Take Home Messages
- BCG has established three farming systems trials to be run from 2023 to 2026.
- These are part of a network of trials within the Farming Systems South project (GRDC-University of Adelaide).
- Initial indication of the likely difference in farming systems outcomes depends on environment and management.
- Stay tuned for outcomes of farming systems trials in subsequent years.
Aim
The aim of the trials is to understand what factors affect the success and economic return of farming systems implemented throughout the Victorian Mallee and Wimmera regions.
Background
Knowing the profitability of specific farming systems and rotations is vital for agricultural sustainability and the financial viability of on-farm decisions. Crop sequencing and management decisions directly impact the overall profitability of a farming enterprise. Evaluating the return on investment associated with different systems and rotations can enable farmers to optimise resource allocation and make information-driven choices that contribute to long-term agricultural resilience.
The trial is part of a network of nine trials being conducted across Victoria and South Australia as part of the GRDC-University of Adelaide ‘Farming Systems South’ project (full title: ‘Enterprise choice and sequence strategies that drive sustainable and profitable southern Australian farming systems’). The project is motivated by the perceived ‘gap’ that remains in profitability and efficiency (e.g. gross margin per mm rainfall) despite good single crop agronomy. The project aims to better understand the drivers of profitability and sustainability in farming systems in the southern region, and better realise water-limited potential. In 2023 BCG established three farming systems trials as part of a project. These three trials focus on systems incorporating a variety of different crop sequences and crop intensities. The objective of each trial is to assess how each system, designed to be representative of its region, performs for key metrics such as yield, return on investment and longer-term sustainability. The trials also include a small number of systems focused on the exploration of yet to emerge strategies, such as intercropping, as well as responsive systems that allow for shifting dynamics to respond to seasonal opportunities. These trials will end in 2026.
Paddock Details
Trial Details
Crop type/s: Refer to Table 3
Treatments: Various nitrogen strategies, refer to Table 3
Seeding equipment: Knife points, press wheels, 30cm row spacing
Replicates: Three
Sowing date: Refer to Table 1
Harvest date: Refer to Table 2
Three nitrogen rates were chosen: standard district practice (SDP) which is a rate chosen to be representative of average nitrogen rates in the region, decile5 (D5) based on rainfall and moisture potential using Yield Prophet®, and the decile 9 (D9) rate.
Trial Inputs
Weed, disease, and pest controls were carried out using a “farmer best practice” approach as a guide. This strategy entails taking necessary action in response to observations of damage, as well as pre-emptive action based on weather conditions, without including excess passes outside what would be economically reasonable.
Method
Three trials were established across the Wimmera and Mallee regions. Two of the trials are large ‘core’ trials based at Kinnabulla and Manangatang; these trials contain a wide variety of farming systems. The remaining ‘satellite’ trial is based in Wallup and contains a truncated number of farming systems.
The systems for each trial are outlined in Table 4, Table 5 and Table 6. Four different strategies are targeted across the various systems, i) Baseline systems which are characteristic of the region, for example System 1 across all three sites, ii) Alternative systems which are similar to the baseline but contain more variability, for example, higher or lower risk associated with crop intensity, such as Systems 7 and 8 across both core sites iii) New systems that explore new frontiers, for example Systems 14 and 15 at the two core sites and System 4 at the satellite site, and iv) Responsive systems which are flexible year-to-year and illustrate different attitudes to risk (Systems 16–18 Kinnabulla, 16–17 Manangatang, and 5–6 Wallup).
Trials are arranged in randomised complete block design, and each treatment contains three replicates. Each system contains up to four crop options to represent a specific crop sequence, however in these trial designs each phase of the rotation is included every year so at any given point in the trial, every stage of the ‘rotation’ is evaluated; this design is described as ‘fully phased’. For example, in System 1 at Kinnabulla, the theoretical rotation follows a lentil-wheat-wheat sequence, however every crop in the sequence is sown and studied year-to-year to observe key legacy effects on subsequent crops (Table 7).
Crops sown each year as part of System 1 at Kinnabulla. The crop sequence is L-W-W-L and every phase of the sequence is sown in Year 1. In the following year for each of the three phases, the subsequent crop in the sequence will be sown.
Assessments
Data being collected/analysed include: productivity (yield, grain quality, biomass) each season, annual soil water and nitrogen, annual soil-borne disease risk (PREDICTA B), annual weed counts, long-term changes in P, SOC and pH.
All management records are also collected to compute gross margins and other key performance metrics of cropping systems over multiple years.
Results & Interpretation
Preliminary findings are included in this report to illustrate how the same crop sequence system can vary in yield and grain quality across different regions. Comprehensive data analyses will be provided in future BCG Research Compendiums once the trials have moved through the second year, allowing legacy effects of the first year’s crops on the subsequent year’s crop to be analysed. In the meantime, comparative data between sites for two common systems has been included here. These two systems are System 1 and System 2, outlined in Table 8, and reflect commonly sown varieties for all regions as well as sequence choice. Comparing the same system across a spatial scale allows the consideration of how one system responds under different environmental conditions, a key point of interest for this project.
In System 1 (lentil-wheat-wheat), wheat yield and grain protein produced significantly different results across all three sites (Table 9). Nitrogen for all wheat was maintained to a ‘standard district practice’ (SDP) of 98kg/ha urea. At the Wallup site, lentil yield was significantly higher than yields at Kinnabulla and Manangatang (P=0.008), and lentil protein at the Kinnabulla site was significantly lower than the other two sites (P=0.011). Wheat yields at the Manangatang site were significantly lower across both phase 2 and phase 3 (P=0.01, P=0.039), however protein content was significantly higher for wheat in phases 2 and 3 compared to Kinnabulla and Wallup wheat (P=0.008, P=0.024). Differences in yield and protein content are likely due to variable rainfall between all three sites: Manangatang received the lowest over the growing season (144mm), and Kinnabulla received the highest (187mm), closely followed by Wallup (177mm). A similar trend was observed for System 2 (lentil-canola-wheat-wheat) (Table 10). Lentil grain yield was significantly higher at the Wallup site (P=0.003), and wheat yields for Manangatang were significantly lower for both phase 3 and phase 4 (P=0.001, P=0.003). Canola yields were significantly different across all three sites, with Wallup yielding the highest and Manangatang yielding the lowest (P=0.01). Canola oil content was significantly higher at the Wallup site (P<.001), however wheat grain protein for both phases 3 and 4 were significantly lower (P=0.025, P=0.003). Grain yield and partial gross margin (PGM) are intrinsically linked. For System 1, the higher lentil yield at Wallup earned $2661/ha, whereas the yield at Manangatang earned just $899/ha, showing a return on investment (ROI) for growing lentils in the higher rainfall zone as $1762/ha. Despite the higher wheat grain quality achieved at the Manangatang site, it was not enough to compensate for lower yields, earning hundreds of dollars less per hectare compared to the Kinnabulla and Wallup sites. Similar trends are observed across System 2, and, like the lentils, growing canola in the higher rainfall zone of Wallup provided the highest ROI.
Commercial Practice and On Farm Profitability
These preliminary findings illustrate the influence that environmental factors (rainfall, soil type) have on the same crop varieties, and in turn affect the profitability of farming enterprises differentially across regions. Navigating crop sequencing and management decisions involves a balance between agronomic considerations, environmental factors and economic returns. A major challenge for farmers is managing the selection of crop sequence to not only maximise economic return, but also mitigate risks from seasonal variation. The unpredictability of these factors adds an extra layer of complexity to decision-making. Future analyses will provide crucial information relating to how previous crop choice affects harvest yields and grain quality, and consequentially economic return, for various systems across regions, and will assess the compounding impact of seasonal weather variation and other factors on their resilience and sustainability.
Acknowledgements
This research is being led by the University of Adelaide and is funded by GRDC as part of the ‘Enterprise choice and sequence strategies that drive sustainable and profitable southern Australian farming systems’ project (UOA2212-003RTX). Thank you to Dr Matthew Knowling and Dr Rodrigo Coqui da Silva, The University of Adelaide, for providing a technical review of this article.
