Detection and distribution of soil-borne Rhizoctonia solani causing black scurf and stem canker in potatoes


Black scurf is a blemish disease of potato caused by the fungus Rhizoctonia solani and is characterised by black sclerotia on the tuber surface. With increasing emphasis on skin quality in the pre-pack and seed potato markets, this disease increased in significance and in the early 2000s was considered to be one of the three major tuber disease problems of the potato industry.

In addition to producing a blemish on the tuber, the fungus can infect developing sprouts and stolons from the seed tuber prior to emergence resulting in the formation of cankers. This infection can result in delayed emergence, an uneven and reduced tuber set and an undesirable tuber size distribution. 

In assessing the risk of disease caused by a soil-borne pathogen, it is necessary to know whether inoculum is present in the soil, and in what quantity. Diagnostic assays are used to study the epidemiology of various plant diseases, and have proved a major step forward in understanding pathogen spread and multiplication in both plants and soil. At the time the research was commissioned, attempts to detect soil-borne R. solani using an ELISA assay had not proved entirely successful. DNA-based, PCR technology had been used to develop a sensitive and specific test for R. solani AG3 in soil. This project compared the use of conventional (non-quantitative) PCR and real-time quantitative PCR (TaqMan) in combination with baiting techniques for the detection of R. solani AG3 in soil. 


Soil samples from 1 ha blocks within twenty-six fields destined for potatoes were tested for soil contamination by three detection methods.  There was no correlation between the results of the  methods.

Using data from intensively monitored sites and the visually assessed bait seed assay, it was clear that the fungus was present at all sampling locations but that the level of contamination varied from point to point.  This suggested that the disease is less patchy than first thought, at least where levels of contamination are relatively high.  In these instances, provided that sufficient random samples were taken, it would be unlikely that the fungus would not be detected. 


Project code:
01 July 2002 - 30 June 2003


807232 Final Report 2004