title: Threshold microsclerotial inoculum for cotton verticillium wilt determined through wet-sieving and real-time quantitative PCR.
abstract: Quantification of Verticillium dahliae microsclerotia is an important component of wilt management on a range of crops. Estimation of microsclerotia by dry or wet sieving and plating of soil samples on semiselective medium is a commonly used technique but this method is resource-intensive. We developed a new molecular quantification method based on Synergy Brands (SYBR) Green real-time quantitative polymerase chain reaction of wet-sieving samples (wet-sieving qPCR). This method can detect V. dahliae microsclerotia as low as 0.5 CFU g(-1) of soil. There was a high correlation (r=0.98) between the estimates of conventional plating analysis and the new wet-sieving qPCR method for 40 soil samples. To estimate the inoculum threshold for cotton wilt, >400 soil samples were taken from the rhizosphere of individual plants with or without visual wilt symptoms in experimental and commercial cotton fields at the boll-forming stage. Wilt inoculum was estimated using the wet-sieving qPCR method and related to wilt development. The estimated inoculum threshold varied with cultivar, ranging from 4.0 and 7.0 CFU g(-1) of soil for susceptible and resistant cultivars, respectively. In addition, there was an overall relationship of wilt incidence with inoculum density across 31 commercial fields where a single composite soil sample was taken at each field, with an estimated inoculum threshold of 11 CFU g(-1) of soil. These results suggest that wilt risk can be predicted from the estimated soil inoculum density using the new wet-sieving qPCR method. We recommend the use of 4.0 and 7.0 CFU g(-1) as an inoculum threshold on susceptible and resistant cultivars, respectively, in practical risk prediction schemes.
authors.forename: Feng
authors.initials: F
authors.lastname: Wei
authors.forename: Rong
authors.initials: R
authors.lastname: Fan
authors.forename: Haitao
authors.initials: H
authors.lastname: Dong
authors.forename: Wenjing
authors.initials: W
authors.lastname: Shang
authors.forename: Xiangming
authors.initials: X
authors.lastname: Xu
authors.forename: Heqin
authors.initials: H
authors.lastname: Zhu
authors.forename: Jiarong
authors.initials: J
authors.lastname: Yang
authors.forename: Xiaoping
authors.initials: X
authors.lastname: Hu
mesh_terms: D056915:DNA Copy Number Variations; D017931:DNA Primers / Q000235:genetics; D003368:Gossypium / Q000382:microbiology*; D010935:Plant Diseases / Q000382:microbiology*; D010957:Plasmids / Q000235:genetics; D016016:Proportional Hazards Models; D060888:Real-Time Polymerase Chain Reaction; D012987:Soil; D012988:Soil Microbiology; D013045:Species Specificity; D020172:Verticillium / Q000235:genetics / Q000254:growth & development / Q000502:physiology*
chemical_list: D017931:DNA Primers; D012987:Soil
keywords: disease severity; proportional odds model