Accounting for pest and diseases in crop models: A case study on Blackleg (causal agent: Leptosphaeria maculans) and canola (Brassica napus)

Jamina Bondad1,2, Dr Jeremy Whish1, Matthew Harrison2, Kara Barry4 

1CSIRO Agriculture and Food, Brisbane, Australia, 2University of Tasmania, Burnie, Australia, 3CSIRO Agriculture and Food, Canberra, Australia, 4University of Tasmania, Hobart, Australia

Understanding the dynamics of pests and diseases within the farming system and the ability to relate incidence and seasonal conditions to yield loss, is the next challenge for the agricultural science community (Donatelli et al., 2017). This highlights the potential of existing crop models to expand their simulation scope and account for biotic stressors. The addition of a lifecycle module to the APSIM Next Generation framework allows for the development of pest and disease models that interact seamlessly with existing crop models but is yet to be tested. To do this, we use Blackleg disease and canola crop as the case study. The development of a Blackleg lifecycle model linked to a canola crop model could do more than support capabilities such as scheduling, scouting or pesticide application.  Currently the management of Blackleg relies on an estimated threshold. The threshold is used to help identify when a pest population needs to be reduced to prevent yield loss. This approach is often prescriptive and or reactive. The development of a dynamic blackleg model within the APSIM next gen framework will enable disease management decisions to be predictive and give the farmer the ability to interact with the environment. This paper reports on the development of a blackleg model within APSIM and presents some early results from key lifecycle stages.


APSIM NextGen Canola model – new flexibility and functionality

Dr Julianne Lilley1, Dr Jeremy Whish2, Dr Neil Huth3, Dean Holzworth3, Neville Herrmann1 

1CSIRO, Canberra, Australia,

2CSIRO, St Lucia, Australia,

3CSIRO, Toowoomba, Australia


The Agricultural Production Systems sIMulator (APSIM) consists of a suite of models developed to simulate the soil, crop and management interactions of farming systems. The canola model was developed in the late 1990s and has been used to investigate different aspects of canola production across Australia ever since. More recently the APSIM Initiative has been building the next generation of APSIM to create a simulation framework that can run larger and more complex simulations at multiple temporal and spatial scales. The Plant Modelling Framework for APSIM NextGen is more versatile and the efficiency of capturing our understanding of crop processes within the model is improved. For example, new routines describing genetic parameters, or the physiological response to new traits or events such as abiotic or biotic stress are readily incorporated, modified and tested.

The new APSIM Next Gen Canola model has been validated against an extensive set of detailed phenology observations (n>400) and yield observations (n>1000) from field experiments that include a wide range of cultivars, locations, seasons and agronomic treatments. A feature of the new model includes improved phenology prediction by better accounting for response to vernalisation and thermal time with parameters to describe new cultivar phenotypes. This allows the evaluation of a novel phenology type in the farming system and improved prediction of canola development beyond the traditional growing regions.


Dr Julianne Lilley is Team Leader of the Integrated Agric Modelling & Decisions team within Agriculture and Food which develops and uses soil, crop, pasture and livestock models in a farming systems context for application in agricultural research across Australia and internationally. Julianne is a crop scientist with over 25 years research experience in crop physiology. Her research has included climate change impacts, crop root system function, crop water-use efficiency, dual-purpose cropping, whole-farm productivity and resource protection. She applies crop physiological understanding embedded within crop simulation models to greatly expand the outcomes of experiments and draw robust conclusions about the impacts of agricultural management decisions.

She is currently leads research investigating farm management practices which optimise profitability of canola, understanding environmental triggers and the underlying genetic control of flowering in canola, and developing the Yield Gap Australia website, a tool developed at CSIRO to inform policy makers and grain producers of the gap between potential and actual yields from local to national scale.

Slow early versus fast late – which works best and where?

Rohan Brill1, John Kirkegaard2, Danielle Malcolm3, Andrew Ware4

1Brill Ag, Ganmain, Australia,

2CSIRO, Canberra

3NSW DPI, Wagga Wagga

4EP Ag Research, Port Lincoln


Optimum start of flowering dates are established for canola across much of Australia but it is possible to flower at the optimum time by sowing slow varieties early or fast varieties later. We conducted 14 experiments across eastern Australia in 2017 and 2018 to determine the optimum sowing strategy (sowing date and phenology type) across a range of yield scenarios (0.4 to 5.7 t/ha). We found that early sowing of slow developing varieties was most successful at sites that had received high (>200 mm) fallow rainfall. At these sites there was also a consistent benefit of selecting a high vigour hybrid variety compared with a low vigour open-pollinated triazine tolerant variety. Later sowing of fast developing varieties was advantageous at low yielding sites and surprisingly at very high yielding sites. Canola growers can adjust their canola sowing strategy (sowing date and phenology type) based firstly on fallow rainfall and secondly on expected in-crop rainfall.


Rohan is an agronomist and farmer with Brill Ag (since 2020) at Ganmain in southern NSW with current research, development and extension projects in canola and pulses.  Previous to this, Rohan was an agronomist with NSW DPI at Wagga Wagga, focussing on tactical canola agronomy.

Developing a wild brassica diversity panel for canola improvement

Ms Jane Brownlee1, Mr Chris Herrmann1, Mr Matthew Nelson1 

1CSIRO, Floreat, Australia

Canola (Brassica napus L.) is a young species (<7500 years old) with a short history of crop improvement. Its narrow genetic base and limited diversity provides a significant challenge for canola breeders to make continual productivity gains while increasing the resilience of varieties to a range of environmental stresses and disease pressures.  In contrast, the wild relatives of canola are extremely diverse but have rarely been used effectively in canola improvement. This project is assembling a diverse panel of primarily diploid Brassica species focusing on wild accessions and oilseed types. The aim of this work is to identify useful traits and to rapidly transfer these to canola using efficient crossing and gene editing strategies.

We have mapped the origins of 922 wild Brassica accessions from 38 taxa held in international seed collections (and listed in the Eurisco database). With collaborators in the USA and Australia we are identifying key gaps in seed collections to prioritise regions for future seed collection activities. With the assistance of the Australian Grains Genebank, we are importing a broad representation of wild Brassica and non-B. napus oilseed species from international seed collections. So far, we have grown out 135 accessions from 19  different taxa from 23 countries for seed multiplication and preliminary phenotypic evaluation (including vernalisation requirement, self-incompatibility, colour, leaf waxiness, days to flowering and maturity). Intensive phenotypic and genotypic evaluations are planned. This genetic resource will be a valuable source of useful genetic and trait diversity for the genetic advancement and research of canola.


Jane Brownlee completed a Bachelor of Environmental Science (Honours), at Carleton University, Ottawa, Canada in 2014. During her honours she worked as a Research Assistant at the Ottawa Research and Development Centre, Agriculture and Agri-Food Canada and explored the relationship between plant height and severity of infection of Fusarium Head Blight in spring wheat. In 2015 she moved to Australia as Senior Research Technician at Sugar Research Australia, Townsville, where she worked alongside Dr Frikkie Botha, QAAFI and the University of Queensland investigating the causes of Yellow Canopy Syndrome in sugarcane. Jane later moved to Perth, Australia, to work as a Glasshouse Lead Coordinator at Intergrain, working with early-stage breeders to improve wheat and barley crop performance in new varieties.  Jane joined CSIRO in Perth, Western Australia, in 2019 and is involved in research exploring chilling tolerance in wild cicer where she is measuring phenology, biomass production and partitioning, water-use, stress onset, and the traits that mitigate these. Jane is also involved in work with wild brassicas to improve genetic diversity in canola and is particularly interested in using wild germplasm to broaden the adaptive and genetic base of elite, modern crops.



Manipulating canola canopies through agronomy & genetics in the high rainfall zone

Dr Jens Berger1, Dr Andrew Fletcher1, Mr Sam Flottmann1, Mr Adam Brown1, Dr Heping Zhang1, Jeremy Curry2, Mark Seymour2 

1CSIRO, Wembley, Australia,

2DPIRD, South Perth, Australia


Canola production is becoming increasingly important in the high rainfall zone, where yield is determined primarily by biomass, trading off harvest index (HI).  However, input management for high biomass production carries greater financial risk, particularly if  rainfall is below average. Moreover, high biomass production can have negative consequences for growers, including harvesting difficulties associated with tall crops, high stubble loads and in-season water use, and increased Sclerotinia risk.

To understand grower capacity to influence the canola yield/harvest index trade-off we used a factorial range of agronomic and genetic levers to manipulate canopy size and yield potential in on-farm HRZ trials:

  • Cultivar: high vigour (RR) versus low vigour (TT)
  • Plant density
  • Input levels (N x S)
  • Early season grazing

These treatments had a huge impact on plant height (119-176 cm), biomass (8.2-15.7 t/ha) and yield (1.9-6.2 t/ha).  Yield differences were driven by HI, while HI was dominated by genetics and its interaction with agronomy.  HI was lower in RR than TT canola but there were important differences/interactions within both groups.  High HI cultivars had stable HI that was not modified by agronomy (TT: Invigor 450 (35%), Hytech Trophy (34%); RR: GT 53 (32%), P45Y28 (29%)).  Low HI cultivars (TT: P45T03 (29%); RR: H540XC (23%)) further reduced their HI in treatments that increased biomass.  Experiments are currently underway to unpick this contrasting interaction.

By understanding biomass partitioning in canola we hope to de-risk production for growers giving them the tools to manage the canopy they require.


Jens has almost 30 years experience studying adaptation of dryland crops using a combination of physiology, genetics and agronomy.  The CSIRO canola team has been using these approaches to focus on the performance of canola across Western Australian rainfall gradients.

Quantitative blackleg resistance in the host differentially interacts with L. maculans isolates

Dr Susie Sprague1, Dr Luke Barrett1, Dr Wendelin Schnippenkoetter1, Dr Angela Van de Wouw2, Dr Steve Marcroft3 

1CSIRO Agriculture And Food, Canberra, Australia, 2University of Melbourne, Parkville, 3010, 3Marcroft Grains Pathology, Horsham, 3400

Blackleg, caused by Leptosphaeria maculans, is a constant threat to canola production in Australia with growers relying on disease resistance for control. Australian canola cultivars have two types of resistance to blackleg: complete or major gene resistance (MGR) and partial or quantitative resistance (QR). MGR can be rapidly overcome while QR is considered a more sustainable resistance and is generally assumed to be partially effective against all blackleg isolates. We conducted controlled experiments in which cultivars differing in QR were inoculated with homogeneous (single spore isolates) or heterogenous (populations of ascospores) to determine the interaction between host and pathogen genotype by assessing severity of leaf lesions produced on cotyledons and crown canker severity at maturity. There were significant host x isolate interactions at different stages of disease development. These interactions were significant for the size and severity of lesions on the cotyledons and in the crown at maturity but were inconsistent between experiments and seasons. Ascospore populations appear to produce a more consistent level of disease amongst cultivars, probably because they are highly heterogeneous. QR does not give partial resistance to all isolates, but instead reacts with individual isolates differently. This finding is highly significant, particularly in the context of developing a robust phenotyping method and needs to be considered in the context of ascospore or pycnidiospore inoculum.


To come

Optimising Canola Phenology for Australian Growing Environments

Dr Chris Helliwell1, Dr Alec  Zwart1, Alex Boyer1, Andrew Gock1, Dr Bangyou Zheng2, Dr Bill Bovill1, Brett Cocks2, Emmett Leyne1, Dr Ian Greaves1, Dr Jeremy Whish2, Dr Jing Wang1, Dr Julianne Lilley1, Dr Matthew Nelson3, Dr Susie Sprague1, Dr Shannon Dillon1 

1CSIRO Agriculture And Food, Canberra, Australia,

2CSIRO Agriculture and Food, Brisbane, Australia, 3CSIRO Agriculture and Food, Perth, Australia

Increased production and profitability of canola can be achieved by better matching phenology with the growing environment. Improved understanding of the factors determining canola phenology will better enable matching of location-specific growing conditions with variety, and direct breeding strategies for improved high yielding canola varieties that match the optimum flowering window. In this project we are taking the novel approach of combining existing crop modelling and knowledge of flowering processes with large-scale phenomic, ‘omic and environmental data to deliver (1) predictive tools to better inform management of canola genetic resources for optimal productivity across a range of environments, and (2) knowledge of genetic and environmental factors underpinning variation in phenology. The team have assessed phenological traits in a diverse set of ~350 modern Australian and globally important canola genotypes across the range of Australian canola growing environments as well as controlled environments. To complement the phenology data, dense genomic SNP and transcriptome data were generated. Genetic diversity in the panel reflected geographic and crop/maturity type and supports earlier reports of the prominence of Asian germplasm in the pedigrees of Australian cultivars. Genome wide associations of preliminary transcriptome, SNP and phenotype data in these experiments identify known and novel factors underpinning phenology traits. Results from a range of model frameworks to predict phenology and parameter traits using SNP data suggest it is possible to predict these traits based on genome data within sites. The new information and tools generated will better enable management of canola genetic resources for optimal productivity.


Dr Chris Helliwell is the Project Leader – Functional genomics for canola traits.

Capturing phenological diversity in canola using fewer key environments

Dr Jeremy Whish1, Dr Julianne Lilley2, Dr Susan Sprague2, Mr Brett Cocks3, Ms Brook Anderson3, Ms Nell Evens7, Mr Barrett Sinclair5, Mr Andrew Ware6, Mr  Matthew Nelson4, Dr Bill Bovill2, Dr Bangyou Zheng1, Mr Alexandre Boyer2, Dr Shannon Dillon2, Dr Chris Helliwell2 

1CSIRO Agriculture and Food, St Lucia , Australia,

2CSIRO Agriculture and Food, Canberra, Australia,

3CSIRO Agriculture and Food, Toowoomba, Australia,

4CSIRO Agriculture and Food, Wembley, Australia,

5Kalyx Australia , Perth , Australia,

6EPAG Research , Port Lincoln, Australia,

7Kalyx Australia , Young , Australia


Phenological development in canola is driven by temperature (thermal time, vernal time) and daylength which vary significantly across Australian canola-growing region.  Minimising the number of sites, seasons and sowing dates required to understand these responses in a large diversity panel of canola germplasm is desirable.  We examined the accumulation of thermal and vernal time across Australia to identify a minimum set of environments that could adequately separate the phenological drivers among the varieties.  Using the cardinal temperatures for thermal and vernal time accumulation previously established for canola, a series of long-term simulations using historic weather data were conducted across relevant environments and sowing dates in Australia.  The ratio of vernal to thermal time accumulation was used to remove duplicate environments until eight overlapping environments, comprising four sites (Boorowa NSW, Beverly WA, Gatton QLD and Cummins SA) with mid-April and mid-May sowing were identified. (Table 1).  Concentrating efforts at four sites with two sowing dates has facilitated an intensive and cost-effective sampling strategy to identify flowering response in a large diversity panel.

Table 1.  Minimum environment set with differing ratios of vernal and thermal accumulation

  1. Fast-Vernal : Slow-Thermal (Boorowa NSW, May-15)
  2. Fast-Vernal : Moderate-Thermal (Boorowa NSW, April-15)
  3. Moderate-Vernal : Decreasing-Thermal (Beverley WA, May-15)
  4. Moderate-Vernal : Slow-Thermal (Beverley WA, April-15)
  5. Moderate-Vernal : Moderate-Thermal (Gatton Qld, May-15)
  6. Slow-Vernal: Fast-Thermal (Gatton Qld, April-15)
  7. Very-slow-Vernal : Fast-Thermal (Cummins SA, May-15)
  8. No-Vernal : Fast-Thermal (Cummins SA, April-15)


Dr Jeremy Whish is a Principal Research Scientist. He uses modelling to understand the complexity of farming systems and identify management strategies to reduce production risk. He has published broadly on many aspects of the farming system including biotic and abiotic constraints, crop physiology, phenology, and risk within the management of crops and rotational sequences. 

Hyperyielding Canola Year 1 – Management for 5 t/ha canola

Rohan Brill1, Darcy Warren, Kat Fuhrmann, Nick Poole 

1Brill Ag, GANMAIN, Australia, 2FAR Australia, , , 3FAR Australia, , , 4FAR Australia, ,

The Hyperyielding Crops project was rolled out across mainland Australia in 2020 with canola sites at Wallendbeen, NSW; Gnawarre, Victoria; and Millicent, South Australia. The aim of the project for canola is to determine the management strategies that achieve 5t/ha of canola in these environments. The primary management strategies investigated in 2020 included, cultivar choice, nutrient management, disease management and plant density. Yield of the best treatment in 2020 was >5t/ha at Wallendbeen and just below 5t/ha at Gnawarre and Millicent. The highest yielding treatment was generally at least double the yield of the lowest yielding treatment at each site. Cultivar choice was the single most important influence on yield variability at all three sites, on average accounting for 2 t/ha difference in yield. Nitrogen management was the next most important influence on yield, accounting for an average 1.2 t/ha difference in yield. Fungicide response was small at Wallendbeen (0.3 t/ha) and Gnawarre (0.2 t/ha) and not significant at Millicent. Where there was a yield response to fungicide recorded it was difficult to attribute the yield loss to any one disease. Plant density had no impact on yield at Wallendbeen and Gnawarre but there was a small penalty from low (<15 plants/m²) at Millicent. Similar trials incorporating an early sowing of winter canola will be included at the three sites in 2021 as well as at Frankland River in Western Australia.


Rohan is an agronomist and farmer with Brill Ag (since 2020) at Ganmain in southern NSW with current research, development and extension projects in canola and pulses.  Previous to this, Rohan was an agronomist with NSW DPI at Wagga Wagga, focussing on tactical canola agronomy.



Was fungicide application worthwhile on canola in southern and central NSW in 2020?

Rohan Brill1, Maurie Street2, Chris Minehan3, Nick Poole4, Ben O’Brien

1Brill Ag, GANMAIN, Australia

2Grain Orana Alliance

3Rural Management Strategies

4FAR Australia


Canola fungicide response trials were conducted at eight locations across southern and central NSW in 2020, from the high yield potential, intensive production environment of Wallendbeen in the south-east, to the less intensive Warren in western NSW. Seven of the trials were conducted on commercial paddocks and one was conducted on small plots. The main diseases present were sclerotinia stem rot on branches/stems; upper canopy blackleg on branches/stems (and pods to a lesser extent); alternaria black spot on branches/stems and pods; and powdery mildew on branches/stems. In general, sclerotinia and blackleg infection was greater in southern NSW, while alternaria black spot and powdery mildew infection was greater in central NSW. Fungicide application reduced disease symptoms (compared to the untreated control) at all sites but yield responses were varied. There was no yield response at three sites – Galore, Ganmain and Warren. There was a small yield response at Barmedman (0.14 t/ha) which would have only just covered the cost of application. Yield responses were stronger at Wellington (0.26 t/ha), Wallendbeen (0.31 t/ha), Kamarah (0.40 t/ha) and Temora (0.66 t/ha). The Temora and Kamarah sites had moderately high levels of upper canopy blackleg as well as minor (Kamarah) and moderate (Temora) sclerotinia infection and yield response at these sites was most likely due to a reduction in both diseases. A single spray of fungicide at the 30% bloom stage was generally the most profitable treatment where yield responses were observed.


Rohan is an agronomist and farmer with Brill Ag (since 2020) at Ganmain in southern NSW with current research, development and extension projects in canola and pulses.  Previous to this, Rohan was an agronomist with NSW DPI at Wagga Wagga, focussing on tactical canola agronomy.

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