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Improvement of Resistance to Late Blight in Hybrid Tomato
박덕환,Yan Zhang,김병섭 한국원예학회 2014 Horticulture, Environment, and Biotechnology Vol.55 No.2
Late blight is one of the major diseases in tomato cultivated both in the greenhouse and the field. In thiswork, we determined the resistance levels of all progeny lines (F1 to F3) and a new variety (NV) F1 to the late blightdisease fungus to evaluate these hybrid lines as potential sources of resistance. The experiments were carried out ingreenhouse conditions in a completely randomized block design with three replications. Fifteen out of 204 F2 plantsof cross A (AV107-4 × L3708) and 13 out of 203 F2 plants of cross B (Campari × 917 × L3708) were found to beresistant to late blight in combined data from greenhouse trials. In addition, 5 resistant F3 lines derived from each ofthe two crosses A and B were selected for further investigation. By screening the NV F1 hybrids obtained by pollinationof the F3 lines by 3 male-sterile cultivars (Wonung-1, 2, and 3), two stable resistant hybrids, Wonung-2 × A120 andWonung-3 × B23, were finally produced. An examination of the qualitative characters in the NV F1 hybrids indicatedimproved fruit weight and quality. Taken together, our screening results indicate that both of these hybrids are goodsources of resistance and have high-value horticultural characters, which can be used for tomato breeding programs.
커리큘럼 학습을 통한 원시 단일 채널 EEG 의 자동 수면 단계 분류 성능 향상
박덕환,이성주,백승혁,이규빈 제어로봇시스템학회 2021 제어로봇시스템학회 국내학술대회 논문집 Vol.2021 No.6
This paper presents a curriculum learning method to improve sleep scoring performance of the deep neural network on raw single-channel EEG. Although deep neural networks have shown remarkable results on automatic sleep scoring, the remaining problem is that N1 and REM stages are hard to be distinguished due to their similar frequency characteristics. To solve this problem, we propose curriculum learning method for automatic sleep scoring; a deep neural network is trained in three phases which are in order of sleep scoring difficulty. The network is trained with three sleep stages (Wake, Non-REM, REM), four sleep stages (Wake, Light Sleep, Deep Sleep, REM), and five sleep stages (Wake, N1, N2, N3, REM) in Phase 1, Phase 2, and Phase 3, respectively. We compared the sleep scoring performance w/ and w/o curriculum learning for three deep neural networks from prior works and two different EEG channels. As the effect of curriculum learning, the overall performance has been enhanced maximum 1.7%p, 2.1%p, 0.022 in ACC, MF1, Kappa, respectively. Especially, per-class F1-scores of N1 and REM have been increased maximum 2.4%p and 2.8%p, respectively.
Erwinia carotovora subsp. carotora에 의한 고추냉이(와사비) 세균성 무름병
박덕환,서상태,최준근,임춘근 한국식물병리학회 1998 Plant Pathology Journal Vol.14 No.5
Occurrence of soft rots was observed on wasabi (Wasabia japonica Matsum) grown in Chuncheon and Pyengchang Kangwon province, Korea. The symptoms appeared on the wasabi root, which became mushy and black. This eventually resulted in wilting and death of the aboveground parts of the wasabi. The causal organism was isolated from the infected lesions and was identified as Erwinia carotovora subsp. carotovora based on the morphological, physiological and biochemical characteristics, and on the results of the Biolog program (Biolog Inc., U. S. A.). E. carotovora subsp. carotovora is the first described bacterium which causes bacterial soft rot on wasabi in Korea.
Erwinia carotovora subsp. carotovora에 의한 비트 세균성 무름병
박덕환,원선영,황수경,원선영,임춘근 한국식물병리학회 1998 Plant Pathology Journal Vol.14 No.5
Bacterial soft rot caused damage to beets massively grown in Pyungchang, Kangwon province, Korea. The affected roots and stems became cream colored and slimy, and turned black, causing the plants to become wilt and die. The casual organism isolated from the infected plants was identified as Erinia carotovora subsp. carotovora based on physiological and biochemical characteristic, and the results of the Biolog program (Biolog Inc., U.S.A.). E. carotovora subsp. carotovora is the first discribed bacterium which causes bacterial soft rot on beet in Korea.
박덕환,Shree Prasad Thapa,김원식,허장현,임춘근 한국식물병리학회 2010 Plant Pathology Journal Vol.26 No.3
We designed a sensitive and specific PCR-based method with enterobacterial repetitive intergenic consensus (ERIC) primer to detect Erwinia pyrifoliae, which cause shoot blight in Asian pear, from a mixed culture and infected plant materials. The primers specifically detected only E. pyrifoliae and showed no cross-reactivity with other bacterial phytopathogens.