Digital innovations in livestock farming: A model proposal

Author: Per Frankelius (Linköping University, Sweden) - September 15, 2017

One revolutionary farming innovation was domestication of cattle in ancient times (Zeuner, 1963). Now the term “fourth agricultural revolution” is proposed (Lejon and Frankelius, 2015), referring to sensors, digital technology and robotics (fig. 1). 

Farmers using MyFarm app, a part of the digital revolution. Photo: DeLaval. 

Innovation discussions quite often gravitate around technology, but the farmer should think about usability and value vis-à-vis price. One way to support farmer’s decisions is using a model of farming activities and then analyse technologies in relation to each activity. In crop production the annual cycle is suitable as model platform (Svensson, 2017), but in livestock business, the animal’s life cycle (fig. 2) is more relevant (Hansson, 2017).

The Agricultural-Phases-Innovations-Model (APIM).

This model describes some core phases in dairy farming, each phase connected with activities and problems that can be solved through innovation. Some innovative concept shown as examples.

Some digital technologies are more important in one or some of the activities connected with the phases. Hoofs, for example, should be in the best trim at I, the time of dries off (Hansson 2017). One digital tool here is infrared thermography (Alsaaod and Büscher, 2012), however not yet a commercial and validated product on the market.

Another example is mastitis detection, which is most frequent in phase M, and can be done through digital technologies, such as Herd Navigator (milk analysis) or Agricam (infrared cameras, fig. 3).


Ellinor Eineren at Agricam in action. Photo: Agricam.

To monitor weight development is important not least in phases M and I. Many solutions exist. One related solution under development is the patented “optical balance” by Smart Agritech Solutions. A camera photographs the animal and an algorithm makes a classification.

Still one example is detection and diagnostics of diarrhea, which is important not least in phase N. Commercial available sensors for detection, however, likely do not exist.

There are problems not related to the phases in the model. One is roe deer detection at hay harvest. It is disastrous to get carcasses into ensilage. This can be prevented by means of thermal sensor drones. Methods have been tested successfully, but commercial available solutions are still in the future. Another example is NIR sensors that register the amount of N, P and K about 4000 times per second in natural manure spreading.  The company m-u-t GmbH made this into an innovation in 2015.

The farmer should evaluate new innovative concept in the light of core activities. Not least proofs of concepts are important (Bågenvik, 2017).

(P.S. In November this year (2017) digital innovations in agriculture will be discussed in the Swedish Parliament, thanks to an initiative from Magnus Oscarsson. Similar political discussions also exist in other countries. The 4D4F project therefore has perfect timing. Klick here for a table including some digital innovations for dairy farming.)



  • Alsaaod M. and Büscher W. (2012). Detection of hoof lesions using digital infrared thermography in dairy cows, Journal of Dairy Science, 95(2), 2012, pp. 735-42.
  • Lejon, E. & Frankelius, P. (2015). Sweden Innovation Power – Agritechnica 2015, Jönköping and Linköping: Elmia and Grönovation at Linköpings University.
  • Zeuner, F.E. (1963). A history of domesticated animals. London: Hutchinson & Co.

Personal sources

  • Cecilia Bågenvik, Program Manager Technical Innovation, Business Area Milking Systems, DeLaval (8 August 2017).
  • Annica Hansson, Advisor, Växa Sverige (16 August 2017).
  • Christer Svensson, practitioner and agri expert (14 August 2017)
  • Ellinor Eineren, CEO, Agricam (18 August 2017)