29 November 2022

World Soil Day: High Tech In Farming

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One of the oldest areas in which technology has made its impact on human civilisation is farming. The development of agricultural techniques in the Neolithic period allowed humans to transition...
UK Environment
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One of the oldest areas in which technology has made its impact on human civilisation is farming. The development of agricultural techniques in the Neolithic period allowed humans to transition from nomadic, hunter-gatherer lifestyles to living in permanent settlements. The agricultural revolution in Britain through the 17th to 19th centuries led to a huge increase in productivity that freed up labour for the Industrial Revolution. New developments in agriculture will continue to be crucial in future as farming adapts to new challenges such as climate change. DEFRA (the UK's Department for Environment, Food and Rural Affairs) recently announced £11 million in funding to support pilot projects under their Farming Innovation Programme. On World Soil Day, we consider some of these projects and how developments in technology may continue to affect farming practices in the future.


The use of artificial fertilisers has greatly increased crop yields over the last hundred years. Nitrogen in particular can be fixed from the atmosphere to produce fertiliser products such as ammonia and ammonium nitrate, and this is commonly achieved using the Haber process. This is a chemical process invented in the early 20th century that fixes atmospheric nitrogen using catalysts, high temperatures, and high pressures. While effective, the Haber process is energy-intensive and uses large amounts of natural gas as a raw material. Some estimates suggest the Haber process alone may account for up to 1% of total CO2 emissions worldwide. Reducing the carbon footprint of agriculture will be important to combat climate change. One way to do so would be to find other ways of producing artificial fertilisers that are less energy intensive and do not rely on fossil fuels.

Two of DEFRA's pilot projects will investigate new processes for low-carbon fertiliser production. The first aims to use organic material in combination with carbon dioxide captured from industrial power generation to produce fertiliser with a reduced carbon footprint. The other aims to produce fertiliser using waste materials from the bio-energy, waste management, and agriculture sectors. Using waste materials and captured carbon dioxide to produce fertiliser would have a doubly-beneficial effect of reducing the environmental impact of both fertiliser production and the processes from which the waste materials are captured.

AI and Automation

The use of chemicals such as fertilisers and herbicides in agriculture can have a negative impact not just through their manufacture. Indiscriminate spraying of large areas can lead to runoff of these chemicals into watercourses. This in turn can harm wildlife and plants around and downstream from the farmed area.

One way to combat this may be through increased use of automation and AI. Another project funded by DEFRA looks to investigate the use of machine learning to automatically monitor crop fields and detect areas where weeds are prevalent. These areas can then be selectively sprayed with herbicides appropriate to the weed species that are detected. This may avoid the need for indiscriminate spraying of large areas with multiple or wide-spectrum herbicides, thereby reducing the impact on surrounding areas.

Automation may also help to improve productivity in a time where the agricultural sector is facing labour shortages. Machine harvesting of crops such as wheat has been performed for a long time. However, machines often struggle to be effective when harvesting crops like fruit that are easily damaged or more difficult to spot among surrounding foliage. Consequently much fruit harvesting in the UK is still done by hand by seasonal workers. Recent advances in robotics and machine learning are beginning to make machine harvesters effective with a wider range of crops. DEFRA has allocated funding for pilot projects investigating the automated harvesting of delicate crops such as lettuce, broccoli, and courgettes.

AI is also increasing being used to assist in livestock farming. Machine learning algorithms can detect the condition of animals to monitor their welfare based on pictures or video feeds of the animals. This could include monitoring weight changes to assess growth, which can be used to accurately determine whether animals are receiving the correct amount of feed and other nutrients. Video monitoring can also monitor for sickness or disease. Early detection of injuries such as lameness or signs of stress such as abnormal eating or drinking can improve animal welfare. It can also reduce costs for farmers by allowing early intervention that reduces the complexity and difficulty of treating any resulting medical problems.

Breeding and Natural Processes

While examples such as those above are typically what we imagine when thinking of technology in agriculture, more traditional techniques continue to play an important role. Others of the projects funded by DEFRA aim to breed sheep for increased resilience against parasites and to identify previously unknown bacterial species that could act as natural fungicides against potato blight.

This is an interesting reminder that, while "high tech" methods such as robots and AI will play an important role in future agriculture, there is still a wealth of information to be gained from improving our understanding of the natural world as well. Innovation of all kinds in this sector will continue to play an important role in feeding the Earth's growing population as the climate changes in the coming decades.

The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.

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