Protecting WA crops

The making of the decision support tool SclerotiniaCM 

SclerotiniaCM developers Fumie Horuichi, Art Diggle and Steve Collins of DPIRD
DPIRD Senior research scientist Art Diggle, DPIRD modelling systems developer Fumie Horiuchi and DPIRD Senior application developer Steve Collins contributed to the development of SclerotiniaCM.

In 2017 Protecting WA Crops published a Sclerotinia stem rot (SSR) issue that discussed the sclerotinia  lifecycle, the environmental factors that contribute to its infection levels and areas of research being undertaken by DPIRD. Since that issue DPIRD has developed a decision support tool to assist growers and consultants with fungicide management decisions for sclerotinia stem rot in canola.

The SclerotiniaCM decision support tool was developed by DPIRD and co-funded by GRDC through the Disease Epidemiology and Management Tools for Australian Grain Growers project in conjunction with national collaborators. This project developed a suite of tools to assist growers with management of yellow leaf spot and stripe rust in wheat, blackleg in canola and powdery mildew in mungbean. A new project is currently developing management tools for field pea blackspot (BlackSpotFPM), canola blackleg upper canopy infection (UCI BlacklegCM) and barley net blotch.

Under conducive conditions SSR can cause over 20% loss in yield. It is one of the most variable and unpredictable diseases for growers, as its incidence varies greatly between paddocks and years, making management challenging. There are a number of factors that determine the disease risk and value of applying fungicide for each paddock sown to canola and these change each season. In addition to this, research by DPIRD has found that fungicide application for sclerotinia stem rot control does not always increase yield, hence is not necessarily economic, despite reductions in disease levels (Figure 1). Determining optimal fungicide timing and whether it may be profitable relies heavily on closely monitoring on-site weather conditions and the growth stage of the crop.

SSR development is highly dependent on seasonal weather conditions and growth stage of the canola crop at the time, as early infections tend to occur on the main stem causing more damage to plants and increasing lodging.

There are three trigger points which are all required for SSR to develop. Firstly, apothecia (tiny cup-like mushrooms ≤5mm) need to germinate from sclerotia (the black rat dropping-like survival structure of the fungus) and this requires cool temperatures and humid/moist conditions, which usually occur when the crop canopy closes over.

Secondly, petal infection occurs when the fruiting bodies (apothecia) release ascospores while the crop is flowering. Petal infection requires high humidity and moisture. Infected petals then fall onto leaves or the axils of canola plants.

Thirdly, plant infection requires specific weather conditions too, as petal infection and even leaf infection does not always result in stem lesion development. Research by NSW DPI and DPIRD has found that SSR symptoms generally develop in canola crops during crop flowering when infected petals drop into the canopy, while relative humidity is continuously over 90 – 95% for 48 hours and temperature is below 25 degrees.

Sclerotinia lesions in canola
Sclerotinia stem rot leaf lesions in canola (© DPIRD, 2022).

One of the challenges of SSR is that foliar fungicide treatments are most effective when applied before SSR symptoms appear. This is why SclerotiniaCM is so useful. The SclerotiniaCM tool incorporates the expert knowledge of national plant pathologists and field research results. The decision support app has been designed to take into account all the major risk factors for sclerotinia stem rot, and its triggers, to give the user a probability of economic return from fungicide applications.

SclerotiniaCM can be used by growers and consultants in the paddock during crop flowering to determine management strategies specific to their cropping circumstances. The user enters their own paddock circumstances including paddock rotation, sclerotinia history, crop inputs, crop growth stage, predicted yield (and price) and expected weather conditions.

SclerotiniaCM gives the user a probability of the economic return from no disease treatment versus one or two fungicide applications. It then calculates what the yield response range is likely to be from the management options selected. Results can be viewed graphically or in tables comparing treated and untreated scenarios. Using the tool will help growers maximise the chances of an economically favourable outcome, reduce unnecessary fungicide application and improve farm sustainability.

As mentioned earlier, field research conducted by DPIRD through GRDC co-funded projects has found that damaging sclerotinia levels in canola are difficult to predict. Analysis of WA trial data from 2013 - 2020 showed that fungicide application for sclerotinia stem rot control is not always economical and does not always increase yield (Figure 1; Andrea Hills) and the SclerotiniaCM tool will assist growers to identify their most profitable management strategy.

Figure 1. DPIRD trials (2013-2020) grouped by yield response or no yield response, where sclerotinia disease incidence was ≥4%.
Figure 1. DPIRD trials (2013-2020) grouped by yield response or no yield response, where sclerotinia disease incidence was ≥4%.

For more information or to download SclerotiniaCM refer to DPIRD's SclerotiniaCM - Sclerotinia management App or GRDC's Validating the SclerotiniaCM app for managing Sclerotinia in canola. Information on how to use SclerotiniaCM is available through this Sclerotinia stem rot in canola in WA webinar.

For more information on Sclerotinia stem rot refer to DPIRD's Managing Sclerotinia stem rot in canola.


Important development work and contributions to supporting scientific information in the development of SclerotiniaCM have been provided by: Ciara Beard, Steve Collins, Jenny Davidson, Art Diggle, Jean Galloway, Andrea Hills, Fumie Horiuchi, Alexander Idnurm, Ravjit Khangura, Kurt Lindbeck, Audrey Leo, Steve Marcroft, Rebecca O’Leary, Susan Sprague, Angela Van de Wouw and Andrew Ware.