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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2021.12
- 수록면
- 450 - 457 (8page)
- DOI
- 10.9787/KJBS.2021.53.4.450
이용수
초록· 키워드
오류제보하기
Fast and accurate selection is essential for breeding to cope with rapid climate changes and a steeply increasing population.
Consequently, technologies for high-throughput phenotyping (HTP) are emerging. These technologies, unlike conventional phenotyping methods,enable us to evaluate agronomic traits in a fast and massive manner. Thus, the HTP facility was built to acquire and analyze crop imagesusing RGB sensors at the National Institute of Agricultural Sciences, Republic of Korea. By testing various conditions to acquire images,we determined the conditions for phenotyping using the RGB sensor as follows: exposure 30,000 ms, gamma 75, and gain 100 using LEDlights in a blue background. Based on this condition, images from 96 individual plants of rice Dongjin cultivar were obtained every weekto measure plant height and shoot area, which are directly associated with yield. The results obtained from the image analysis were comparedwith the manually collected results. The r2 value between the projected plant height obtained from image analysis and the plant height obtainedfrom manual measurement was 0.989. Furthermore, the r2 value between the projected shoot area obtained from image analysis and the shootarea obtained from manual measurement was 0.981. These results show that image analysis is highly reliable and can be used for crop phenotyping.
Therefore, we expect that the new method we developed will be used for breeding in the near future.
목차
등록된 정보가 없습니다.
참고문헌 (35)
참고문헌 신청
Berger B / 2010 / High-throughput shoot imaging to study drought responses / J Exp Bot 61:3519~3528
Campbell MT / 2015 / Integrating image-based phenomics and association analysis to dissect the genetic architecture of temporal salinity responses in rice / Plant Physiol 168:1476~1489
Cao L / 2015 / Research on video image recognition technology of maize disease based on the fusion of genetic algorithm and simulink platform / 9th International Conference on Computer and Computing Technologies in Agriculture
Chen WY / 2005 / Efficient depth image based rendering with edge dependent depth filter and interpolation / International Conference on Multimedia and Expo
Chuanlei Z / 2017 / Apple leaf disease identification using genetic algorithm and correlation based feature selection method / IJABE 10:74~83
Campbell MT / 2015 / Integrating image-based phenomics and association analysis to dissect the genetic architecture of temporal salinity responses in rice / Plant Physiol 168:1476~1489
Cao L / 2015 / Research on video image recognition technology of maize disease based on the fusion of genetic algorithm and simulink platform / 9th International Conference on Computer and Computing Technologies in Agriculture
Chen WY / 2005 / Efficient depth image based rendering with edge dependent depth filter and interpolation / International Conference on Multimedia and Expo
Chuanlei Z / 2017 / Apple leaf disease identification using genetic algorithm and correlation based feature selection method / IJABE 10:74~83
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