Phases of novel annual pasture legumes are a profitable and low risk option in low-medium rainfall regions

Key messages

• Rotation sequences that included annual legume-based pastures were more profitable and had reduced risk, compared with continuous cropping rotations.
• Successful legume pasture establishment and high pasture utilisation were required to achieve high profitability from pasture phases.
• Including improved grazed legume pastures in rotations resulted in an increase in farm profit of about $100/ha, compared with other break options.
• To investigate the economic value and risk implications of productive annual legume-based pasture phases on mixed farms.

Aim

• To investigate the economic value and risk implications of productive annual legume-based pasture phases on mixed farms.

Introduction

Annual legume pasture phases have historically been an integral part of mixed farming in southern Australia. However, the level of integration of these phases in modern farming businesses is limited, and novel approaches are required so that legume-based pastures remain economically competitive with continuous cropping (Hogg and Davis, 2009; Bell and Moore, 2012). Potential benefits of mixed crop and pasture systems are high, and include reduced inputs, increased profit, improved sustainability, and lower risk (Howieson et al 2000; Bell et al 2021). Recently, work undertaken to develop the next generation of annual pasture legumes in farming systems has increased the flexibility and performance of pasture phases (Nutt et al 2021). In this paper we use the Land Use Simulation Optimiser model (LUSO; Lawes and Renton, 2010) calibrated with data from recent field experimentation to evaluate profitability and risk of rotations where systems including novel pasture legume systems were compared with cropping dominant systems.

Method

We investigated the economic performance of crop and pasture rotations using the LUSO bioeconomic model, focusing on break crop effects that may persist across multiple years. Considering crop and pasture phases in whole farm economic analyses requires a complex understanding of the drivers of value and biological effects generated both from cropping and the pasture produced within a livestock enterprise. To gather this information as input data for the LUSO model, simulation modelling of crop and pasture production was conducted at one project location, Corrigin, Western Australia (Met. station 10536, BOM data drill), across 30 years (1991–2020) to ensure that inter and intra-seasonal variability was considered.

Crop simulations

The APSIM model (Holzworth et al 2014) was used to simulate crop production for three winter crops: wheat (W), canola (C) and lupins (L). Simulations of a mid-development cultivar grown continuously (1991–2020) for wheat, canola and field pea (lupin) crops were run. The wheat, canola and field pea crops were sown on a fixed sowing date of 10-May, 15-April and 15-May respectively. All crops were grown with unlimited N, and APSIM assumes no weeds or diseases.

Pasture simulations

Four pasture management scenarios were evaluated using GrassGro (Moore et al 1997), including a gross margin analysis needed to parameterise grazed pasture scenarios in LUSO. Within the GrassGro scenarios, pastures were grazed as part of a self-replacing Merino enterprise with pasture management alternatives adapted in the GrassGro scenarios as follows:

1. Volunteer pasture (Pv). Unimproved weedy pasture, with low plant density, common in break phases in mixed farming systems.
2. Improved pasture (Pi). Pastures managed to maintain higher annual legume content and plant densities using traditional pasture species (e.g., older variety sub clovers and medics)
3. Novel pasture (Pn). Higher growth and nutritive value species being developed and evaluated in the DLPS project. A new beta plant model Bartolo bladder clover was used in this scenario.
4. Ungrazed novel pasture (Pnug). The same as novel pasture, except that pastures were not grazed.

Key parameters in GrassGro scenarios are shown in Table 1.

The livestock enterprise was set up in GrassGro with the pastures grown in a single 1000ha paddock and set-stocked, except during i) two months when sheep were moved to stubbles in December and January and ii) one month grazing shrub-based pastures in March. The stocking rate for all scenarios and locations was five breeding ewes/ha winter-grazed pasture area, based on preliminary economic optimisation testing. Winter-grazed pasture area refers to the area of the farm that is retained for grazing (not cropped) during the winter/spring growing season.

LUSO simulations

LUSO model simulations were conducted to evaluate the economic return of a particular crop and pasture sequence over six seasons (Lawes and Renton 2010). The model represents how each crop or pasture within a simulated sequence affects disease population dynamics, weed population dynamics and nitrogen. The disease, weed, and nitrogen processes then affect the yield and economic return of subsequent crops. The model predicts the effect of each crop on future yields, profits, and biotic stresses.

LUSO has five main components that require parameterisation. These are estimates of average yield for each crop choice; commodity prices and costs associated with growing each commodity; weed population dynamics and the impact of weeds on each crop; disease population dynamics and the impact of disease on each crop; and the N requirements and quantity of N each crop returns to the soil (i.e., fixed N). Biotic stressors (disease and weeds) were parameterised to i) low (mild) and ii) high (aggressive) settings for continuous cereal rotations, contrasting yield penalties for continuous sequences of wheat. In these scenarios, the high disease and weed settings (or high biotic stress) were calibrated to produce substantive yield penalties, consistent with published break crop effects (e.g., Seymour et al 2012). Penalties increased as the sequence length of continuous cereal cropping increased, according to the algorithm used in LUSO. Base yield values and N requirements for each of the phases are reported in Table 2. Base yields were scaled to annual yield values for each season using the results of 30 years of simulated crops and pasture yields.

Using phases defined in Table 2, eight rotation combinations were used (based on typical wheatbelt systems) to test effects of the type and frequency of different phases on crop and sheep production.  The control scenario was a six-year continuous wheat rotation, with break treatments of canola, lupins, or one of the pasture scenarios included in combinations that might occur in practice. Rotations that included novel pastures either fully grazed or completely ungrazed in the establishment year, were compared with either improved or volunteer pastures for the same phase sequences. Each of the rotations was run 1000 times, using randomly selected annual weather combinations for each of the six phases, to represent all likely six-year seasonal conditions for the crop and pasture rotations.

Assumed costs and prices

Values of costs and prices used in the economic analyses were kept static and based on PIRSA 2021 Farm Gross Margin and Enterprise Planning Guide values (Table 3). Annualised establishment costs were estimated for each of the pasture management scenarios. In addition, a sensitivity analysis was conducted based on current prices for wheat ($400/t), canola ($900/t), and the cost per unit of nitrogen ($3000/t).

Results

Profit

The profitability of rotation sequences (by phase) for both five-year average costs and prices and current prices, averaged across high and low biotic stress scenarios for the 1000 annual weather combinations, is reported in Table 4. Phases of improved and novel pastures that were grazed were found to be more profitable than cropping phases for scenarios based on five-year average costs and prices used. The most profitable rotation including pastures (PnWPnCWW) was $117/ha/year higher than the most profitable crop-only rotation (CWWCWW). The large loss from establishing novel pastures that were not grazed in the first season meant profitability was similar to the rotation with grazed volunteer pastures. Higher profit from productive pastures was maintained in the sensitivity analysis conducted using current (higher) prices for wheat and canola, and current N costs, with $88/ha/year higher profit in the rotation than included grazed novel pastures. The profitability of rotations with unimproved pastures was similar to continuous cropping rotations, except for continuous wheat which was less profitable.

Effects of the level of biotic stress on the profitability of rotations were as expected (Figure 1). Decrease in profit in scenarios with high biotic stress was about half in the most profitable rotation containing pastures, compared with the most profitable continuous cropping scenario. The decrease in profit from biotic stress was highest in the continuous wheat rotation. Effects remained the same for the sensitivity analyses scenarios with current prices and costs applied for wheat, canola and nitrogen fertiliser.

Risk

There were differences between the rotations in conditional value at risk (CVaR) i.e., the least profitable 20% of simulated rotation sequences due to seasonal conditions. Under high biotic stress, and average prices, the most profitable continuous cropping rotation over six years (CWWCWW) was unprofitable in the poorest 20% of season sequences. The profitability of the rotations with novel pasture were more consistent, and higher, than continuous cropping in the least profitable 20% of sequences, except with current prices x low biotic stress where CVaR values were similar (Figure 2).

Conclusions

Our study demonstrated that productive legume-based pastures are a profitable option in mixed farming rotations. These pastures have a dual role in supporting a self-replacing Merino enterprise and by reducing biotic stress and nitrogen input costs for subsequent cropping phases. Further, we identified benefits in reducing CVaR, where rotations that included an annual pasture phase returned higher profit under the least profitable seasonal conditions, compared with cropping-only phases. Where scenarios had low biotic stress and used current (historically high) prices for wheat, canola and nitrogen fertiliser there was no downside risk benefit from annual legume pastures.

These results give a positive picture for annual legume-based pastures in the mixed farming region, although with some qualifications due to assumptions used in the modelling. The study assumed that the establishment of productive high-quality pastures is always successful, producing high quality livestock feed and fixed N during each pasture phase including the establishment year. If pastures are ungrazed in the establishment year, or all years, there is a large reduction in profit. Sheep stocking rates that are economically optimal were used in the study, whereas stocking rates in the mixed farming region are typically conservative. Further, alternative management tactics to reduce biotic stress and maximise profit were not considered, nor were any effects of conserved soil water in the prior season. This research supports the potential for a greater role for novel annual pasture legumes combined with sheep in low-medium rainfall agricultural regions.

References

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Lawes R, Renton M (2010) The Land Use Sequence Optimiser (LUSO): a theoretical framework for analysing crop sequences in response to nitrogen, disease and weed populations. Crop and Pasture Science 61, 835-843.

Nutt BJ, Loi A, Hackney BF, Yates RJ, D’Antuono M, Harrison RJ, Howieson JG (2021) “Summer sowing”: A successful innovation to increase the adoption of key species of annual forage legumes for agriculture in Mediterranean and Temperate environments. Grass and Forage Science 76, 93-104.

Seymour M, Kirkegaard JA, Peoples MB, White PF, French RJ (2012) Break-crop benefits to wheat in Western Australia - insights from over three decades of research. Crop & Pasture Science 63, 1-16.

Acknowledgments

The authors acknowledge The Dryland Legumes Pasture Systems project, which is funded by the Australian Government Department of Agriculture Water and the Environment as part of its Rural R&D for Profit program, the Grains Research and Development Corporation, Meat and Livestock Australia and Australian Wool Innovation (Project No. RnD4Profit-16-03-010).

Paper reviewed by: Rick Llewellyn, CSIRO Agriculture and Food.

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