【摘要】 目前研究所获得的抑制烟草青枯病的微生物以细菌为主,放线菌(Actinobacteria)较少。本研究拟筛选可用于研制和生产防治烟草青枯病生物有机肥的放线菌,确定其分类地位。首先采用抑菌圈测定法从烟草(Nicotiana tabacum)根际土中筛选烟草青枯病拮抗放线菌,然后通过其表型特征、生理生化特征和遗传特征等多相分析来确定分类地位。结果显示,共筛选获得3株对烟草青枯病原菌(Ralstonia solanacearum)拮抗效果良好的放线菌,3株放线菌同时对烟草赤星病病原菌(Alternaria alternata)及辣椒(Capsicum annuum)、番茄(Solanum lycopersicum)和马铃薯(Solanum tuberosum)等茄科类植物青枯病原菌具有抑制作用。3株放线菌中,菌株SC-105-B-10属于细黄链霉菌(Streptomyce microflavus, GenBank No.KT633863),菌株L2-003-A-5属于微白黄链霉菌(Streptomyces albidoflavus, GenBank No. KT119348),SC-168-A-2属于链霉菌属的Streptomyces pratensis (GenBank No. KR140205)。本研究筛选获得3株放线菌,具有用于研制防治烟草青枯病生物有机肥的潜力。更多还原

【Abstract】 At present, bacteria are the main microorganisms to inhibit tobacco bacterial wilt, and Actinobacteria are few. In this study, Actinobacteria, which can be used to develop and produce bio organic fertilizer for controlling tobacco bacterial wilt, were screened to determine their taxonomic status. Firstly,antagonistic Actinobacteria against tobacco bacterial wilt were screened from tobacco(Nicotiana tabacum)rhizosphere soil by the method of inhibition zone assessment. The taxonomic status of antagonistic Actinobacteria was determined by polyphase analysis of phenotypic and physio biochemical characterizations,in combination with genetic characteristics. The results showed that 3 Actinobacterial strains with good antagonistic effect against tobacco bacterial wilt were obtained, and the 3 Actinobacterial strains could inhibit the pathogen of tobacco brown spot disease(Alternaria alternata) and other bacterial wilt pathogens of Solanaceae plants such as capsicum(Capsicum annuum), tomato(Solanum lycopersicum) and potato(Solanum tuberosum). In the 3 strains, SC-105-B-10(GenBank No. KT633863) belonged to Streptomyces microflavus, L2-003-A-5(GenBank No. KT119348) belonged to Streptomyces albidoflavus, and SC-168-A-2 belonged to Streptomyces pratensis(GenBank No. KR140205). This study obtained 3 Actinobacterial strains, which have potential for the development of bio-organic fertilizer for controlling tobacco bacterial wilt.更多还原