Threshold microsclerotial inoculum for cotton verticillium wilt determined through wet-sieving and real-time quantitative PCR

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Abstract

Quantification of Verticillium dahliae microsclerotia is an important component of wilt management on a range of crops. Estimation of micro-sclerotia by dry or wet sieving and plating of soil samples on semi-selective 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 poly-merase 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.

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Wei, F., Fan, R., Dong, H., Shang, W., Xu, X., Zhu, H., … Hu, X. (2015). Threshold microsclerotial inoculum for cotton verticillium wilt determined through wet-sieving and real-time quantitative PCR. Phytopathology, 105(2), 220–229. https://doi.org/10.1094/PHYTO-05-14-0139-R

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