공학과) ;
  • 이홍석 (국립식량과학원 생산기술개발과) ;
  • 김송림 (국립농업과학원 유전자공학과) ;
  • 박상렬 (국립농업과학원 유전체과) ;
  • 지현소 (국립농업과학원 유전자공학과) ;
  • 최인찬 (국립농업과학원 스마트팜개발과) ;
  • 김경환 (국립농업과학원 유전자공학과)
  • Received : 2020.09.09
  • Accepted : 2020.10.05
  • Published : 2020.10.31

Abstract

One of the most important vegetables consumed in Korea, chili peppers (Capsicum annuum) are widely cultivated around the world. Chili peppers have been severely damaged by anthracnose during their growth, so it is important to study prevention and resistance varieties. K1 anthracnose was inoculated against four cultivar of chili peppers that are resistant to anthracnose and one cultivar that is sensitive. The area of the disease that appeared over time was photographed and quantified through the program was analyzed. Through the ratio of the area of chili pepper fruit and the area of the bottle, the sensitive variety An-S showed weak reactions to anthracnose with about 40%, the resistant variety An-12R (23%), An-Tan (21%), and An-9R (19%), and PBC81 showed a strong response to anthracnose with about 11%. These quantitative value can be used as a basis for comparison in conducting resistance studies for new varieties.

전세계적으로 널리 재배되는 고추 (Capsicum annuum)는 한국에서 소비가 많은 채소류 중 매우 중요한 작물중 하나이다. 고추는 생육기간 동안에 고추 탄저병에 심한 피해를 입어 방제나 저항성 품종에 대한 연구가 중요하다. 본 연구에서는 탄저병에 저항성이 있는 고추 4품종과 민감성을 가진 1품종에 대해 K1탄저균을 접종하였으며, 시간이 지나면서 나타나는 병 면적을 촬영하여 프로그램을 통해 정량화한 내용을 분석하였다. 고추과일 면적과 병면적의 비율을 통해 감수성 품종인 An-S는 약 40%로 약하게 나타났으며, 저항성 품종인 An-12R (23%), AR-Tan (21%), An-9R (19%)로 비교적 강하게 나타났고, PBC81는 약 11%로 탄저균에 강한 병 반응을 보였다. 이와 같은 정량적인 수치는 탄저병 품종이나 탄저균에 대한 저항성 연구를 수행하는데 비교할 수 있는 기초자료로 활용할 수 있다.

Keywords

References

  1. BAEK, J., Lee, E., Kim, N., Kim, S. L., Choi, I., Ji, H., Chung, Y. S., Choi, M.-S., Moon, J.-K., and Kim, K.-H. (2020). High throughput Phenotyping for Various Traits on Soybean Seeds using Image Analysis, Sensors, 20(1), 248. https://doi.org/10.3390/s20010248
  2. Barka, G. D., and Lee, J. (2020). Molecular Marker Development and Gene Cloning for Diverse Disease Resistance in Pepper (Capsicum annuum L.): Current Status and Prospects, Plant Breed. Biotech., 8(2), 89-113. https://doi.org/10.9787/PBB.2020.8.2.89
  3. 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. https://doi.org/10.9723/JKSIIS.2019.24.4.001
  4. Khirade, S. D., and Patil, A. B. (2015). Plant Disease Detection using Image Processing, International Conference on Computing Communication Control and Automation, Pune, 768-771.
  5. Kim, K.-H., Yoon, J.-B., Park, H.-G., Park, E. W., and Kim, Y. H. (2004). Structural Modifications and Programmed Cell Death of Chili Pepper Fruit related to Resistance Responses to Colletotrichum Gloeosporioides Infection, Phytopathology 94, 1295-1304. https://doi.org/10.1094/PHYTO.2004.94.12.1295
  6. Kim, S. G., R, N.-Y., Hur, O.-S., Ko, H.-C., Gwag, J.-G., and Huh, Y.-C. (2012). Evaluation of Resistance to Colletotrichum Acutatum in Pepper Genetic Resources, Res. Plant Dis., 18(2), 93-100. https://doi.org/10.5423/RPD.2012.18.2.093
  7. Kim, S. L., Chung, Y, Silva, R. R., Ji, H., Lee, H., Choi, I., Kim N., Lee, E., Baek, J., Lee, G.-S., Kwon, T.-R., and Kim, K.-H. (2019). The Opening of Phenome-assisted Selection Era in the Early Seedling Stage, Scientific Reports, 9, 9948. https://doi.org/10.1038/s41598-019-46405-3
  8. Lee, W.-M., Yang, E. Y., Cho, M. C., Chae, S. Y., Choi, H. S., and Moon, J.-H. (2018). Breeding of Korean Red Pepper Variety 'Jeockyoung' with High Carotenoid Content, Korean J . Breed. Sci., 50(3), 302-306. https://doi.org/10.9787/KJBS.2018.50.3.302
  9. Lee, J. H., Kim, B. M., and Shin, Y. S. (2018). Effects of Preprocessing and Feature Extraction on CNN-based Fire Detection Performance, Journal of the Korea Industrial Information Systems Research, 23(4), 41-53. https://doi.org/10.9723/JKSIIS.2018.23.4.041
  10. Schneider, C. A., Rasband, W. S., and Eliceiri, K. W. (2012). NIH Image to ImageJ:25 Years of Image Analysis, Nat Methods, 9(7), 671-5. https://doi.org/10.1038/nmeth.2089
  11. Song, S., Kim, S., Jin, Y. S., and Lee, J. (2020). Enhancement Techniques of Color Segmentation for Detecting Missing Persons in Smart Lighting System using Radar and Camera Sensors, Journal of the Korea Industrial Information Systems Research, 25(3), 53-59. https://doi.org/10.9723/JKSIIS.2020.25.3.053
  12. Yoon, J. B., Do, J. W., Yang, D. C., and Park, H. G. (2004). Interspecific Cross Compatibility among Five Domesticated Species of Capsicum Genus, J. Korean Soc. Hort. Sci., 45, 324-329.