Comparison of Various Drought Resistance Traits in Soybean (<i>Glycine max</i> L.) Based on Image Analysis for Precision Agriculture

Drought is being annually exacerbated by recent global warming, leading to crucial damage of crop growth and final yields. Soybean, one of the most consumed crops worldwide, has also been affected in the process. The development of a resistant cultivar is required to solve this problem, which is considered the most efficient method for crop producers. To accelerate breeding cycles, genetic engineering and high-throughput phenotyping technologies have replaced conventional breeding methods. However, the current novel phenotyping method still needs to be optimized by species and varieties. Therefore, we aimed to assess the most appropriate and effective phenotypes for evaluating drought stress by applying a high-throughput image-based method on the nested association mapping (NAM) population of soybeans. The acquired image-based traits from the phenotyping platform were divided into three large categories—area, boundary, and color—and demonstrated an aspect for each characteristic. Analysis on categorized traits interpreted stress responses in morphological and physiological changes. The evaluation of drought stress regardless of varieties was possible by combining various image-based traits. We might suggest that a combination of image-based traits obtained using computer vision can be more efficient than using only one trait for the precision agriculture

New method for detecting Collectorichum species found in Korea using image analysis

Colletotrichum acutatum spp. infects various economical crops worldwide and causes massive loss on their yields. Among those, Capsicum spp., which known as chili pepper, is on a critical issue by those pathogens. Due to the lack of their genetic markers in Korea, the unidentifiable various species of C. acutatum obstructs the mechanism studies of these pathogens and the selection of disease resistant breed lines. Therefore, we screened RGB images of the colonization progresses of pathogens to identify the species of Ca40042, K1, NN, AS2, and SW1 by time and temperature. Cultivated pathogens such as Ca40042, K1, and SW1 were detectable on quantified shape and color data of images from specific temperature conditions, while other pathogens were difficult to recognize. Although several limitations exist in identification results of current experiment, but also, we can expect this method can suggest the possibility to replace the genetic marker methods which is now unavailable in Korea

High Throughput Phenotyping for Various Traits on Soybean Seeds Using Image Analysis

Data phenotyping traits on soybean seeds such as shape and color has been obscure because it is difficult to define them clearly. Further, it takes too much time and effort to have sufficient number of samplings especially length and width. These difficulties prevented seed morphology to be incorporated into efficient breeding program. Here, we propose methods for an image acquisition, a data processing, and analysis for the morphology and color of soybean seeds by high-throughput method using images analysis. As results, quantitative values for colors and various types of morphological traits could be screened to create a standard for subsequent evaluation of the genotype. Phenotyping method in the current study could define the morphology and color of soybean seeds in highly accurate and reliable manner. Further, this method enables the measurement and analysis of large amounts of plant seed phenotype data in a short time, which was not possible before. Fast and precise phenotype data obtained here may facilitate Genome Wide Association Study for the gene function analysis as well as for development of the elite varieties having desirable seed traits

Rice Genome Resequencing Reveals a Major Quantitative Trait Locus for Resistance to Bakanae Disease Caused by <i>Fusarium fujikuroi</i>

Bakanae disease (BD), caused by the fungal pathogen Fusarium fujikuroi, has become a serious threat in rice-cultivating regions worldwide. In the present study, quantitative trait locus (QTL) mapping was performed using F2 and F3 plants derived after crossing a BD-resistant and a BD-susceptible Korean japonica rice variety, &#8216;Samgwang&#8217; and &#8216;Junam&#8217;, respectively. Resequencing of &#8216;Junam&#8217; and &#8216;Samgwang&#8217; genomes revealed 151,916 DNA polymorphisms between the two varieties. After genotyping 188 F2 plants, we constructed a genetic map comprising 184 markers, including 175 kompetitive allele-specific PCR markers, eight cleaved amplified polymorphic sequence (CAPS) markers, and a derived CAPS (dCAPS) marker. The degree of BD susceptibility of each F2 plant was evaluated on the basis of the mortality rate measured with corresponding F3 progeny seedlings by in vitro screening. Consequently, qFfR9, a major QTL, was discovered at 30.1 centimorgan (cM) on chromosome 9 with a logarithm of the odds score of 60.3. For the QTL interval, 95% probability lay within a 7.24&#8722;7.56 Mbp interval. In this interval, we found that eight genes exhibited non-synonymous single nucleotide polymorphisms (SNPs) by comparing the &#8216;Junam&#8217; and &#8216;Samgwang&#8217; genome sequence data, and are possibly candidate genes for qFfR9; therefore, qFfR9 could be utilized as a valuable resource for breeding BD-resistant rice varieties

New Parameters for Seedling Vigor Developed via Phenomics

Early seedling establishment in rice (Oryza sativa L.), which is measured by primary/secondary tiller, shoot length, biomass, root-related traits, and leaf area index, is an important trait because it helps to compete for light, air, and water for better tolerating various abiotic stresses. Consequently, it can affect the yield. However, there are not many research studies on this subject. Furthermore, previous studies have only measured the target traits once. However, this does not reflect the variation of growth rate during the seedling stage. Thus, two data points, two weeks and four weeks after planting, were used in the current study. As a result, two QTL regions were detected for the growth differences via plant height and green area (reflecting tillering). We expect that these results can be utilized by breeders to evaluate and select vigorous seedlings for their breeding programs