작물 표현체 플랫폼 기반 벼 이미지 분석 조건 확립
Determination of the Conditions for Image Analysis of Rice Based on a Crop Phenomic Platform
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다운로드
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참고문헌
키워드
초록
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.
Abstract
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.
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