Optimised canola profitability
An overview of 5 years of canola agronomic research in South Australia.
Authors: Andrew Ware and Jacob Giles (SARDI), Rohan Brill (NSW DPI), Therese McBeath, Julianne Lilley and John Kirkegaard (CSIRO)
Take Home Messages
Match sowing time to varietal phenology to flower in the optimal window and maximise biomass to maximise yield.
Phenology information for most new varieties is now available.
Well adapted hybrids can produce high, stable yields in the low rainfall zone.
Background
Since 2014 research to better understand the yield drivers of canola has been conducted in southern and eastern Australia in the GRDC funded Optimized Canola Profitability Project (OCP). The aim was to improve canola profitability through a better understanding of how phenology and environment can guide tactical agronomy to improve canola yield and profit. This research is targeted at low to medium rainfall zones and is a collaboration between CSIRO, NSW DPI and GRDC, in partnership with SARDI, CSU, MSF and BCG (CSP00187). The project links closely with similar GRDC supported projects in Western Australia and high rainfall zones (HRZ).
From southern Queensland, down through New South Wales, into Victoria and across to South Australia the OCP Project has conducted a range of field experiments and modelling simulations to improve canola profitability in the region. Activities have included:
Phenology experiments, to determine the triggers for canola development, to help understand when a variety will flower in a particular environment.
Variety x time of sowing experiments, to determine how flowering time influences canola yield and water use efficiency across a range of environments.
Critical stress period experiments, to determine the period (growth stage) when canola yield is most vulnerable to external stresses such as water, heat or frost.
Risk management experiments, aimed to make canola yield more stable profitable in the low rainfall zone.
Experiments to improve the way the canola accumulates biomass cost-effectively to optimise grain yield across a range of environments. Biomass accumulation drives yield as harvest index is reasonably stable.
Improving the ability to model canola growth and yield using APSIM. The canola model was developed some time ago with older varieties and different farmer practices. The improved model has added considerable value to field experiments.
Improving harvest management, particularly through improved windrow timing. Despite a focus in northern NSW, the message to not windrow too early (with significant yield penalty) holds true in the southern region.
This article will discuss how findings from these activities are being integrated to help improve canola profitability.
Field experiments and modelling conducted in the first few years of the project helped to better understand the drivers of canola development (temperature, day length) in modern varieties, as well as improving the understanding how early sowing of canola influences varietal phenology (flowering time) and grain yield. This information then helped to improve the ability to simulate canola growth under Australian conditions, so that models could be used to evaluate a range of scenarios not possible in just a few years of field experiments.
One of the key findings in this phase of the project, was that canola yield was optimised by ensuring that canola started flowering in a window where the effects of heat/ drought and frost on flowers and pods were minimised. The dates for the flowering window were specific to each locality, depending on the risk of heat and/or frost events.
An example of this is the trial conducted in 2018 at Yeelanna (Figure 1). The longer season variety, Archer CL performed well relative to the other varieties when planted early (14 April), whereas shorter season variety Nuseed Diamond improved in grain yield when planted later (8 May). At the later sowing time, the lower yielding Archer treatment flowered too late (3 Sept) (Table 1) compared to the optimal start of flowering around 12 Aug, and the lower yielding Nuseed Diamond treatment flowered too early (5 July) compared to the more optimal 3 August.
Figure 1. Grain yield (t/ha) of 2018 Yeelanna time of sowing x variety experiment with sowing dates of April 14 and May 8 (error bars = lsd).
Table 1. Start of flowering dates (when 50% of plants have at least one open flower) for the 2018 Yeelanna time of sowing x variety trial. The optimal start of flowering for Yeelanna is 19 July.
Sowing Date
Using APSIM crop modelling, meteorological data and information gathered from field experiments over the past four years, optimal start of flowering dates can be generated for any canola growing locality in Australia (some of these can be found in the e-book: https://grdc.com.au/10TipsEarlySownCanola). Once the phenology characteristics of a variety are understood (i.e. how long it will take a variety to flower in a given environment) it is possible to work backwards from the optimal start of flowering date to find an optimal sowing date (Table 2) for a locality.
Table 2. Sowing time guidelines for phenology types at three South Australian locations.
Variety Phenology
The method that many of the canola breeding companies use to classify variety development is largely based on time to maturity, relative to other varieties sown at a conventional sowing time, and not measured by time to reach flowering when sown early. Also, canola varieties can rapidly change. Many of the varieties that were used in the first few years of the OCP Project are now no longer available.
To better categorise the development speed of canola varieties, particularly in relation to early sowing, and to gather information on newly released varieties, four experiments were established across Australia in 2018 (Perth - WA, Port Lincoln- SA, Wagga Wagga – NSW and Trangie – NSW). The sites were selected for their range in climatic conditions. The experiments recorded the time to reach the start of flowering (50% of plants with one open flower) from early and more conventional sowing times. Results for the Port Lincoln site are presented in Figure 2.
Figure 2. Date of start of flowering of canola varieties sown at two dates (16 April and 18 May) near Port Lincoln in 2018.
These data show that while most of the varieties rank similarly in their time to start flowering regardless of sowing time, there are some notable exceptions, for example, Hyola 580CT will flower at a similar time to many of the mid phenology varieties when sown in May, but flowers very quickly and outside the optimum when sown in April. Sowing early also increases the differences to flowering time, largely due to the warmer temperatures in April accelerating plant development of the varieties that are most sensitive to temperature. This means, that sowing a variety with fast phenology early will flower considerably quicker (in calendar days) than if it was sown at a more conventional time, and often outside the optimum window.
By adding the data from the four phenology trial sites conducted in 2018 to data previously collected in the optimised canola profitability project it is possible to categorise each of the modern varieties for its phenology type in early sowing situations (Table 3).
Table 3
Table 3. Phenology and maturity rating of most of the modern canola varieties.
* Varieties with three site years of data. Remaining varieties have at least five site years of data.
Matching the planned sowing time (or most common break to the season) from Table 2 with a variety that has the correct phenology (from Table 3) is now possible. For example in the Yeelanna environment on Lower Eyre Peninsula, the most common break to the season often occurs in the last week of April. If planting in the last week of April, growers in this environment have the choice of growing any variety from fast to mid phenology and have it flower in the optimal window. However, for growers at Lameroo, who may commonly get a break to the season in early May, the best chance of flowering in the optimal window and maximising yield will come from planting only fast phenology varieties.
Risk Management
Two of the factors that add considerably to canola’s risk profile in the low rainfall zone is (i) the crops high demand for nitrogen and (ii) the decision of whether or not to grow a hybrid or open pollinated variety. Being able to understand how effectively canola is able to convert soil available and applied nitrogen to yield across a range of soil types in the low rainfall environment will help identify a strategy that delivers the highest yield at the lowest risk. In 2018, field experiments examining this were conducted at Karoonda, Minnipa and Lameroo. Just the Karoonda experiment will be discussed here.
The Karoonda trial was sown on 4 May across a range of soil types, typical of many Mallee type environments, ranging from dune sand, down through the mid-slope and into the swale. Varieties Stingray and Pioneer 43Y92CL were planted and nitrogen applied at differing rates early post-emergent. On the day of sowing, the sand averaged 37 kg mineral N/ha/m depth and 92 mm PAW while the mid-slope averaged 53 kg mineral N/ha/m depth and 84 mm PAW. Rainfall to end September was 114 mm compared with 257 mm average
Table 4. Canola grain yield (t/ha) at Karoonda, 2018. Two varieties, sown across four soils types with different nitrogen strategies applied early post-emergence.
Grain yield results from this trial show that hybrid Clearfield® variety Pioneer 43Y92CL yielded higher than ATR Stingray in all soil type zones at comparable nitrogen rates. 43Y92 yield was relatively stable across all soil types (ranging from 0.92t/ha – 1.16t/ha) and produced a higher level of yield than Stingray when compared at 5 and 90 kg N/ha, suggesting a higher N use efficiency Stingray produced a positive response to N in all soil types, with the largest response to high rates on the crest and dune soils, but yield was more variable than 43Y92 across soil types.
The obvious way to reduce risk in canola production in the low rainfall zone is to reduce some of the upfront costs, such as the cost of hybrid seed. However, as results from this trial and other observations in the low rainfall zone show, the adoption of well-adapted hybrids has the potential produce high, stable, N use efficient yields that are potentially more profitable than lower cost open pollinated varieties. Previous recommendations to not grow hybrids in low rainfall environments should be reconsidered.
Conclusion
Matching sowing time with varietal phenology so that start of flowering occurs in a window where the risk of water, heat and frost stress is minimised will greatly improve the chances of maximising yield.
Phenology information on most of the currently available canola varieties, particularly their response to early sowing, is now known, and can be used to aid variety selection.
Well-adapted hybrid varieties planted in the low rainfall zones have been shown to produce high, stable canola yields in a well below average rainfall season.
Useful resources
https://grdc.com.au/Resources/GrowNotes
https://grdc.com.au/10TipsEarlySownCanola
Acknowledgements
The research undertaken as part of this project is made possible by the significant contributions of growers through both trial cooperation and the support of the GRDC, the authors would like to thank them for their continued support.
This work is a component of the 'Optimised Canola Profitability' project (CSP00187) a collaboration between NSW DPI, CSIRO and GRDC in partnership with SARDI, CSU, MSF and BCG.
Thank you the South Australian growers and Hart Field Site group for making their land available for the field trials and to the technical officers of the SARDI New Variety Agronomy group for their assistance in conducting the field trials.
Contact details
Name: Andrew Ware
Business Address: EPAG Research, 7 Seaton Ave Port Lincoln, 5606
Phone: 0427 884 272
Email: andrew@epagresearch.com.au
Twitter handle: @Ware_AH