Predicting Cereal Root Disease in Western Australia Using Soil DNA and Environmental Parameters

Abstract

Root diseases have long been prevalent in Australian grain-growing regions, and most management decisions to reduce the risk of yield loss need to be implemented before the crop is sown. The levels of pathogens that cause the major root diseases can be measured using DNA-based services such as PreDicta B. Although these pathogens are often studied individually, in the field they often occur as mixed populations and their combined effect on crop production is likely to vary across diverse cropping environments. A 3-year survey was conducted covering most cropping regions in Western Australia, utilizing PreDicta B to determine soilborne pathogen levels and visual assessments to score root health and incidence of individual crop root diseases caused by the major root pathogens, including Rhizoctonia solani (anastomosis group [AG]-8), Gaeumannomyces graminis var. tritici (take-all), Fusarium pseudograminearum, and Pratylenchus spp. (root-lesion nematodes) on wheat roots for 115, 50, and 94 fields during 2010, 2011, and 2012, respectively. A predictive model was developed for root health utilizing autumn and summer rainfall and soil temperature parameters. The model showed that pathogen DNA explained 16, 5, and 2% of the variation in root health whereas environmental parameters explained 22, 11, and 1% of the variation in 2010, 2011, and 2012, respectively. Results showed that R. solani AG-8 soil pathogen DNA, environmental soil temperature, and rainfall parameters explained most of the variation in the root health. This research shows that interactions between environment and pathogen levels before seeding can be utilized in predictive models to improve assessment of risk from root diseases to assist growers to plan more profitable cropping programs.

Fusarium crown rot caused by Fusarium pseudograminearum in cereal crops: recent progress and future prospects

“…However, the correlation found between pre‐sow and post‐harvest pathogen DNA levels was relatively weak for F. pseudograminearum compared with the correlations for other soil‐borne pathogens (Poole et al ., ). The levels of pathogen DNA measured with PreDicta B commercial PCR assays (Ophel‐Keller et al ., ) explained only a small portion of the overall root health (Poole et al ., ). Therefore, the prediction of disease incidence solely on the level of FCR inoculum present before sowing may not be sufficient for all cereal‐growing regions.…”

“…Given that F. pseudograminearum survives in colonized plant debris, the level of fungal inoculum already present in the field before sowing can be an indicator of the FCR incidence of the subsequent year. Several polymerase chain reaction (PCR) and quantitative PCR (qPCR) protocols have been developed to estimate the levels of FCR inoculum present in the soil or stubble (Evans et al, 2010;Hogg et al, 2007Hogg et al, , 2010Hollaway et al, 2013;Knight and Sutherland, 2017;Poole et al, 2015;Williams et al, 2002). In South Australia and Victoria, the levels of F. pseudograminearum and F. culmorum inocula found in the field prior to the planting season were positively correlated with FCR disease expression (e.g.…”

“…A recent study examining the effect of prior inoculum levels of various soil-borne pathogens on FCR concluded that prior inoculum levels, when combined with environmental factors, can exacerbate disease problems (Poole et al, 2015). However, the correlation found between pre-sow and post-harvest pathogen DNA levels was relatively weak for F. pseudograminearum compared with the correlations for other soil-borne pathogens (Poole et al, 2015). The levels of pathogen DNA measured with PreDicta B commercial PCR assays (Ophel-Keller et al, 2008) explained only a small portion of the overall root health (Poole et al, 2015).…”

Field assessment of microbial inoculants to control Rhizoctonia root rot on wheat

“…Assessing strains for control of Rhizoctonia root rot on-farm presents a number of challenges, including selection of sites where disease is expected and the uneven distribution of Rhizoctonia patches across a field (Anees et al, 2010;Schillinger and Paulitz, 2006). The sites used in this present study provide a rigid evaluation of the microbes because they were fields which had greater than 100 pg R. solani AG8 DNA per gram of soil, which is considered high risk for disease expression (Ophel-Keller et al, 2008;Poole et al, 2015).…”

“…Pathogen DNA levels were assessed by taking 50 x ~10 g samples across prospective trial sites from the top 10 cm of the soil profile for analysis by the Root Disease Testing Service at the South Australian Research and Development Institute. This service is provided commercially as PreDictaB TM (http://www.pir.sa.gov.au/research/services/molecular_diagnostics/predicta_b) (Ophel-Keller et al, 2008;Poole et al, 2015). Trial site location, and pre-sowing R. solani AG8 levels and in season rainfall are given in Table 2.…”