Innovations Towards Sustainable Systems in Arable Farming

There’s an increasing need to farm in a way that uses resources efficiently. This will enable us to produce more, nutritionally complete food for the growing, global population and protect the environment [1]. Innovative precision technologies support farmers in growing more food on the same amount of land whilst using fewer resources and having less impact on the environment.

There are two types of innovative technologies that can support decision-making for farmers. The first category includes novel GPS technologies that can simplify farming operations, such as automatic steering and sensors that collect data. Adoption of this category of technology doesn’t require the user to develop new skills or knowledge. However, the second category requires the analysis and interpretation of the large amount of data generated from these innovative technologies and users need to develop new, digital skills to interpret the outputs (for example, the use of variable rate applications). We’ll explore the second category in this course and consider the factors that influence the adoption of precision farming and digital solutions, as well as the support available to enable farmers to use them for maximum benefit.

Precision Farming

Precision farming refers to the application of ‘different technologies and solutions to manage the variability of agricultural production, to improve crop yield and reduce environmental impact’ [2] and uses GNSS (Global Navigation Satellite System) guidance, such as GPS, to apply site specific agricultural measures [3] which can lead to a wide range of environmental benefits.

Graphic to show the importance of satellite communications in precision farming. ©John Deere

The International Society of Precision Agriculture provides a detailed definition that focuses on the contribution of precision agriculture to the sustainability of food production:

“Precision Agriculture is a management strategy that gathers, processes and analyses temporal, spatial and individual data and combines it with other information to support management decisions according to estimated variability for improved resource use efficiency, productivity, quality, profitability and sustainability of agricultural production.”

The following table summarises the types of precision technologies available and briefly describes how they can support farmers.

GNSS (Global Navigation Satellite System) Arable Agriculture applications (adapted from [2])

Digital Solutions

Other data-driven solutions are also becoming available to support sustainable arable production.

• Forecasting and Decision Support Systems; using models for data-driven agronomic decision making
• Field robots and drones; for remote tasks, sensing and data gathering
• Internet of Things (IoT) to connect / link technologies
• Traceability and blockchain technologies
• Artificial intelligence (AI)
• 3D printing

Data-driven Agriculture

Taken together, these innovations allow (and require!) large amounts of data to be gathered and analysed in order to improve decision making by farmers and their advisors. This digital ecosystem also provides a data trail for informing public authorities, regulators and inspectors with the relevant production information.

Digital Farming Framework. Click to expand. (FMS is the Farm Management System, WSN is Wireless Sensor Network) ©D. Paraforos (University of Hohenheim)

How does Precision Farming Compare to Traditional Farming Techniques?

Precision farming offers a more precise way of applying and using inputs such as fertilisers, leading to reductions in use compared to traditional farming techniques while maintaining or increasing outputs [4]. Precise application may mean more precise planting, making more efficient use of the land [5].

We can make comparisons between traditional farming techniques and precision farming in terms of the quantity of resources used and how the land is farmed. So, for example, precision farming may involve more use of technology such as sensors for monitoring crops and more in-depth analysis and interpretation of the data gathered [6]. This could be taken further, with farming becoming more automated, as digital technologies such as the IoT (Internet of Things), AI, and machine learning become more prevalent [7]. Comparative studies have shown precision farming has the ability to reduce (in comparison to more traditional farming techniques) the quantity of inputs used (pesticides, herbicides, fertilisers, fuel) [8,9] yet maintain or increase the quantity and quality of the crops / yields produced [10,8]. You’ll find out more about the various techniques required for precision farming in Week 2, along with an exploration of the financial benefits.

Precision farming can also support the adoption of farming techniques such as low or no-tillage, integrated pest management and using cover crops, all of which can support environmental sustainability [11,12]. You’ll find out more about the social and environmental benefits and risks of precision farming in Week 3.

Precision farming and digital solutions require data acquisition and analysis skills. Is this a potential hurdle for you? Please tell us about the obstacles you face in terms of workforce training.