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Digital Farming

The terms Digital Farming, Smart Farming and Agriculture 4.0 describe the use of digital information and communication technologies in agriculture. The digitalization of agriculture is also called the 'Third Green Revolution'.

Aim and innovation

The digitalization of agriculture aims at a more efficient use of resources for the protection of the environment and animals as well as at an increasing economic profitability.[1] Through a targeted use of digital technologies, farmers can be supported in their operational decisions. More information can be collected and also made available externally.

Digital Farming can be structured around three key areas:

  1. Management of information systems: These are systems for collecting, processing, analyzing, storing and communicating data for further use in subsequent processes. For example, field record software enables farmers to digitally control and manage all farm processes, which can lead to reduced workload.
  2. Precision Farming: This refers to methods that adapt the input for working agricultural land to the different soil conditions within a field. The input includes inter alia fertilizers, seeds, plant protection products and fuel for soil cultivation. This way, negative environmental impacts can be reduced and resources saved[2]. For example, the amount of fertilizer required can be reduced with a combination of satellite-controlled application and soil samples (soil probes).
  3. Agricultural automation and robotics: This involves the application of artificial intelligence at various stages of agricultural production, including robots (e.g. milking robots, farmbots) and drones. Field robotics stands for the use of light, unmanned vehicles for tillage, seeding and weed control with the aim of avoiding soil compaction by heavy vehicles. In pest management, drones have been used for some time now. In corn fields, for example, the drones drop eggs from beneficial insects, which act as an antagonist to vermin and contain their spread.

Examples

BoMill - Sweden[11], System Cameleon from Gothia Redskap - Sweden[12], senseFly - Switzerland[13], Hummingbird - United Kingdom[14]

 

 

Category

intermediate consumption, production

 

Actors and players

producers, technology providers

 

Development and current dynamics

In the US, digital farming tools are already used by an estimated 20-80% of farmers[8]. In Europe, on the other hand, the use is estimated at 0-24%[9]. It is a rapidly growing sector, where new technologies are constantly being developed and mainly applied on large farms. Currently, there is a trend for large corporations to focus on big data, which includes the data collection of soil fertility, plant stress and climate[10].

 

Sustainability potential

The sustainability potential of the various technologies, which are summarized herewith under Digital Farming, differs greatly from one another. The following values should be understood as average figures. Single innovations may differ significantly from these.

 

Ecological

  • soil (indirect)
  • water (indirect)
  • climate (indirect)
  • air (indirect)
  • resource efficiency in production and consumption

Economic

  • increase of food security (indirect)
  • creation of transparency along the value chain

Risks / disadvantages

Prerequisites for the digitization of agricultural processes are an able-bodied rural infrastructure, access to these modern technologies on farms and, in particular, tech-savvy employees on farms. Instead of the frequent patenting of modern technologies, open source solutions can be promoted to ensure the cost-effective access for small farms. In addition, this would promote a faster and more participatory further development of the technologies.

A number of risks and disadvantages are associated with the various digital farming techniques. According to scientists at the Thünen Institute, it is assumed that jobs will tend to be lost over the next ten to fifteen years as a result of the digitalization of agriculture, especially in the area of low-skilled jobs[15]. The application of Digital Farming is mainly economical viable for larger farms by creating high-tech jobs.[16] Michelsen of INKOTA-netzwerk e.V. points out that, among other things, vertical mergers of companies at different process stages driven by digitization can lead to a concentration of power[17]. Mooney, working in the field of international cooperation, also sees dangers for small-scale farming structures when technologies encounter unequal societies[18]. Small farmers in particular could be disadvantaged: "For example, almost half of all agricultural research by the private sector is concentrated on a single crop, maize. As a result, the interest of plant breeding companies in the 7,000 food crops grown by small farmers (in conditions where robots have not yet set foot) is negligible. This could urge governments to further discriminate against this plurality of species, and instead create sufficient markets for more 'commercial' plants"[19]. In addition, small farms are now increasingly threatened by large corporations’ takeovers, as the application of the new technology makes even small fields economically interesting for large corporations. At the same time, the competitiveness of small farms is decreasing, as they cannot keep up with the cost-intensive equipment[20]. In order for new technologies to benefit small farm structures as well, it should be ensured that their needs are taken into account in the development of the technologies, that they are given access to the technologies, for example in the form of open source, and that they possess their data themselves[21].

Defective technologies and algorithms can also have negative effects. If a wrong decision is made due to the technology, entire harvests can be destroyed[22]. Also the risk of confidential internal company data being passed on to third parties cannot be ruled out either.


[1] Bundesministerium für Ernährung und Landwirtschaft (2018): Digitalisierung in der Landwirtschaft. Chancen nutzen - Risiken minimieren. S. 21

[2] Mulla, D. und Khosla, R. (2017): Historical Evolution and Recent Advances in Precision Farming.

[3] Bundesministerium für Ernährung und Landwirtschaft (2018): Digitalisierung in der Landwirtschaft. Chancen nutzen - Risiken minimieren.

[4] Napier, T. L.; Robinson, J. und Tucker, M. (2000): Adoption of precision farming within three Midwest water-sheds.

[5] Mulla, D. und Khosla, R. (2017): Historical Evolution and Recent Advances in Precision Farming, p. 22.

[6] ibid, p. 20.

[7] Larsen, W. E. et al. (1988): Field navigation using the global positioning system (GPS).

[8] Kernecker, M. et al. (2018): D2.4 Peer-reviewed paper. Smart AKIS. Smart Farming Thematic Network. https://www.smart-akis.com/wp-content/uploads/2019/01/Peer-reviewed-paper.pdf

[9] ibid.

[10] Mulla, D. und Khosla, R. (2017): Historical Evolution and Recent Advances in Precision Farming. p. 24.

[11] Bomill (n.d.). https://bomill.com/ (20.02.2020)

[12] Gothia Redskap (2018).  https://www.gothiaredskap.se/c (20.02.2020)

[13] SenseFly (2020): SenseFly—The Professional’s Mapping Drone of Choice. https://www.sensefly.com/ (20.02.2020)

[14]Hummingbird Technologies (2019). https://hummingbirdtech.com/ (20.02.2020)

[15] Bundesministerium für Ernährung und Landwirtschaft (2018): Digitalisierung in der Landwirtschaft. Chancen nutzen - Risiken minimieren. p. 21.

[16] ibid.

[17]ibid.

[18] Mooney, P. & ETC Group. (2018): Blocking the chain. Industrial food chain concentration, Big Data platforms and food sovereignty solutions. INKOTA, ETC Group, Glocon & Rosa-Luxemburg-Stiftung. https://webshop.inkota.de/node/1551

[19] ibid. p. 28.

[20] ibid. p. 31.

[21] Michelsen, L. (2018): INKOTA-Infoblatt Welternährung 17: Digitalisierung. INKOTA-netzwerk e.V. https://webshop.inkota.de/node/1555

[22] ibid. p. 29.