Crop robotics are coming soon to a farm near you. Retrofit kits to convert conventional equipment for autonomous use are already being marketed in several countries. In the next few years several UK start-up companies have plans to commercialise robots designed for farm use. Those robots have the potential to change the management of rural land in the UK.
With tractors, combine harvesters and other conventional mechanisation, the economic rule of thumb is that bigger is better – but when human operators are removed from the equation the need for ever-larger equipment almost disappears. On the farm of the future, crop operations are likely to be accomplished by a swarm of smaller machines on small irregularly shaped fields, with woods, wetlands and other non-arable areas being farmed by robots almost as efficiently as large, flat, rectangular fields.
This large-scale shift to autonomous crop equipment is poised to occur in the next five to ten years. Most major farm equipment companies have autonomous equipment research and development programmes, and there are some 45 start-up companies around the world focusing on robotic farm technology. A kit to convert conventional equipment to autonomous use is already being marketed in the USA. The transition to crop robotics will create demand from landowners, farm tenants and farming enterprises for advice on how best to adapt their businesses; for example, tenancy agreements will need to be modified to reflect changing costs and production potential.
The Hands-Free Hectare (HFH) project at Harper Adams University has shown that it is technically possible to produce arable crops in the UK with autonomous machines.
Researchers are using HFH to provide a glimpse of the implications of crop robotics for farm management, including the following:
Those changes affect comparative advantage and trade: for the past century, countries with large, flat rectangular fields such as Argentina, Australia, Brazil, Canada and the USA that can be farmed efficiently with conventional equipment have had a comparative advantage in grains and oilseeds. In the future, this advantage may pass to countries with good soil and reliable rainfall that are close to consumer markets, and where production practices fit consumer preferences in spite of their fragmented landscape, such as the UK.
HFH uses conventional small- and medium-scale farm equipment retrofitted for autonomous operation. Starting with a flat, square, 1ha field on Harper Adams University farm in 2017, two years later it was scaled up to a 35ha hands-free farm that will test the equipment under typical UK agricultural conditions. Until HFH, little public data has been collected on the farm management implication of crop robotics. Although several agribusinesses are developing autonomous equipment, their data is proprietary, while many universities and research institutes worldwide with prototype crop robots have little experience producing crops at a commercial scale.
In contrast, the costs and returns from an HFH-type farming system are relatively easy to estimate. Because HFH uses retrofitted conventional farm equipment, the cost, reliability, repair expense, useful life and other machine characteristics are well known. HFH documented retrofit costs based on commercial global navigation satellite systems (GNSS) guidance and modified open-source drone software. The input requirements, field operations and yields for the commercial crops produced are also well documented.
Some key assumptions in this analysis include:
As the hands-free farm expands and provides new information, the research team plans to refine this analysis to examine the impact of field size, shape and topography, extend the analysis to assess a broader range of farm sizes and crops, and consider the impact of automation for larger-scale equipment.
James Lowenberg-DeBoer is professor and the Elizabeth Creak chair of agri-tech applied economics and Simon Keeble is chartered surveyor and senior lecturer at Harper Adams University
Related competencies include: Agriculture, Big data, GIS (geographical information services)