Bellflower is an edible ornamental gardening plant in Asia. For predicting the flower color in bellflower plants, a transcriptome-wide approach based on machine learning, transcriptome, and genotyping chip analyses was used to identify SNP markers. Six machine learning methods were deployed to explore the classification potential of the selected SNPs as features in two datasets, namely training (60 RNA-Seq samples) and validation (480 Fluidigm chip samples). SNP selection was performed in sequential order. Firstly, 96 SNPs were selected from the transcriptome-wide SNPs using the principal compound analysis (PCA). Then, 9 among 96 SNPs were later identified using the Random forest based feature selection method from the Fluidigm chip dataset. Among six machines, the random forest (RF) model produced higher classification performance than the other models. The 9 SNP marker candidates selected for classifying the flower color classification were verified using the genomic DNA PCR with Sanger sequencing. Our results suggest that this methodology could be used for future selection of breeding traits even though the plant accessions are highly heterogeneous.

Cirsium japonicum (C. japonicum) is an important oriental herb belonging to the family Asteraceae. The C. japonicum complete chloroplast genome is composed of 152,606 bp, which form a large single-copy region (LSC, 83,492 bp), a small single-copy region (SSC, 18,772 bp), and 2 inverted repeats (IRs, 25,196 bp). There are 114 genes annotated, including 80 protein-coding genes, 4 ribosomal RNA genes, and 30 transfer RNA genes. Our phylogenetic analysis suggests that C. japonicum is closely related to the Cirsium genus of the Asteraceae family, and that C. japonicum (subfamily: Carduoideae) is separate from the Asteroideae subfamily.

Using 10,625 valid patents registered among six countries and 6,949 plant varieties registered in Korea, we evaluated technology trends in the horticultural seed industry. The six patent indices were investigated to determine the technology stage, such as market capability, technological level, and technological development potential, for different types of crop seeds. In addition, a patent multilayer (PM) model was developed based on vacant technology, future growth, and entry barriers to predict the best directions for technology development. In Korea, seed technologies for horticultural crops have low growth potential, although they are at a mature developmental stage and do not have high market concentration. There is high market competitiveness and development potential for flower seed technologies, whereas technologies for fruit seeds are in a decreasing developmental stage.

No abstract