【目的】挖掘烟草黑胫病的生防资源,通过试验对前期分离到的2株生防菌进行种类鉴定和防治效果测定。【方法】根据其形态学、生理生化特征和16 S rDNA序列分析,YCYM-04菌株被鉴定为嗜麦芽寡养单胞菌(Stenotrophomonas maltophilia),YCYM...【目的】挖掘烟草黑胫病的生防资源,通过试验对前期分离到的2株生防菌进行种类鉴定和防治效果测定。【方法】根据其形态学、生理生化特征和16 S rDNA序列分析,YCYM-04菌株被鉴定为嗜麦芽寡养单胞菌(Stenotrophomonas maltophilia),YCYM-09菌株被鉴定为贝莱斯芽孢杆菌(Bacillus velezensis)。【结果】平板对峙结果显示,YCYM-04菌株和YCYM-09菌株对烟草疫霉的抑菌带分别达13.7和8.9 mm。此外,YCYM-04菌株和YCYM-09菌株发酵滤液5倍稀释液菌落抑菌率分别达71.8%和50.6%;YCYM-04菌株发酵滤液造成烟草疫霉菌丝节间缩短、断裂、生长缓慢等现象,YCYM-09菌株发酵滤液造成烟草疫霉菌丝体膨大、增粗、畸形、原生质体凝结。盆栽试验表明,YCYM-04菌株和YCYM-09菌株培养液灌根处理对烟草黑胫病的防治效果分别达50.5%和61.5%。【结论】YCYM-04和YCYM-09菌株在烟草黑胫病的生物防治上具有潜在的应用价值。展开更多
The identification of key nodes plays an important role in improving the robustness of the transportation network.For different types of transportation networks,the effect of the same identification method may be diff...The identification of key nodes plays an important role in improving the robustness of the transportation network.For different types of transportation networks,the effect of the same identification method may be different.It is of practical significance to study the key nodes identification methods corresponding to various types of transportation networks.Based on the knowledge of complex networks,the metro networks and the bus networks are selected as the objects,and the key nodes are identified by the node degree identification method,the neighbor node degree identification method,the weighted k-shell degree neighborhood identification method(KSD),the degree k-shell identification method(DKS),and the degree k-shell neighborhood identification method(DKSN).Take the network efficiency and the largest connected subgraph as the effective indicators.The results show that the KSD identification method that comprehensively considers the elements has the best recognition effect and has certain practical significance.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.61961019)the Youth Key Project of the Natural Science Foundation of Jiangxi Province of China(Grant No.20202ACBL212003).
文摘The identification of key nodes plays an important role in improving the robustness of the transportation network.For different types of transportation networks,the effect of the same identification method may be different.It is of practical significance to study the key nodes identification methods corresponding to various types of transportation networks.Based on the knowledge of complex networks,the metro networks and the bus networks are selected as the objects,and the key nodes are identified by the node degree identification method,the neighbor node degree identification method,the weighted k-shell degree neighborhood identification method(KSD),the degree k-shell identification method(DKS),and the degree k-shell neighborhood identification method(DKSN).Take the network efficiency and the largest connected subgraph as the effective indicators.The results show that the KSD identification method that comprehensively considers the elements has the best recognition effect and has certain practical significance.
