Root health – a key factor for cereal crop productivity

Take home messages

  • Root health issues were observed in all regions and seasons suggesting that significant potential exists to benefit from improving root health
  • Multiple diseases were commonly observed in a single field
  • Agro-ecological region based distribution variation of specific diseases was also found
  • Agro-ecological region based variation in the types of root disease suggest the need for different management solutions. Recurring major diseases versus multiple diseases in single paddocks require different combinations of control measures in an integrated disease management program
  • Root disease observations coupled with water-limited yield estimations and paddock data, indicated that root diseases are one of the key factors causing significant yield gaps in cereal crops.

Background

Soilborne root diseases are a major constraint for Australian cereal crop production with more than $800 million annual costs (Murray and Brennan 2010). In the northern region, there are a number of soilborne fungal and nematode diseases which collectively cost grain growers over $370 million each year. Good root health is critical for higher water use efficiency and plant nutrition in terms of ability to access nutrients from soil organic matter mineralisation. Nitrogen mineralised from the soil organic matter and crop residues makes a substantial contribution (~50%) to crop N uptake (Angus and Grace, 2017).

Cereals cropped continuously are at high risk from soilborne diseases, in particular from crown rot and Rhizoctonia bare patch, for which there is no reliable chemical or plant resistance based control measures (Gupta et al. 2015). Therefore, effective disease control requires the management of pathogen inoculum, in order to reduce the infection process and disease severity.

The most important soil-borne pathogens in the northern region are: crown rot and root lesion nematode (see pathogen distribution maps at PreDicta B, PIRSA website in particular Pratylenchus thornei. Control strategies only provide good control at low to medium inoculum levels and their effectiveness declines as inoculum levels increase and where soil biological disease suppressive activity is low.

The aim of the GRDC-funded National Paddock Survey Project (2015 to 2018) is to quantify the yield gap on 250 paddocks nationally and to identify factors driving yield limitations in cereal crops across northern, southern and western grain production regions. The term yield gap refers to the difference between achieved and potential yield.  On average, Australia’s wheat growers currently achieve about half their water-limited yield (Hochman et al. 2016). Root health assessments are a crucial factor assessed in this context. Further, the projects aims to provide growers with information and the tools required to close the yield gap.

Methods

On average 250 paddocks per annum nationally, 80 in each of northern NSW/Qld and WA and 90 in southern NSW, Vic and SA, were monitored intensively over a four-year rotation (2015 to 2018). Consultants and farming systems groups undertook monitoring and sample collection for pathogen inoculum and root diseases. Two zones in each paddock were monitored at five geo-referenced monitoring points along a permanent 200 to 250m transect.  Each monitoring point was visited four times per season (pre- and post-season soil sampling, and in-crop at the equivalent crop growth stages of GS30 and 65).

For root health assessments, wheat and barley root samples were collected at the GS31 stage from cropped fields (10 plants from each of five GPS locations on a 200 metre transect) from up to 200 fields/year. Seminal and crown roots were independently scored for general root health using a 0-5 rating scale (0=healthy; 5=80% of roots were diseased or showed abiotic damage).  Additionally, the roots were collectively scored for the incidence and severity of seven major soilborne diseases on a 0-2 scale, based on presence and severity (0=no disease; 2=50% of roots infected with the disease). The seven different diseases were: take-all, Fusarium crown rot, Pythium root rot, Bipolaris root rot, Rhizoctonia root rot, Phoma root rot and nematode damage (cereal cyst nematode & Pratylenchus).  Roots were also scored for non-biological damage and other root diseases. Subsamples of roots with typical symptoms of known diseases, and difficult to diagnose disease symptoms, were analysed using DNA based identification tests. Pre-sowing soils from each location were analysed (PREDICTA®B) to quantify the pathogen DNA loads of a range of cereal root pathogens.

Results and discussion

Overall root health

Root health in cereal crops is a general concern in all regions, localities and fields in all three seasons. In general, plant roots sampled across all regions contained at least some root damage and only a few fields (<20%) had plants without disease symptoms (Figure 1). However, few fields (on average 20%) had an overall root disease score of 3 or above. In general field level root disease scores were higher in the 2016 and 2017 seasons, when compared to disease scores in the 2015 season in all regions. Results show widespread moderate levels of root disease in cereal crops across Australia.  Average root disease scores across all regions during 2015 to 2017 were: southern=1.5 to 1.8, western=1.2 to 2.7 and northern=1.5 to 3.4.

This is three maps of Australia showing root disease incidence score (on a 0-5 scale; 0=healthy and 5=diseased) for each field across all regions during the 2015 to 2017seasons. Average root disease score varied between fields within a region, between regions and seasonally.  Results show widespread moderate levels of root disease in cereal crops across Australia.  Average root disease scores across all regions during 2015 to 2017 were: southern=1.5 to 1.8, western=1.2 to 2.7 and northern=1.5 to 3.4.

Figure 1. Root disease incidence score (on a 0-5 scale; 0=healthy and 5=diseased) for each field across all regions during the 2015 to 2017 seasons. Average root disease score varied between fields within a region, between regions and seasonally

As good root health is essential to access nutrients and water from the entire soil profile in the rainfed cropping regions of Australia, these results suggest that there is a significant potential to benefit from improving root health by adopting management practices that reduce pathogen inoculum levels and improve soil biological activity (disease suppression) to buffer against disease impacts on crop performance. It is generally recommended that most effective strategies to minimise yield losses in cereals caused by soil-borne diseases must be implemented before sowing. It is important to know which soil-borne disease poses the greatest risk to the planned crop for the development of effective management strategies.

This is a set of three column graphs showing average root disease ratings in cereal crops sampled 8 weeks after emergence from paddocks monitored by the National Paddock Survey project during 2015 to 2017. Horizontal lines represent the regional average.Within each region there were clear locality (district) based differences (e.g. Goondiwindi, Emerald) in terms of overall root health (root disease ratings) in all seasons (Figures 1 and 2).

Figure 2. Average root disease ratings in cereal crops sampled 8 weeks after emergence from paddocks monitored by the National Paddock Survey project during 2015 to 2017. Horizontal lines represent the regional average.

Within each region there were clear locality (district) based differences (e.g. Goondiwindi, Emerald) in terms of overall root health (root disease ratings) in all seasons (Figures 1 and 2). Also, within each locality there were significant between field differences in overall disease scores and the distribution of different diseases. Observations from the Predicta B DNA test results for farmer fields during the last decade have shown distinct regional based differences and seasonal variation in the distribution of various soilborne pathogens (PreDicta B, PIRSA website). Together, these observations indicate that soilborne disease risks are wide spread across all grain crop growing regions. 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 northern region could exceed 20% per annum.  However, management and environmental factors such as seasonal conditions would influence the level of impact on production. For example, the 2015 season in the northern region was characterised by little rainfall in spring and hot grain-fill temperatures, 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.

Regional distribution and recurring problems

Diseases such as Fusarium, take-all and Bipolaris root rot and root lesion nematodes were observed in multiple regions, whereas Rhizoctonia root rot was seen in southern and western regions only (Figure 3 and Figure 4). This type of regional distribution can be related mainly to environmental factors such as amount and seasonal distribution of rainfall, temperature, and soil properties such as clay content and pH. While the distribution of root lesion nematodes (Pratylenchus) was observed in all regions, when developing a management program, it is important to know which species are present within individual paddocks, e.g. P. thornei or P. neglectus, as each can have a different host range including differential effects on varieties. For example, in the northern region, P. thornei is considered as the most important nematode causing yield loss.

This is a set of four maps showing the frequency of occurrence (% plants showing the disease) of individual diseases in each field/paddock for major diseases during 2017 crop season. Diseases such as Fusarium, take-all and Bipolaris root rot and root lesion nematodes were observed in multiple regions, whereas Rhizoctonia root rot was seen in southern and western regions only (Figure 3 and Figure 4).

Figure 3. Frequency of occurrence (% plants showing the disease) of individual diseases in each field/paddock for major diseases during 2017 crop season.

Results over four seasons have clearly indicated the recurring nature of some of the soilborne diseases in all the regions although the severity of these diseases may vary between seasons. For example, Pythium root rot and Pratylenchus were commonly observed in the northern region (Figure 4). Similarly, the risk for Fusarium crown rot in the northern region was observed in all seasons, in particular in continuous cereal crop rotations, but the disease impact may only be seen in some years based on seasonal rainfall. Additionally, some of the recurring diseases in one region could be seasonally dependent in other regions, for example, Pythium root rot in the northern region is a recurring disease, but in the southern region it is only severe in wet seasons. Recurring diseases requires management intervention to avoid higher losses, mainly through adopting practices that reduce pathogen inoculum levels. For example, continuous vigilance is recommended to avoid inoculum build-up of pathogens like take-all and to reduce the potential impact on production in seasons of optimal conditions for disease expression.

This is a set of four box and whiskers graphs showing the regional average pathogen inoculum level (log DNA copies per gram soil, left) and frequency of disease incidence (right) in fields within a region for Pratylenchus in 2016 and 2017. Results over four seasons have clearly indicated the recurring nature of some of the soilborne diseases in all the regions although the severity of these diseases may vary between seasons. For example, Pythium root rot and Pratylenchus were commonly observed in the northern region (Figure 4).

Figure 4. Regional average pathogen inoculum level (log DNA copies per gram soil, left) and frequency of disease incidence (right) in fields within a region for Pratylenchus in 2016 and 2017.

Disease complexes

Results have shown the presence of multiple diseases i.e. more than one soilborne disease, in single paddocks with the presence of at least two diseases in most fields surveyed in the northern region. Significant levels of specific or multiple soilborne pathogens were also found in the pre-crop soil samples (data not presented). However, the combination of specific diseases varies in different fields, localities and regions (Figure 5). For example, in the northern region, the commonly observed soil-borne diseases found within a single paddock are Fusarium crown rot, Pratylenchus thornei and Common (Bipolaris) root rot (Figure 5). In seasons receiving above average rainfall, especially during the early growing season, Pythium root rot is also a common occurrence. It is suggested that interactions between multiple pathogens could exacerbate yield losses, however the magnitude of yield loss from different combinations of diseases is not well known. Previous research by NSW DPI researchers (Steven Simpfendorfer and team) has shown that yield losses associated with crown rot (Fusarium) and common root rot infection, increased when both pathogens occurred together, and the primary driver of losses varied depending upon rainfall conditions. In the southern region, root diseases caused by Rhizoctonia solani AG8 and root lesion nematode were the most common multiple diseases.  In such situations, pre-sowing analysis of soil using Predicta-B testing, would inform the disease risk for various diseases, thereby assisting to identify management options that limit the impact from multiple diseases and improve overall root health. In addition to pathogen load, abiotic factors (rainfall, soil fertility, residual herbicides), biotic factors (presence of suppressive microorganisms) and crop management practices (crop rotation and fertilizer additions), play an important role in determining the extent to which root disease symptoms are expressed. Therefore, effective management of soilborne diseases require both the reduction of pathogen inoculum through crop rotation, stubble management, restricting infection through improved soil biological activity (biological disease suppression capacity) and use of resistant varieties where available. Research in southern and western Australia has shown that adoption of management practices that increase carbon inputs and turnover (e.g. retention of stubble and no-till practices) and maintain biological activity during non-crop season over 5-7 years will improve biological disease suppression of soilborne diseases (Gupta et al. 2015).

Specific issues and other issues

In addition to the commonly observed diseases described above, other soilborne diseases and non-biological root health problems (e.g. residual herbicide impacts) can either directly affect root health or exacerbate disease impacts. The common root rot (Bipolaris) disease was observed in all regions, with its frequency of incidence and severity highest in the northern region.  The brown root rot caused by Phoma scleroitedes was less commonly recorded, but occurred mostly in the southern and western regions.

This is a column graph showing the frequency of specific disease occurrence in each field zone in the Northern region during 2017 crop season (transect numbers for individual field zones are shown on X-axis).  Results have shown the presence of multiple diseases i.e. more than one soilborne disease, in single paddocks with the presence of at least two diseases in most fields surveyed in the northern region. Significant levels of specific or multiple soilborne pathogens were also found in the pre-crop soil samples (data not presented). However, the combination of specific diseases varies in different fields, localities and regions (Figure 5). For example, in the northern region, the commonly observed soil-borne diseases found within a single paddock are Fusarium crown rot, Pratylenchus thornei and Common (Bipolaris) root rot (Figure 5).Figure 5. Frequency of specific disease occurrence in each field zone in the Northern region during 2017 crop season (transect numbers for individual field zones are shown on X-axis).

Implications

The National Paddock Survey project is helping to understand the critical drivers of the yield gap across Australia. Results indicated that multiple and interacting factors contribute to the yield gap in cereal crops and no significant relationship was observed between yield gap and any one  single factor e.g. N fertiliser application, in-crop rainfall, weeds, disease  (Lawes et al. 2018). Multiple season observations of root health, incidence of diseases and severity coupled with water-limited yield estimations and paddock data, indicated that root diseases are one of the key factors causing significant portions of the yield gaps in wheat and barley crops (Lawes et al. 2018; Van Rees et al. 2019). In the northern region, growing season rainfall, applied N and root disease score, were the three most important variables contributing to the yield gap. For example, crop rotation with legumes can have a significant impact on disease inoculum along with soil N dynamics and thus play an important role in alleviating root health and explaining the size of the yield gap. Whereas recurring diseases may require more than one season of non-host crops along with other management practices, e.g. sowing date, stubble management, fertilizer N addition, to reduce pathogen levels and disease impacts. In the case of disease complexes, an integrated disease management program is needed to reduce the impact from individual pathogens requiring different management interventions for reducing inoculum levels, restrict infection, improve nutrient availability during early seedling phase and remove abiotic constraints to root growth etc. Poor root health also restricts plants accessing soil N and water, hence improving root health is also essential to increase nutrient and water use efficiency. Other research has shown that there is potential to reduce the size of the yield gap with more targeted N management and crop rotation for disease and weed issues. Overall, farmer field based observations in the NPS project have demonstrated that, with the wide scale adoption of intensive cropping systems and as crop management becomes more sophisticated, knowledge about the reasons for crops’ failure to perform at their potential is essential for the selection of appropriate management practices. The only way to achieve this is to keep records of what is happening in the soil, crop and weather and to make use of these records in deciding the crop management practices to be adopted (van Rees et al. 2019).

Useful resources

Angus J and Grace P (2017) Nitrogen balance in Australia and nitrogen use efficiency on Australian farms. Soil Research 55 (6) 435-450

Gupta VVSR et al. (2015) Management of soilborne Rhizoctonia disease risk in cropping systems. MSF 2014 Compendium articles, MSF Inc, Mildura.1-5

Hochman Z. et al. (2016). Data rich yield gap analysis of wheat in Australia. Field Crops Research, 197, 97-106

Murray GM and Brennan JP (2010) Estimating disease losses to the Australian barley industry. Australasian Plant Pathology, 39: 85.

Lawes R et al. (2018) The National Paddock Survey – What causes yield  gap across Australian paddocks? GRDC Updates 2018, Perth, WA.

Poole G et al. (2015) Predicting cereal root disease in Western Australia Using Soil DNA & environmental parameters. Phytopathology 105, 1069-1079.

Van Rees H et al. (2019) National paddock  survey – closing the yield gap and informing decisions. GRDC updates, Goondiwindi, Qld, Australia.

GRDC Tips and Tactics: Crown rot in winter cereals

Acknowledgements

This research was undertaken with the financial support provided by GRDC (project BWD00056) and CSIRO. Significant contributions by growers through both trial cooperation, agronomists for sample collection and Stasia Kroker for sample processing are acknowledged.

Contact details

Vadakattu Gupta
CSIRO Agriculture, Waite campus
Ph: 08 8303 8579
Email: Gupta.Vadakattu@csiro.au;
Twitter: @LifeinSoil5

GRDC code: BWD00056

GRDC Project code: BWD00056