Cereal root diseases — current status on impact, detection and management

Take home messages

  • Soil-borne diseases most likely to pose the greatest risk to cereal crops in the southern region during 2018 include rhizoctonia root rot, crown rot and root lesion nematodes.
  • PREDICTA® B has new tests for ascochyta blight of chickpeas, plus yellow leaf spot and white grain disorder of wheat. Follow sampling recommendations in manual V10. Misplaced PREDICTA® B accreditation numbers can be retrieved by contacting Nigel Percy
  • Rhizoctonia root rot symptoms are worse in low rainfall seasons, but net yield losses increase when growing season rainfall increases from 200mm to 400mm in combination with a dry finish. PREDICTA® B can identify paddocks before seeding where losses are likely to occur. To reduce losses: control summer weeds, sow early, use soil openers that disturb soil below the seed. Consider seed treatments. Best protection is achieved by dual streaming fungicide on soil surface above the seed and at the base of the furrow below the seed. Barley is affected more than wheat.
  • Crown rot losses are greater in seasons with good winter rainfall followed by moisture stress during spring. Yield loss is highest in durum, followed by wheat then barley. If growing durum use PREDICTA® B to avoid medium to high crown rot risk paddocks. Select from the best adapted, least susceptible cereal varieties. Sow early within the optimum seeding window, match nitrogen (N) fertiliser to season potential. In non-cereal phases, grow pulses and oilseeds that achieve early canopy closure to hasten stubble breakdown.
  • Root lesion nematode effects on yield vary between seasons. In 2017 at Pinery SA, Pratylenchus neglectus caused yield losses of 0.5t/ha to 1.5t/ha in a range of wheat varieties. Use PREDICTA® B to determine which species are present, then check latest cereal disease variety guide to select the least susceptible of the best adapted varieties. Sow early within the optimum seeding window. When growing non-cereals, check seeding guides to select non-host crops/resistant varieties.

Aims

  • Improve the value of PREDICTA® B to growers and researchers to monitor levels of soil- and stubble-borne pathogens in cropping systems and evaluate new management practices.
  • Improve understanding of yield losses caused by soil-borne diseases.
  • Develop reliable management strategies to control crown rot and root lesion nematodes.

Background

There are a range of soil-borne diseases, which collectively are estimated to cost grain growers over $370 million each year (Murray and Brennan 2009). The most important soil-borne diseases in the southern region are: rhizoctonia root rot, crown rot and root lesion nematodes 2017 distribution maps.

Strategies to minimise yield losses caused by soil-borne diseases must be implemented before sowing. Knowing which soil-borne disease poses the greatest risk to the planned crop is vital for the development of effective management strategies. PREDICTA® B provides growers and consultants with this crucial information.

In the past four and a half years’ four national GRDC projects including DAS00125, DAN00175, DAV00128 and DAS00137 have collaborated to improve the value of PREDICTA® B in identifying the regional risks from different soil-borne diseases and develop improved management options to control rhizoctonia, crown rot and root lesion nematodes (Pratylenchus species). Other projects including DAS00139 and BWD000025 have also contributed to improved understanding of soil-borne disease distribution and incidence.

Results and discussion

Root disease survey (BWD000025)

A root disease survey of paddocks monitored by the GRDC National Paddock Survey (NPS) project (BWD000025) revealed widespread moderate levels of root disease in cereal crops across Australia. Root disease ratings varied between seasons and districts (Figures 1 and 2). In general, each 0.5 unit increase in root disease score above a base of 0.5 units can reduce yield by 10%. This means average yield losses caused by soil-borne diseases in the southern region could exceed 20% per annum.

In 2015 rainfall across the southern region was generally below average and spring was hot and dry, by contrast 2016 generally had above average rainfall and minimal moisture stress during grain fill. Root health was generally worse in 2016 in comparison to 2015, as evidenced by an increase in the root disease score.

Figure 1. Average root disease ratings in cereal crops sampled eight weeks after emergence from paddocks monitored by the National Paddock Survey project in 2015. Horizontal lines represent the average score in each region.

Figure 1. Average root disease ratings in cereal crops sampled eight weeks after emergence from paddocks monitored by the National Paddock Survey project in 2015. Horizontal lines represent the average score in each region.

Figure 2. Average root disease ratings in cereal crops sampled eight weeks after emergence from paddocks monitored by the National Paddock Survey project in 2016. Horizontal lines represent the average score in each region.

Figure 2. Average root disease ratings in cereal crops sampled eight weeks after emergence from paddocks monitored by the National Paddock Survey project in 2016. Horizontal lines represent the average score in each region.

Rhizoctonia (DAS00123 and DAS00125)

Impact of rhizoctonia root rot

Rhizoctonia solani AG8, the cause of rhizoctonia root rot, is adapted to low rainfall conditions, especially in districts with sandy soils. It is notorious for causing distinctive bare patches. These patches develop when seminal roots of seedlings are severely damaged. This is most likely to occur when early root growth is restricted due to cold soil temperatures, compaction layers, inadequate soil moisture below 10cm and herbicide damage.

Less well known is that crops sown early into Rhizoctonia-infected, warm, moist soil often establish and grow well until mid-winter when soil temperatures drop to around 10°C or lower. Under these conditions rhizoctonia root rot infects the crown roots that support tillering causing the crop to develop uneven growth. Barley is more vulnerable than wheat because it produces more tillers, and therefore, is more dependent on crown roots.

Yield losses can exceed 50%, but this varies between seasons. The symptoms are often most visible in low rainfall seasons, however research undertaken to develop liquid streaming of fungicides to control rhizoctonia root rot (funded by GRDC, SAGIT, DAFWA, UniSA and SARDI) shows that there is a strong effect of growing season rainfall on the magnitude of yield response (Figure 3).

This research found that when April to October rainfall increased from 200mm to 400mm, yield responses in wheat increased from around 10% to 50% in the dual liquid streaming Uniform® fungicide treatment (200mL/ha above and 200mL/ha below the seed) in field experiments with medium to high initial levels of R. solani AG8. Two of the sites had greater yield responses for similar April to October rainfall at the other sites; both had significant summer rainfall so the additional response was probably due to stored soil moisture.

Figure 3. Percentage yield responses in wheat field experiments between 2011 and 2015 treated with dual streams of Uniform® fungicide at 200mL/ha above and below the seed to control rhizoctonia root rot in medium to high risk paddocks versus April to October rainfall; *Low summer rainfall <>High summer rainfall.

Figure 3. Percentage yield responses in wheat field experiments between 2011 and 2015 treated with dual streams of Uniform® fungicide at 200mL/ha above and below the seed to control rhizoctonia root rot in medium to high risk paddocks versus April to October rainfall; *Low summer rainfall <>High summer rainfall.

Detection

While growers generally know which are their worst rhizoctonia root rot paddocks — these typically have a long history of bare patches, PREDICTA® B can assist growers to identify paddocks in which cereals are likely to develop uneven growth during winter. These paddocks are more likely to be missed by growers.

Management of rhizoctonia root rot

Most of the practices to reduce the impact of rhizoctonia root rot need to be implemented when the crop is sown, so it is important to identify all paddocks at risk as soon as possible.

There is no ‘magic bullet’ however, including as many of the following practices as possible will reduce yield losses:

  • Control summer weeds, these use stored moisture and can increase Rhizoctonia levels.
  • Sow early within the optimum period, seedlings that establish in warm moist soil are more likely to develop a deeper root system.
  • Consider using seed treatments registered to control rhizoctonia root rot; on average these increase yield by 5% in the presence of Rhizoctonia infection.
  • Consider liquid streaming fungicides to better control rhizoctonia root rot, dual placement above and below the seed provides the best protection of the root system and is the treatment most likely to produce the greatest yield responses in above average rainfall seasons.
  • Adequate nutrition; place starter fertiliser below the seed to facilitate early vigour. The aim is to get the plant to establish a deep root system quickly.
  • Use soil openers that disturb soil below the seed to facilitate root growth down the soil profile.
  • Sow wheat instead of barley; losses in wheat are 40% lower than those in barley.
  • Increase seeding rate if liquid streaming fungicide is not an option. This will help compensate for loss of tillers caused by Rhizoctonia reducing the number of crown roots.
  • Post emergent N application will help crops compensate for having a reduced root system, note the benefits have yet to be measured for crops affected by rhizoctonia.

Crown rot (DAN00175 and DAS000137)

Crown rot impact

Crown rot is an important disease throughout the cropping regions. Analysis of 43 field experiments showed average yield losses of 26%, 15% and 5% in durum wheat, susceptible bread wheat and barley, respectively in crown rot conducive seasons (dry Sept/Oct) (Figure 4).

Figure 4. Yield loss in cereals based on an analysis of 43 field experiments conducted in Victoria and South Australia in 1998 to 2015. Percentage yield loss detailed above each column. Wet and dry seasons were defined as above or below average September/October rainfall, respectively. n.s. = yield response was not significant.

Figure 4. Yield loss in cereals based on an analysis of 43 field experiments conducted in Victoria and South Australia in 1998 to 2015. Percentage yield loss detailed above each column. Wet and dry seasons were defined as above or below average September/October rainfall, respectively. n.s. = yield response was not significant.

Yield losses are greatest in seasons with good winter rainfall followed by moisture stress during anthesis and grain fill, for example 2015 (Figure 5). Losses are not significant when there is no moisture stress during grain fill, as occurred in 2016 (Figure 5). In general, losses in seasons with a dry finish were double those with a wet finish (Figure 4).

Figure 5. Grain yield of durum and bread wheat in the presence of increasing crown rot loads at Dooen, Victoria in 2015, dry finish, p<0.001, Lsd = 0.23 and 2016, wet finish, n.s. (DAW00245). Durum (WID802) is rated very susceptible (VS) to crown rot, the bread wheat Cobra is rated susceptible (S) and Emu Rock is classified as moderately susceptible (MS).

Figure 5. Grain yield of durum and bread wheat in the presence of increasing crown rot loads at Dooen, Victoria in 2015, dry finish, p<0.001, Lsd = 0.23 and 2016, wet finish, n.s. (DAW00245). Durum (WID802) is rated very susceptible (VS) to crown rot, the bread wheat Cobra is rated susceptible (S) and Emu Rock is classified as moderately susceptible (MS).

Crown rot detection

Studies undertaken in collaboration with National Variety Trial (NVT) and NPS projects, showed that avoiding stubble when collecting PREDICTA® B samples led to a significant under estimation (failure to warn) of the risk of crown rot. This can be fixed by adding a 5cm piece of stubble (two pieces recommended if growing durum) from the base of the previous plants (one to several years old) from 15 different locations. Adding stubble in this way also facilitates testing for other stubble-borne pathogens.

Crown rot management

Growers can reduce yield loss from crown rot through crop choice. If a cereal must be grown in a high risk paddock, barley or a wheat variety rated MS for crown rot are the best options (Figure 4 and 5). However, if the most resistant cultivar is not adapted to the area, the best option is to grow the least susceptible of the best adapted cultivars, e.g. Emu Rock instead of Mace (Figure 6).

It is also important to note that even though barley had the lowest yield losses, barley along with all other cereals increase crown rot inoculum levels.

Figure 6. Grain yield of triticale, durum, bread wheat and barley plus and minus crown rot inoculum at Pinery SA, sown 31 May 2014.

Figure 6. Grain yield of triticale, durum, bread wheat and barley plus and minus crown rot inoculum at Pinery SA, sown 31 May 2014.

General management advice to reduce the impact of crown rot:

  • Durum is most susceptible to crown rot, followed by wheat then barley.
  • If planning to grow durum, then use PREDICTA® B to identify and avoid paddocks with medium to high risk of crown rot.
  • Check the latest cereal disease variety guides and select the least susceptible of the best adapted varieties for your area.
  • Sow early within the optimum seeding window recommended for a selected variety.
  • Match N fertiliser to season potential and ensure adequate zinc nutrition.
  • Control grass weeds in fallow and crop phases.
  • Inter-row sowing with guidance performance systems’ (GPS) guidance between intact standing previous cereal rows reduces contact with inoculum and hence infection levels.
  • In non-cereal phases, where possible grow pulses and oilseeds that form early canopy closure to hasten stubble breakdown.
  • Avoid cultivation/harrowing as this increases the chance of infected stubble contact with the next cereal crop, thus increasing risk of crown rot.

Root lesion nematodes (DAV00128 and DAV00144)

Impact of root lesion nematodes

Field experiments conducted since 2010 show that different groups of varieties respond to root lesion nematodes in different seasons. This means there is a strong interaction with environmental conditions.

In 2017, Pratylenchus neglectus at 12 nematode/g soil caused significant (p<0.05) yield losses in the following wheat varieties: Trojan (25% or 1.5t/ha), Cutlass (1.26t/ha), Hatchet CL Plus (0.83t/ha), Emu Rock (0.8t/ha), Scout (0.70t/ha), Beckom (0.67t/ha) and Mace (0.48t/ha). Bison triticale also lost (0.52t/ha) (Figure 7).

Further work is required to define conditions that represent a high risk season, but in general these appear to have good rainfall before grain fill followed by moisture stress. When there is no moisture stress during grain fill as occurred in 2016, P. neglectus had no effect on yield of any cereal varieties.

Figure 7. Effect of Pratylenchus neglectus on yield of wheat, durum, barley and triticale varieties at Pinery SA in 2017. LHS column shows the yield in low (0.6 P. neglectus/g) soil treatments and RHS columns the yield in high (12 P. neglectus/g) soil treatments; the yield in the hatched columns was significantly lower than the paired low nematode treatment at p<0.05.

Figure 7. Effect of Pratylenchus neglectus on yield of wheat, durum, barley and triticale varieties at Pinery SA in 2017. LHS column shows the yield in low (0.6 P. neglectus/g) soil treatments and RHS columns the yield in high (12 P. neglectus/g) soil treatments; the yield in the hatched columns was significantly lower than the paired low nematode treatment at p<0.05.

There is growing evidence that the impact of root lesion nematodes is greater when combined with other soil-borne diseases. In a field experiment conducted by Northern Grower Alliance at Macalister, Qld in 2015, yield loss across six wheat varieties was greater when crown rot and P. thornei occurred together (Figure 8).

Figure 8. Mean yield loss of six wheat varieties in different combination of Pratylenchus thornei (Pt) and crown rot (CR) in a Northern Grower Alliance field experiment at Macalister, Qld 2015.

Figure 8. Mean yield loss of six wheat varieties in different combination of Pratylenchus thornei (Pt) and crown rot (CR) in a Northern Grower Alliance field experiment at Macalister, Qld 2015.

Root lesion nematode detection and risk assessment

When developing a management program for root lesion nematodes, it is important to know which species are present within individual paddocks as each can have a different host range including differential effects on varieties.

A national survey of root lesion nematodes conducted by DAS00137 and DAV00128 confirmed that the PREDICTA® B tests for P. neglectus, P. thornei, P. quasitereoides and P. penetrans are reliable. So PREDICTA® B can be used with confidence to determine which of the main root lesion nematode species are present in a paddock, plus the level of each species, before crops are sown.

Work also undertaken by DAV00128 and DAW00245 indicates that the current PREDICTA® B regional yield loss risk categories are appropriate, though this work is continuing.

Root lesion nematode resistance rankings for cereals

Figures 9 and 10 show representative current wheat, barley, durum and triticale varieties ranked by their effect on P. neglectus and P. thornei multiplication respectively for low and medium initial nematode densities; multiplication rates decline as initial nematode densities increase. A multiplication rate of one maintains the initial population.

Triticale varieties usually have excellent resistance to P. neglectus, followed by barley then wheat. Most wheat varieties are susceptible, but individual varieties such as Mace are less susceptible.

Durum wheat varieties are often the most resistant to P. thornei, followed by barley. Bread wheat are usually susceptible. Some southern region wheat varieties such as Scout are less susceptible.

Figure 9. Predicted multiplication of Pratylenchus neglectus on cereal varieties at low and medium initial population densities across four southern region trials 2015-16. Initial population densities in the low (LHS column) and high nematode (RHS column) treatments were 2and 19nematodes/g soil, respectively.

Figure 9. Predicted multiplication of Pratylenchus neglectus on cereal varieties at low and medium initial population densities across four southern region trials 2015-16. Initial population densities in the low (LHS column) and high nematode (RHS column) treatments were 2and 19nematodes/g soil, respectively.

Figure 10. Predicted multiplication of Pratylenchus thornei on cereal varieties at low and medium initial population densities across four southern region trials 2011 to 2016. Initial population densities in the low (LHS column) and high nematode (RHS column) treatments were 5 and 15 nematodes/g soil respectively.

Figure 10. Predicted multiplication of Pratylenchus thornei on cereal varieties at low and medium initial population densities across four southern region trials 2011 to 2016. Initial population densities in the low (LHS column) and high nematode (RHS column) treatments were 5 and 15 nematodes/g soil respectively.

Crop effects of P. neglectus and P. thornei multiplication

Figures 11 and 12 shows how varieties of different crops have affected multiplication of P. neglectus and P. thornei, respectively, in field trials accessed in South Australia and Victoria in the past five years. Some susceptible crops, for example canola in Figure 12, span a range of resistance categories due to the effects of low rainfall seasons. In other crops such as wheat the broad range also reflects varietal differences. Therefore, it is important to consult a current disease variety guide when selecting cultivars to manage root lesion nematodes.

Figure 11. Spread of Pratylenchus neglectus resistance rankings for cereal, pulse and oilseed varieties evaluated in field experiments across a range of sites and above and below average rainfall.

Figure 11. Spread of Pratylenchus neglectus resistance rankings for cereal, pulse and oilseed varieties evaluated in field experiments across a range of sites and above and below average rainfall.

Figure 12. Spread of Pratylenchus thornei resistance rankings for cereal pulse and oilseed varieties evaluated in field experiments across a range of sites and growing season rainfall.

Figure 12. Spread of Pratylenchus thornei resistance rankings for cereal pulse and oilseed varieties evaluated in field experiments across a range of sites and growing season rainfall.

Management practices to reduce losses caused by root lesion nematodes.

Crop and variety selection is the best way to manage root lesion nematode populations.

  • Control summer weeds, these often host root lesion nematodes.
  • Use PREDICTA® B to determine which Pratylenchus species pose a significant risk to yield.
  • Use the latest cereal disease variety guide to select the least susceptible of the best adapted varieties.
  • When growing non-cereals, check seeding guides to select non-host crops/resistant varieties.
  • Sow early within the optimum seeding window.
  • Provide adequate nutrition.

PREDICTA® B new developments

PREDICTA® B is under continual development to provide a comprehensive assessment of the levels of soil- and stubble-borne pathogens that pose a potential risk to cereals and increasingly, pulse and oilseed crops. The aim is to provide a fast and cost-effective way for growers to determine the soil- and stubble-borne disease risks, to help inform decisions of crop and variety choice and guide management to minimise losses.

New tests under evaluation are reported with categories based on population density so growers and consultants can benchmark levels of pathogen DNA detected in paddocks against the rest of industry. When the relationship between the initial pathogen level and disease has been defined, the level detected in the sample is reported with a disease risk rating.

New tests to be reported in 2018

In the southern region in 2018 results of new tests for ascochyta blight of chickpea, yellow leaf spot and white grain disorder of wheat and charcoal rot will be reported in the ‘tests under evaluation’ section on PREDICTA® B reports.

Ascochyta blight of chickpea

Ascochyta blight is a serious disease of chickpea that can severely reduce yields in the southern region. The PREDICTA® B results can be used to rank paddocks based on inoculum levels and monitor decline after the previous chickpea crop. However, any detection of this pathogen by PREDICTA® B should be considered as significant and it is recommended that chickpeas are grown only in paddocks in which the pathogen is below the detection limit and industry best practice is adopted to manage the risk of ascochyta blight.

If chickpea stubble is in the paddock, then in addition to adding cereal stubble, add one small piece (5cm) of chickpea stubble from each of the 15 sampling locations to the PREDICTA® B soil sample.

Yellow leaf spot

Yellow leaf spot is a stubble-borne disease of wheat. PREDICTA® B test results can be used to rank paddocks based on the levels of inoculum (including determining if there has been post-harvest saprophytic colonisation of cereal stubble in wet summers), monitor inoculum decline during different phases of the cropping sequence and confirm disease diagnosis.

Field research undertaken by Agriculture Victoria and DPIRD show there is a good correlation between DNA levels detected pre-sowing and early leaf disease development in the crop (Figure 13) showing the potential for PREDICTA® B to assist with paddock selection. In wet seasons, secondary infection later in the season will likely cause more severe disease development that may require spraying.

Growers should consider not sowing high risk paddocks to wheat, but if wheat is to be sown plant the most resistant varieties in the paddock with highest risk of initial infection. PREDICTA® B can also be used to monitor changes in inoculum load at different phases of the cropping sequence.

Yellow leaf spot management options.

Figure 13. Percentage leaf area affected by yellow leaf spot at growth stage 25 versus pre-sowing log (DNA copies/g soil), Longerenong, 2017.

Figure 13. Percentage leaf area affected by yellow leaf spot at growth stage 25 versus pre-sowing log (DNA copies/g soil), Longerenong, 2017.

White grain disorder

White grain disorder does not occur very often in the southern region and does not warrant an active management program. It causes symptoms in grain that can lead to downgrading or rejection of affected wheat loads at receival sites.

PREDICTA® B can identify the paddocks with the potential to develop white grain disorder. When seasonal conditions are conducive for infection (i.e. wet during flowering and early grain fill), growers should check for symptomatic grain and plan to harvest high risk paddocks separately.

White grain disorder management options

Charcoal rot

Charcoal rot is caused by Macrophomina phaseolina, which has a very broad host range of more than 400 species. Charcoal rot is a serious disease of summer crops including sorghum, soybean and sunflower. It has been recorded as causing significant disease on lupin in WA when conditions in spring are dry and hot.

The impact of charcoal rot in the southern region is unknown. The results will be reported by PREDICTA® B because Macrophomina is widespread throughout Australia including the southern region.

Progress on developing disease risk categories

Research to develop disease risk categories for several of the tests under evaluation is progressing. Another season of data should be sufficient to develop disease risk categories for common root rot caused by Bipolaris sorokiniana, the current data is summarised in Figure 14. Research is also progressing to develop disease risk categories for yellow leaf spot and eyespot.

Figure 14. Current population density categories and provisional disease risk categories for Bipolaris sorokiniana. Horizontal lines indicate the disease incidence categories based on plating stubble post-harvest (grey). Vertical lines indicate the boundaries for the current population density categories (black).

Figure 14. Current population density categories and provisional disease risk categories for Bipolaris sorokiniana. Horizontal lines indicate the disease incidence categories based on plating stubble post-harvest (grey). Vertical lines indicate the boundaries for the current population density categories (black).

New tests under development

SARDI is currently working on developing tests for sclerotinia, clubroot in canola and Botrytis cinerea (which causes grey mould of lentil and chickpea). Additionally, the team will shortly commence work on developing a test for one of the mites that affect crop establishment.

Further information on the ‘tests under evaluation’. SARDI accredited consultants can obtain information on new tests and management options in Version 10 of the Broadacre Soilborne Disease Manual,

Useful resources

SARDI Cereal Variety Disease Guide 2017

Soil borne diseases

Rhizoctonia factsheet 

Crown rot winter cereals factsheets

References

Murray and Brennan (2009) Estimating disease losses to the Australian wheat industry. Australasian Plant Pathology.

Acknowledgments

The research reported in this paper was made possible by the significant contributions of growers including hosting trials, input from consultants and the support of the GRDC. Contributing projects include DAS00137 national molecular diagnostics, DAN00175 National crown rot project, DAV00128 National nematology project, DAW00245 National yield response curve project, DAV00144 Southern region nematology project, DAS00139 Improving grower surveillance, management, epidemiology knowledge and tools to manage crop disease in South Australia and BWD000025 National Paddock Survey project, the authors would like to thank them for their continued support.

Contact details

Alan McKay
SARDI
(08) 8303 9375
alan.mckay@sa.gov.au

GRDC Project Code: DAS00137, DAN00175, DAV00144, DAS00125,