Lucerne-based pasture for the central wheatbelt region of Western Australia – whole-farm economics Felicity Flugge1,Amir Abadi1,2 and Perry Dolling1,2 1: CRC for Plant-based Management of Dryland Salinity 2: Department of Agriculture, Western Australia

Abstract

Lucerne is a perennial pasture species that has the potential to aid salinity mitigation because of its higher water use relative to annual pastures and crops. However its wide-scale adoption will depend on its profitability when compared with current land uses. In addition to profitability, a grower must also consider the management and cash flow consequences of making the transition from the current land use to one with lucerne. This analysis evaluates the economics of lucerne-based pasture for a typical central wheatbelt farm in Western Australia. Using a whole-farm model, the analysis found that including lucerne-based pasture increased farm profit by 3%. However, including lucerne-based pasture and allowing the option of running merino prime lambs and cross-bred lambs increased farm profit by 23%. Management changes, such as a change of rotations and a change in livestock structure, were necessary in order to realise the gains in profit. Furthermore, results indicated that as the new system of lucerne-based pasture and prime lambs was adopted, there was an initial reduction in cash flow before it increased to above the original level.

Lucerne is a perennial pasture species that is adapted to a wide range of environments in the Mediterranean climatic zone of southern Australia (1) and has potential to increase water-use relative to annual pastures (2,3). However, adoption of any perennial plant at the scale required for dryland salinity prevention will largely depend on the economic viability of the option (4,5). Two economic analyses of lucerne for the South Coast region of Western Australia (4,6) have shown that lucerne can be a profitable option without considering salinity benefits. While these findings are positive, both studies concluded that the optimal area of lucerne (as found by the whole-farm model) is insufficient to address large-scale salinity problems.

The paper presents results from a whole-farm economic analysis of adopting lucerne as a pasture species in the central wheatbelt of Western Australia. The whole-farm economics are explored from two angles. Firstly, the factors that influence and enhance the inclusion of lucerne in the optimal farm plan, as well as the necessary changes to farm management practices and enterprise structures are examined. Secondly the analysis explores the transition costs of moving from one farm structure to a new, more profitable farm structure.

Modelling

This analysis used two models. Firstly the central wheatbelt version of MIDAS (Model of an Integrated Dryland Agricultural System), which is a whole-farm model that jointly emphasizes the biology and economics of the farming system (7). The model’s objective function is profit maximisation, subject to managerial, resource and environmental constraints. For a full description of MIDAS see (8).

The central wheatbelt MIDAS model (CWM) is based on a typical farm in the central wheatbelt region of Western Australia. Farms in this region generally run a mix of crop and livestock enterprises, with up to 70% of the farm area cropped (9). The predominant livestock enterprise in the region is Merino sheep for wool production. Crops grown include wheat, barley, lupins, canola and alternative grain legumes, such as field peas. Annual rainfall is around 350 - 400mm. CWM assumes a farm size of 1800 hectares, made up of 8 land management units (LMU).

The model used for the second stage of this analysis is known as STEP (Simulated Transitional Economic Planning). STEP is a spreadsheet model which assists the user to simulate over time the financial consequences of changing from one enterprise mix to another (10). STEP differs from traditional gross margin approaches in that firstly it represents the whole farm business, and secondly, because it tracks the farms’ activities and finances over the number of years required for transition to the new equilibrium. All data and assumptions regarding the farm must be entered into the model in order to conduct an analysis. In this case, data and assumptions were taken from the CWM model.

The lucerne biomass data was estimated by the Agricultural Production Systems Simulator (APSIM, (11)) based on historical weather data (1957-2002) from Cunderdin. The lucerne biomass includes an annual pasture component during winter and spring, thereby making it a lucerne-based pasture. In this paper lucerne-based pasture is referred to as lucerne. The data was estimated for a soil representing good sandplain (LMU 3). The study involved simulating a repeating rotation of four years of lucerne (sown in the first year and removed in the 5th year) followed by two years of wheat. To simulate a 6 week rotational grazing pattern in APSIM, the lucerne was cut (to simulate a grazing event) on 26 November in the initial year and then every 6.5 weeks after the first cut. The lucerne stem density was 150 stems/m2 throughout the study. The average lucerne biomass production for each 6.5 week period was then used in CW-MIDAS. The biomass of other LMUs was estimated relative the base LMU. Poor sandplain (LMU 1) was 50% of the biomass of good sandplain, average sandplain (LMU 2) 65%, shallow duplex (LMU 4), heavy valley floors (LMU 5) and sandy surfaced valleys (LMU 6) 75% and medium heavy (LMU 7) and deep duplex soil (LMU 8) 100%.

Establishment costs of lucerne were assumed to be $120/ha, including fertiliser, chemicals, cash machinery costs, machinery depreciation and seed costs. Costs of lucerne in subsequent years, for phosphate fertiliser, were assumed to be $20/ha.

The option of running merino prime lambs and crossbred lambs was included in the analysis. Prime and crossbred lambs were assumed to sell for premiums of $12/head and $17/head, respectively, over the same class of unfinished lambs. In this analysis, the time of lambing was assumed to be May and prime and crossbred lambs were sold in December. In this paper, prime and crossbred lambs are referred to jointly as prime lambs. Note that the farm is still predominantly running a wool-producing flock, as only a portion of lambs is sold as prime or crossbred lambs.

The role of lucerne in the optimal farm plan

When lucerne rotations were made available to the model, lucerne was selected as part of the optimal plan at 6% of total farm area (Table 1). This has a small impact on whole-farm profit, increasing it by 3%. The main economic benefit from lucerne, in this case, was that it decreased supplementary feed requirements by 5kg/DSE, through the provision of some summer and autumn feed. Including the option of prime lambs (without lucerne) had a larger impact on profit, increasing it by 12% (Table 1).

Adopting both lucerne and prime lambs together had a multiplying effect with a larger gain in profit ($26,300 per year, or 23%) than adding the two options together (Table 1). Selling prime lambs increased the optimal area of lucerne from 115 ha to 215 ha. Profit increased because the additional feed provided by the lucerne meant that more ewes were carried and more prime lambs were finished per hectare of pasture. Prime lambs are finished during the months of September, October and November. Including lucerne allowed some deferment of the annual pasture from September until November and lucerne also provided feed of higher quality, in terms of increased metabolisable energy and digestibility, during October and November.

With the introduction of lucerne and prime lambs, the proportion of farm in crop decreased by 6% (Table 1). The percentage of farm selected as lucerne was 12%, meaning there was replacement of annual pasture with lucerne. However, this was not a direct replacement of annual pasture with lucerne (Table 2). Lucerne rotations were selected on LMUs 7 and 8 and replaced a three year crop rotation of wheat and field peas/lupin. Consequently, the annual pasture which is selected on part of LMU 2 was replaced by a three year crop rotation of wheat and lupins. Therefore, the optimal way of including lucerne in the farm plan involves a shift, not only on the LMU’s where lucerne is to be grown but on another of the LMUs as well.

Table 2: Rotations selected on three of the Land Management Units (LMU), with and without lucerne included in the model. (LMUs where the rotation does not change are not shown)

PPPP = continuous annual pasture; WWLp = wheat, wheat, lupin; WWF = wheat, wheat, field pea;
LuLuLuWW = lucerne, lucerne, lucerne, wheat, wheat

When adopting a new crop, many farmers in practice may not make this many management changes to their rotations. Instead, they may introduce a lucerne rotation on one or two particular LMUs but will keep the rotations on all other LMUs unchanged. The importance of the rotational changes to the profitability of lucerne was tested by constraining the model in one of two ways. Firstly, lucerne was made available to the model only on LMUs that were previously in annual pasture. Secondly, the model was constrained so that lucerne was only available on the optimal LMUs, i.e. LMU 7 and 8, but no other rotations could be changed.

Table 3 shows the effect of these management constraints on profit. The results indicate that growing lucerne on the optimum LMUs and changing the rotations of other LMUs are both important factors in maximising profit from lucerne. If this level of rotational change is not adopted, then there it a small decrease in profit relative, to the scenario with prime lambs included only.

Table 3: Change in profit from initial farm plan, when management options are constrained

1 Increase in profit from scenario where prime lambs are included as an option but not lucerne.
2 Optimal adoption of lucerne is when prime lambs are included and rotations change as per Table 2

Transition to the optimal farm plan

In practice, changing from the current system to one with lucerne, as well as achieving higher stocking rates and selling more prime lambs, will take a number of years. The STEP model was used to explore the transition from the optimum solution without lucerne to the optimum solution with lucerne. This transition was spread over 5 years. Figure 1 shows the annual cash flow over a fifteen-year period of farming systems with and without lucerne and prime lambs together.

Figure 1: Net cash flow, of the farming system with and without lucerne.

Figure 1 shows that the farm business experiences two years of lower cash flow before the financial benefits of adopting lucerne are realised. The two years of lower cash flow are primarily caused by the farm retaining more lambs and ewes in order to reach the higher stocking rate that is possible with the lucerne system. Livestock receipts initially decrease because of less livestock sales, while livestock costs (including pasture establishment) increase during the same period. This results in the net cash surplus of the livestock enterprise decreasing from the initial year for the following two years, before it increases to above the initial level in the fourth year.

Despite the lower initial cash flow, the net present value of the lucerne and prime lamb system is higher - $2.09 million compared with $1.96 million if the system was left unchanged. Over 15 years the farmer is approximately $130,000 better off from changing to the new system. However, if the time horizon was only ten years (as may be the case for many farmers) the difference in NPV between the two systems is reduced to $74,000.

While this analysis shows cash flow as initially decreasing, profit also decreased during the same period, although to a lesser extent. Profit includes non cash costs such as depreciation plus changes in asset value, or capital (12). As mentioned above, the size of the sheep flock increased over the first five years to reach the new optimum flock size. This means that the farm asset value was increasing through an increase in stock value. However the increase in asset value did not fully compensate for the decrease in cash flow and profit decreased for the first two years.

Concluding comments

This analysis has shown that whole-farm management changes will drive the profitability of lucerne. In particular, it has identified two whole-farm adjustments that will influence the profitability of lucerne: namely a change in livestock management and a change in the pasture/crop rotations. As demonstrated in this paper, if these whole-farm changes are not made, then the full increase in profit from including lucerne will be not realised and in some cases, may not be worth the time and cost of adopting this innovation.

This analysis has also shown that the transition to a new optimal farming system will incur an initial reduction in cash flow. In this paper, cash flow decreased below the initial level for two years before benefits were realised.

Therefore, there are a number of factors that a farmer wishing to adopt lucerne must consider, including both whole-farm changes and adoption strategies. In reality, this may dissuade farmers from adopting lucerne even though there are potential gains to be made. Improved sheep and wool prices and increasing salinity problems mean that further research and extension of lucerne as a pasture option is warranted. However, this analysis has shown that future research and extension of lucerne will need to include consideration of whole-farm management practices.

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