Every year, more than 4,000 grain growers in Western Australia harvest their crops in early summer. They aim to harvest crops at maturity as quickly as possible, and transport and store it before its quality can degrade. The vast majority of crops are transported from the field to port via a bulk storage and handling network, but this system can become congested, slow and expensive during the harvesting period. Farmers can also elect to store grain on-farm for later distribution, but the cost of grain storage silos is a significant factor. Changes in the bulk grain handling network operation, cheaper on-farm storage options, larger trucks, higher-yielding crops and new harvest technologies can separately and in combination completely alter the nature of a farmer’s grain harvest logistics. Planning a harvest is becoming an increasingly difficult series of interrelated harvesting, transport and storage choices that can have a significant impact on farm profits.
A rigorous mathematical model was developed to connect the related harvest, transport and storage options available for multiple grain crops. Over 60 inputs could be set to match a specific farm’s operations, from the number of hectares under each different crop to the amount and cost of storage available, the number of harvesters and trucks, harvesting rates, truck capacity and speed, distances to transport network receival sites with their opening times and requirements, right through to current market prices for different crop qualities. Other variables could then be adjusted to consider crop moisture limits, blending ratios, yield and quality downgrades to any unharvested crop overtime, transportation costs and the percentage of harvest split between different distribution pathways and markets.
The mathematical algorithm was programmed into a robust decision-making software tool for farmers. Farmers can input a range of variables about their crops, farming equipment, supply chain options, weather and market forecasts, and the model can calculate the expected costs and profits. Different harvest, transport and storage scenarios can be tested, to compare the different harvesting strategies and quantify their relative benefits.
Applying the model to a typical Western Australian grain farm shows that many newer options for harvest logistics unambiguously advantage the farm business, and often, a combination of these changes can increase a farmer’s harvest profits by over 10 per cent. Through ‘what if’ scenario testing, the financial viability of using on-farm storage options can be realistically assessed, in turn opening up further commercial opportunities, such as the direct selling of premium and niche grain blends to the customer.
- Luke Gamble, Managing Director, Global Grain Handling Solutions
The decision support tool is simplifying the highly complex economics of grain harvesting and distribution, letting farmers efficiently manage their harvest logistics to maximise their crop portfolios, market opportunities and profits.
The optimisation model can be used for one-off scenario testing, to inform strategic decisions about investing in on-farm grain storage, an additional harvester, a larger truck or a different crop mix for example, where the cost–benefit choice may be clear across both good and bad growing seasons.
Equally, once the boundary conditions of crop mix, available equipment, storage and transport options have been decided for a season, the model can also be used to plan a specific harvest. When the farmer has a good understanding of the likely crop yields, the possibility and timing of bad weather events during the harvesting period, and the immediate storage and transport options available, the model can be used to optimally time the stages of the harvest across the farm to preserve the highest grain yields and qualities possible.
