Robot dog advises farmers on healthy soil

Soil health is something which is often overlooked by most people. If you want something to grow, the usual thought pattern is: plant things in soil, water the soil, the things grow. However, this process takes the vital and non-renewable resource that is soil for granted, and it is an intrinsic component of agriculture and environmental sustainability.

Why does soil health matter?

When we talk about soil health we are referring to the soil's ability to function as a living ecosystem, supporting plants, animals, and humans. If soil is healthy, then it sustains crop growth, stores carbon, filters water, and promotes biodiversity, however, keeping this balance is a challenge, particularly in modern agriculture where practices, such as tiling, intensive cultivation, overgrazing, and deforestation can degrade soil quality making it harder to support sustainable agriculture.

Traditional soil testing methods involve labour-intensive practices like collecting samples with tools such as trowels, followed by laboratory analysis, which can take weeks or months to deliver results and it is an expensive endeavour. The limitations that this process causes make it difficult for farmers to get a quick and comprehensive understanding of their land. This can lead to overuse of artificial fertilisers and additives which are harmful to the environment.

The robot

The University of Plymouth has been researching sustainable farming and soil health for more than a decade, and it is collaborating with Robotriks on a pilot project using a robot dog equipped with advanced gamma-ray detection technology.

The device, which is capable of navigating challenging terrain such as hills and hedgerows, scans the soil for naturally occurring radiation levels to assess its health.

Developed by Jake Shaw-Sutton, a University of Plymouth alumnus and co-director of Robotriks, the robot dog combines speed and versatility. It can move at up to 5m per second, weighs only 15kg, and excels at reaching areas that would typically be inaccessible to farmers or traditional machinery.

Faster, smarter soil analysis

Unlike current methods that require manual sampling and laboratory processing, this technology delivers fast, field-wide data on-the-spot. The robot dog generates detailed maps of soil properties relevant to farming decisions, these are things such as nutrient levels and composition, and this allows for a more nuanced understanding of soil health, which enables farmers to optimise their land management strategies.

Importantly, the data generated doesn’t stop at diagnosis. Farmers can use the insights to manage their land more effectively, adapting planting schedules, irrigation systems, and nutrient applications to specific areas. This level of precision farming saves resources, reduces environmental harm, and ultimately boosts profitability.

Sustainability and future farming

The trial is part the University of Plymouth’s wider work in soil health and sustainable agriculture, such as the Healthy Soil, Healthy Food, Healthy People (H3) project and the development of artificial soils through the FABSOIL initiative. These programmes are designed to improve soil resilience and sustainability, ensuring that farming practices are not only productive but also ecologically responsible.

Robot dogs like the one being tested in Cornwall show how technology can transform agriculture by enabling more informed and sustainable land management decisions. They not only address fundamental challenges faced by farmers such as soil degradation and the overuse of chemicals, but if soil health can be understood on the spot, rather than weeks or months later, it helps farmers adapt to changes in soil conditions and better understand the factors affecting their land – data is key.

This isn’t the only initiative to help farmers determine soil health, PES Technologies also knows the universal value of helping farmers maintain healthy yields, and they have produced a portable sensor device that allows farmers to analyse soil health on the spot at a fraction of the cost of traditional methods and with a much faster analysis time.