The use of digital cameras in plant phenotyping studies using RGB sensors has increased. However, the need for standardization has become apparent because of the diverse analytical approaches used by individual researchers. In this study, we optimized the image acquisition conditions for apples, including scaling tool positioning, lighting conditions, and background color selection. In addition, we developed an ImageJ-based automated image acquisition and analysis program. We generated 240 images of four apple cultivars (Hongan, Hongro, Fuji, and Hwangok) and used 12 image indices to analyze the fruit size, width, length, and shape. We measured the accuracy by comparing the results with actual measurements. Significantly high correlation values were observed between fruit width and the major index (R2=0.947-0.993) as well as between fruit length and the height index (R2=0.964-0.984) based on the analysis using R-squared values to assess accuracy. These findings are expected to enhance the efficiency of apple fruit sorting in the future and can be applied to investigate the shapes of other fruits.
A new garden chrysanthemum (
Many studies concerning breeding maize varieties are in progress in Korea and other countries. Double haploid technology is widely used for the development of commercial maize varieties worldwide, and has also been utilized in Korea since its introduction by the Maize Research Institute, Gangwondo. We performed a study to improve the efficiency of selecting haploid maize seeds using fluorescence imaging. It was verified that anthocyanin produced by the expression of
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 images using 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 LED lights in a blue background. Based on this condition, images from 96 individual plants of rice Dongjin cultivar were obtained every week to measure plant height and shoot area, which are directly associated with yield. The results obtained from the image analysis were compared with the manually collected results. The r2 value between the projected plant height obtained from image analysis and the plant height obtained from manual measurement was 0.989. Furthermore, the r2 value between the projected shoot area obtained from image analysis and the shoot area 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.
A dwarf mutant rice line was selected from an Ac/Ds insertion mutant population and named
Perilla is an oilseed crop cultivated in Korea since ancient times. Due to the high α-linolenic acid content in perilla, perilla seed oil can easily become rancid. α-Linolenic acid is synthesized by two enzymes, endoplasmic reticulum-localized Δ15 desaturase (FAD3) and chloroplast-localized Δ15 desaturase (FAD7) in vivo. In order to lower the α-linolenic acid content of the seed oil without disturbing plant growth, we tried to suppress the expression of only the