Management of early sown wheat: soil water requirements for establishment

Genevieve Clarke1, Kenton Porker2, James Hunt3, Kelly Angel1, Ashley Wallace4

1 BCG, 73 Cumming Ave, Birchip VIC 3483

2 South Australian Research and Development Institute, Hartley Grove, Urrbrae SA 5064

3 Department of Plant, Animal and Soil Sciences, La Trobe University, 5 Ring Rd, Bundoora VIC 3086

4 Agriculture Victoria, 110 Natimuk Rd, Horsham VIC 3400

*Presenting author;



Following the release of new winter wheat cultivars in Australia, growers have been presented with the opportunity to sow wheat early, capitalising on early rainfall. The potential to sow winter wheats early without increasing frost risk may be an important tool for some growers where sowing programs are difficult to keep within optimal windows. However, the effect of early vegetative stress on these cultivars when sown early is not yet fully understood. Experiments were established at two sites in Victoria and one in South Australia in 2017 and 2018 to investigate the amount of soil water required to establish winter wheat cultivars early across different environments. Four establishment dates were targeted; 15 March, 1 April, 15 April and 1 May. We found that 10 mm was sufficient to allow germination and emergence in most soil types and carry plants through until winter. However, when planting in March on heavier soil types, at least 25 mm of rainfall and/or accessible soil water was required for successful establishment and to keep plants alive until late May and early June rainfall.

Recent research into the effects of climate change and extreme weather events on Australian cotton systems

Katie Broughton1, Michael Bange1,2, David Tissue2

1 CSIRO Agriculture and Food, LMB 59, Narrabri, NSW, 2390,

2 Western Sydney University, LMB 1797, Penrith, NSW, 2751


Climate change may have significant impacts on the physiology and yield of cotton. Understanding the implications of integrated environmental impacts on Australian cotton systems is critical for developing management solutions resilient to stress induced by climate change. Uniquely, Australian cotton systems are characterised by high input/high yielding intensively managed systems which may lead to challenges not seen in other research on climate change in cotton. This study combined (1) an analysis of temperature trends throughout key Australian cotton regions, and (2) an investigation into the integrated effect of warmer temperature and elevated [CO2] on physiology and growth of cotton grown in high-input field conditions. The research has demonstrated an increased accumulation of day degrees across a number of important cotton regions from 1957 to 2017, indicating season long temperature effects. This study found that although there was no difference in total biomass between the three treatments, cotton grown at warmer temperatures had greater vegetative biomass and less fruit biomass than the control. Thus, climate change will potentially cause significant rank growth, reducing yield and water use efficiency. Further research is currently investigating whether the recommendation for use of growth regulators to control excessive vegetative growth will need revision for future climates.

Stay-green associates with water soluble carbohydrates in oat

Victor Sadras, M. Mahadevan, Pamela K. Zwer

South Australian Research Institute, Waite Campus, Australia


The aim of this paper was to assess the association between grain yield and canopy senescence quantified with NDVI in oat lines selected for grain yield and milling quality. Sixteen lines were grown in four winter-rainfall environments where logistic curves between NDVI and thermal time from anthesis (GS60) were fitted to return five traits: maximum NDVI, NDVImax; minimum NDVI, NDVImin; thermal time to 50% senescence, x50; rate of senescence, rate; and the area under the NDVI curve, leaf area duration.  Across sources of variation, residuals of yield after removing the effect of phenology correlated with LAD (r = 0.69), NDVImax (r = 0.67), x50 (r = 0.57), NDVImin (r = 0.51) and rate (r = -0.30), all significant at P < 0.05. All five senescence traits correlated negatively with concentration of water soluble carbohydrates at anthesis, particularly area (r = -0.75, P < 0.0001). There was no correlation for yield between environments in 5 out of 6 comparisons (broad sense heritability = 0.39) and water soluble carbohydrates correlated between environments in 6 out of 6 comparisons (broad sense heritability = 0.89). Correlations between environments were irregular for senescence traits. Selection for low concentration of water soluble carbohydrates could increase oat grain yield by improving both grain number per m2 and leaf area duration.


The impact of farming systems with more legumes and nutrient inputs on nitrogen phosphorus and potassium inputs and use

Jon Baird1, Jayne Gentry2, David Lawrence2, Lindsay Bell3, Darren Aisthorpe2, Greg Brooke1, Andrew Erbacher2, Andrew Verrell1, Andrew Zull2, Kaara Klepper4

1NSW Department of Primary Industries, Narrabri, NSW, 2390,

2Qld Department of Agriculture and Fisheries, Toowoomba, Qld, 4350

3 Commonwealth Scientific and Industrial Research Organisation, Toowoomba, Qld, 4350

4 Grains Research and Development Corporation


Farming systems are currently underperforming in terms of yield, due to challenges that include declining soil fertility, herbicide resistant weeds and increasing soil pathogens. Farming system changes are required to maintain and improve productivity. In 2014 long term farming systems research began at seven sites located throughout Queensland and northern New South Wales. These experiments assessed the impact of nine farming systems with respect to numerous measures, including system production and economics, resource use efficiency, pathogen loads/populations, weed populations and soil health. Changes included modifying farming systems to include more legumes and applying fertiliser rates aimed at higher yield potential. The farming system ‘modifications’ impacted several facets of nutritional results. By applying nutrients via fertiliser (nitrogen (N) and phosphorus (P)) to meet the demands of 90th percentile grain yield potential (higher nutrient system), nutrient exports and inputs were balanced, resulting in stable mineral N when compared to current growers’ practice (baseline system) at 10 of the 11 sites. The higher frequency of legumes (higher legume system) increased N and potassium export from the system at most sites (9 of 11 sites), but there was no legacy benefit to plant available N (nitrate and ammonium) for the following grain crops compared to growing non-legume crops. Longer-term examination of farming systems may lead to greater differentiation between systems and geographical location, providing greater insights into the impact different farming systems have on nutrient balances and long-term soil fertility.

Litterbag decomposition and nutrient change study of poultry litter

 Anika Molesworth, Wendy C. Quayle, John Hornbuckle

Centre for Rural and Regional Futures, Deakin University, Hanwood, NSW 2680, Australia


Quantifying in-situ patterns of poultry litter (PL) mass decomposition and changes over time in NO3-N, NH4-N and Colwell P when applied alone or in combination with urea fertiliser helps farmers to synchronise nutrient additions to the soil with crop requirement. Using a buried litterbag technique in the field, decomposition and nutrient changes followed a two-phase pattern suggesting labile and recalcitrant PL components. Twenty-five days after burial (DAB), PL at 10 cm in loam soil contained64% dry matter (DM), 66% NO3-N, 16% NH4-N, and 69% Colwell P compared with initial concentrations at burial. After 27 DAB, PL in a clay loam had 73% DM, 8% NH4-N and 85% Colwell P remaining compared with initial concentrations, with increases of 6 times in NO3-N. Using an exponential model to estimate PL remaining values from day of burial until final excavation in the loam, it was determined there was 63% DM, 6% NO3-N, 5% NH4-N and 55% Colwell P remaining. After another 43 days buried in the clay loam, there was 63% DM and 2% NH4-N remaining of initial PL values, a 1.2 increase in NO3-N, while Colwell P had returned to starting levels. The rate of PL-N:urea-N had significant effect on NH4-N in phase 2, with greater concentration with higher litter ratio. Since only ~5% of starting PL NH4-N remained at the end of the experimental period on both soil types, the data indicates timely application of PL is required to synchronise any short-term N fertiliser benefit to a developing crop. The free-draining nature of the loam compared with the heavier clay loam are likely to be the main drivers of difference in PL decomposition and nutrient change observed between soil types. The patterns suggest that PL may better fulfil the expectations of a slow release nutrient source in a clay loam than a loam.

Stubble load increases frost severity, duration and damage in frost-prone landscapes in south-western Australia

Ben Biddulph1 Rebecca Smith2, Chloe Turner3 Karyn Reeves4 and Sarah Jackson1

1Department of Primary Industries and Regional Development

2 Living Farm.

3 Facey Group

4SAGI West /Curtin University

Corresponding author:


Frost damage across Western Australia’s cropping regions causes annual losses estimated to be between $100 and $300 million each year. This paper reports on results from field experiments in 2014-2016 investigating whether increasing stubble load influences the severity, duration and damage from spring frost events in wheat crops in WA. In most experiments, increasing stubble load increased the severity and duration of spring frost events. Increased stubble load also increased frost damage and resulted in lower grain yield under moderate and severe frost damage conditions.  Reducing stubble load is one tool growers can use as part of a comprehensive frost management plan.

Can we close crop yield gaps in Australia?

Zvi Hochman1, Airong Zhang2, Marta Monjardino3, Heidi Horan1

1 CSIRO Agriculture and Food, Queensland Bioscience Precinct, 306 Carmody Road St Lucia QLD 4067, Australia;

2 CSIRO Health and Biosecurity, EcoSciences Precinct, GPO Box 2583, QLD 4001, Australia

3 CSIRO Agriculture and Food, CSIRO Waite Campus, Waite Road, Urrbrae SA 5064, Australia


Why do Australian grain growers achieve only half the yield potential of their crops? We took three approaches to investigate this question. First, we applied in silico experimentation to quantify the impact of eight suboptimal practices at 50 sites across the grain zone. This analysis highlighted the critical importance of nitrogen nutrition. Other management-related factors included: conventional tillage, summer weeds, low seedling density and late sowing. Second, we interviewed 232 wheat producers from 14 contrasting local areas. The findings linked yield gaps to farm and grower characteristics as well as to farming management. Farms with smaller yield gaps are more likely to be smaller holdings growing less wheat on more favourable soil types. Growers with smaller yield gaps are more likely to apply more N fertiliser, to have a greater crop diversity and to be less likely to grow wheat following either cereal crops or a pasture; they are more likely to soil-test a greater proportion of their fields, use a fee-for-service agronomist, have a university education and adopt new technologies, and they are less likely to have problems with herbicide-resistant weeds. Third, we applied a profit-risk-utility trade-off analysis and showed that risk aversion has a strong influence on the choice of practice in low yield potential sites, which help explain yield gaps in those agro-climatic zones. However, in medium to high yielding areas, applying the management inputs required to achieve water-limited yield is the most economical choice even for highly risk averse growers.

Crop simulation for farming systems: from phenotype to farm

Julianne Lilley

CSIRO Agriculture and Food, GPO Box 1700, Canberra ACT 2601, Australia


The value of simulation models to assist (i) crop breeding, (ii) agronomic research, and (iii) farm decision-making has been demonstrated in many studies (Holzworth et al. 2014; van Ittersum and Donatelli 2003). In the Australian grains industry several modelling platforms have been developed for a variety of needs, with APSIM (Agricultural Production Systems Simulator) the predominant tool (Robertson et al. 2015). APSIM allows models of crop and pasture production, residue decomposition, soil water and nutrient flow, and erosion to be configured to simulate soil and crop management for various production systems using conditional rules (Holzworth et al. 2014). The model has been well validated in many studies and shown to accurately capture the effects of variability in climate, soil type and management for a range of crops. Linking of APSIM and GRAZPLAN farming systems models (Moore et al. 2007) has also enabled assessment of whole farm issues associated with crop and animal production as well as environmental impacts of a range of practices on mixed farms (Lilley and Moore 2009, Robertson et al. 2009).

In this paper I discuss application of the APSIM model at three scales; (i) the value of individual genetic traits within the context of the farming system, (ii) single or multiple changes to management practices for individual crops over multiple years and locations, and (iii) the effect of a management or genotype change, in the context of multi-year sequences, or multiple paddocks across the whole farm. Case studies at each scale will demonstrate the value of simulation modelling as an integrated tool in modern farming systems research.

Using machine learning to sharpen agronomic insights to improve decision making in Australian cotton systems

Kavina Dayal1, Tim Weaver2, Michael Bange2, CSD Ltd. Extension & Development Team3

1 CSIRO Agriculture & Food, 15 College Road, Sandy Bay, TAS, 7005,,   

2 CSIRO Agriculture & Food, 21888 Kamilaroi Highway, Narrabri, NSW, 2390

3 Cotton Seed Distributers Ltd., 2952 Culgoora Road, Wee Waa, NSW 2388


The ability to understand the impact of genetics x environment x management (GxExM) influences at a farm and paddock scale offers significant opportunities for informing management interventions to raise crop productivity. New means of agronomic data collection and collation, along with machine learning statistical approaches can help realise these opportunities. Cotton Seed Distributors Ltd. agronomy and extension team collect a large number of crop physiological and agronomic characteristics every year in their key varieties across the whole industry. Over the past four seasons this has resulted in the collection of a significant dataset for in-depth modelling. A machine learning algorithm (i.e., Random Forest) has been applied to understand which measured variables affect yield which can be used to identify management interventions. To evaluate the approach, the Random Forest method was applied to the dataset using key variables only during first flower. Variables were then used to predict yield at this stage (r2 = 0.74). The machine learning algorithm is intended to form the back bone of a decision tool so that crop managers can access the insights being generated from the dataset in real time and project current crop performance, giving them the ability to investigate the consequences of management interventions.


Profitable management packages for canola

Elizabeth Meier1, Julianne Lilley2, John Kirkegaard2, Jeremy Whish1, Therese McBeath3

1CSIRO Agriculture and Food, 306 Carmody Road, St Lucia Qld 4067, Australia,,

2CSIRO Agriculture and Food, GPO Box 1700, Canberra ACT 2601, Australia

3CSIRO Agriculture and Food, Waite Road, Urrbrae SA 5064, Australia


In rotations, canola can provide a disease break for cereals and a broader spectrum of herbicide options to reduce the risk of herbicide resistance in weeds. However, canola can have higher costs of production than cereal crops. We therefore sought to identify combinations of management practices that would maximise gross margins and reduce the risk of financial loss from growing canola. We simulated continuous canola management packages (combinations of in-season N fertiliser rate, cultivar choice, time of sowing) for 50-years. To compare practices identified for contrasting environments we report results from two locations with relatively high and low average annual rainfall at Breeza, NSW and Minnipa, SA, respectively.  Management practices made little contribution to gross margins unless climate variability was accounted for so results are presented within a framework of a hypothetical, always-correct seasonal rainfall forecasts and sowing opportunities. Regionally specific packages of the most profitable practices for sowing single canola crops were identified that can be adopted as sowing opportunities arise. These packages broadly included: decreasing N fertiliser rate in lower rainfall deciles and/or as the growing season progressed; a change in choice of cultivar rate of development from slow to fast when sowing was delayed; and selection of a conventional or hybrid cultivar at Breeza. These findings were relevant despite the lact of perfect seasonal forecasts available for growers.



The Australian Society of Agronomy is the professional body for agronomists in Australia. It has approximately 500 active members drawn from government, universities, research organisations and the private sector.

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