- 著者
- Shin Taketa June-Sik Kim Hidekazu Takahashi Shunsuke Yajima Yuichi Koshiishi Toshinori Sotome Tsuneo Kato Keiichi Mochida
- 出版者
- Japanese Society of Breeding
- 雑誌
- Breeding Science (ISSN:13447610)
- 巻号頁・発行日
- vol.73, no.5, pp.435-444, 2023 (Released:2023-12-21)
- 参考文献数
- 52
Two modern high-quality Japanese malting barley cultivars, ‘Sukai Golden’ and ‘Sachiho Golden’, were subjected to RNA-sequencing of transcripts extracted from 20-day-old immature seeds. Despite their close relation, 2,419 Sukai Golden-specific and 3,058 Sachiho Golden-specific SNPs were detected in comparison to the genome sequences of two reference cultivars: ‘Morex’ and ‘Haruna Nijo’. Two single nucleotide polymorphism (SNP) clusters respectively showing the incorporation of (1) the barley yellow mosaic virus (BaYMV) resistance gene rym5 from six-row non-malting Chinese landrace Mokusekko 3 on the long arm of 3H, and (2) the anthocyanin-less ant2 gene from a two-row Dutch cultivar on the long arm of 2H were detected specifically in ‘Sukai Golden’. Using 221 recombinant inbred lines of a cross between ‘Ishukushirazu’ and ‘Nishinochikara’, another BaYMV resistance rym3 gene derived from six-row non-malting Japanese cultivar ‘Haganemugi’ was mapped to a 0.4-cM interval on the proximal region of 5H. Haplotype analysis of progenitor accessions of the two modern malting cultivars revealed that rym3 of ‘Haganemugi’ was independently introduced into ‘Sukai Golden’ and ‘Sachiho Golden’. Residual chromosome 5H segments of ‘Haganemugi’ surrounding rym3 were larger in ‘Sukai Golden’. Available results suggest possibilities for malting quality improvement by minimizing residual segments surrounding rym3.
- 著者
- Toshiyuki Hagiya Tsuneo Kato
- 出版者
- 一般社団法人 情報処理学会
- 雑誌
- Journal of Information Processing (ISSN:18826652)
- 巻号頁・発行日
- vol.22, no.2, pp.410-416, 2014 (Released:2014-04-15)
- 参考文献数
- 25
- 被引用文献数
- 1
To provide an accurate and user-adaptable software keyboard for touchscreens, we propose a probabilistic flick keyboard based on hidden Markov models (HMMs). Touch and flick operations for each character are modeled by HMMs. This keyboard reduces input errors by taking the trajectory of the actual touch position into consideration and by user adaptation. We evaluated the performance of an HMM-based flick keyboard and maximum-likelihood linear regression (MLLR) adaptation. Experimental results showed that a user-dependent model reduced the error rate by 28.3%. In a practical setting, the MLLR adaptation to a specific user with only 10 words reduced the error rate by 16.6% and increased the typing speed by 11.9%.