Machinery costs, a significant part of any farm business, can be dramatically mitigated if machinery is matched not just to farm size but to the farming system.

Research led by CSIRO farming systems scientist Dr Lindsay Bell shows that matching farm machinery to the cropping enterprise is critical for efficient and profitable farming. However, it is often overlooked when comparing and evaluating farming systems.

“High-intensity farming systems clearly have a higher demand for machinery, compared to lower-intensity systems. That means it is important that land size is not the only consideration when making machinery decisions,” Dr Bell says.

“Machinery costs are not insignificant and optimising those costs can be more important than first thought.”

As an example, he says a cropping sequence that includes a mix of summer and winter crops could cost between $30 to $50 less a hectare than a sequence dominated by winter crops.

This is because the mix of summer and winter crops creates less pressure on machinery at critical times. “Essentially, the load is spread through the year so a larger area can be serviced by farm machinery more often. This also factors in contracting costs.”

In contrast, predominantly winter cropping systems have frequent overlaps in machinery demands at sowing and harvesting. “This limits the area that could be serviced by a single set of machinery.”

Farm efficiency

The research forms part of a broader GRDC-supported, CSIRO-led project called ‘Optimising whole-farm water use efficiency and risk using whole-farm bioeconomics’.

The project, which finished recently, aimed to better understand how whole-farm factors affect farming system adoption. That is, how equity, debt, labour, social factors and machinery affect the implementation of systems that maximise productivity.

CSIRO farming systems scientist Dr Lindsay Bell. Photo: Nicole Baxter

The research examined whole-farm modelling tools to address multiple farm-level attributes and analysed the labour and machinery demands required to implement cropping systems that varied in their intensity and diversity across New South Wales and southern Queensland.

In what is believed to be a first, the project considered how farming systems interact efficiently or otherwise with machinery. Calculations were made for sowing, spraying and harvesting for six different farming systems that varied in crop mix and intensity. Calculations also included the area required to be serviced for each on-farm operation, plus the balance of daily machinery demand and supply for each operation.

Dr Bell says that when insufficient machinery capacity was available, the researchers assumed contractors would be used. “Contracting costs were $60 per hectare for harvesting and sowing and $15/ha for spraying, based on average prices quoted in the region at the time.”

The costs of owning and operating machinery, including depreciation, interest, maintenance, fuel, insurance and contracting costs, were also included in the calculations.

The analysis tested combinations of differing machinery sizes and associated costs across three contrasting environments ranging from higher rainfall (at Dalby), moderate rainfall (Goondiwindi) and lower rainfall (Mungindi).

Results

To explain the work, Dr Bell shares the farming systems interactions for a moderate-rainfall location with a medium-sized machinery complement – a 12-metre planter with tractor, a 9m harvester and a 24m boomspray (Table 1).

Table 1: Crop rotations and impacts for different farm sizes in the moderate-rainfall zone.

x = six-month fallow, xx = 12-month fallow, xxx = 18-month fallow
W = wheat, Ch = chickpeas, Mg = mungbeans, S = sorghum, Fb = faba beans

“There was up to a $60/ha difference in machinery costs calculated between systems. It shows that while the higher-intensity systems can have a higher potential to generate income than the lower-intensity systems, they involve a much higher machinery cost, both in fixed and operational costs,” Dr Bell says.

“This is food for thought when comparing farming systems and their impact on whole-farm profitability. The analysis shows that the cost of machinery required to operate a farming system can vary significantly and such costs should be considered to fully evaluate a cropping system’s profitability.”

Future

Dr Bell is keen to find out whether there is a demand for more generic tools or information that could help improve on-farm machinery decisions and match these to farming systems.

In the meantime, for those keen to examine how their farming system adds up, Dr Bell suggests as a first step considering machinery costs per hectare relative to contracting costs.

“When this disparity is large – that is, the contracting cost is high compared to owning machinery – then a system that optimises owned machinery is going to be very important. This may mean considering a crop sequence that spreads machinery load over time so that machinery costs per hectare are as low as possible.”

Although this work was done for the northern region, it demonstrates useful approaches that could be used or are applicable elsewhere.

Farming system adoption

Perhaps what the project has also importantly demonstrated is that whole-farm-related issues, such as labour, machinery and capital requirements, are rarely considered in many research activities. Yet these are clearly important drivers for farm-level adoption.

“This project has used some very simple analysis to examine these issues, but more-sophisticated analytical tools and approaches are available that are likely to produce further insights if applied in future research,” Dr Bell says.

“Partnerships with farm advisers offering benchmarking services or the financial sector is likely to be a fruitful way of targeting such research to critical issues and maximising its impact into the future.”

More information: Lindsay Bell, 0409 881 988, lindsay.bell@csiro.au