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.

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 R1-nj gene can be detected by fluorescence imaging, and we developed a high-throughput method for discriminating between haploid and diploid seeds. Compared with discriminating with naked eye, this method reduced the time for discriminating haploid and diploid maize by 91.7% and increased selection accuracy by 16.8% for haploid and 2.2% for diploid maize. This method enabled the acquisition of more haploid seeds and improved the efficiency of breeding research by shortening the time involved.

To improve the seed purity management system of Korean wheat cultivars, 50 Korean wheat cultivars were subjected to chemical assays for grain color, genotyping of grain weight-related genes, and grain image analysis. The tested cultivars were primarily classified by NaOH and ninhydrin tests as white (26%) and red (74%) cultivars, as well as high PPO activity (48%), and low PPO activity (52%) cultivars, respectively. The allelic variations of Tamyb10 gene revealed Tamyb-A1a/Tamyb-B1a/Tamyb-D1a as the major allelic combination in white wheat and five different Tamyb10 genotypes (i.e., aba, abb, baa, bba, and bbb) in red wheat. Those cultivars with high PPO activity possessed the Ppo-A1a/Ppo-B1b/Ppo-D1b genotype, while those with low PPO activity possessed the Ppo-A1b/Ppo-B1a/Ppo-D1a genotype. In the grain image analysis, long grain cultivars displayed increased grain width, circularity, and area. Based on cluster analysis of grain traits, the Korean wheat cultivars were classified into two groups - 1) large red grain cultivars released before 2000, and 2) small red grain cultivars and white wheat cultivars released after 2000. Further research is required to determine the effects of grain filling conditions on the grain characteristics of Korean wheat cultivars and to develop efficient and reliable molecular markers for an improved seed purity management system.

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.