INTRODUCTION General Agriculture has always been a driver of innovation of new technologies and developments, especially in Germany. Johnson describes a direct link between the mechanization of agriculture and the prosperity of a country 1 . This is par- ticularly evident in the number of people working in the agricultural sector. In Germany, the number of people employed in agriculture fell from 22.5% in 1950 to 1.5% today. Despite all this, more food is currently being produced in Germany than ever before 2 . The average yield per hectare of a wheat field has quadrupled since 1900 from 1.85 tonnes to 7.64 tonnes in 2017 3 . The mechanization and automation of production processes had a particular influence on the advancement in agriculture 4 [4]. According to the German Federal Statistical Office, 6.4 billion euros were spent on new and highly-auto- mated agricultural machinery in 2017 [2]. This high sum underlines the willing- ness of the agricultural industry in Germany to invest in new innovative tech- nology. The requirements with regard to agricultural machinery have changed over time. Some features of earlier agricultural machines are no longer in demand today, while new skills are required. Typical changes over the years included absolute machine size, engine power, comfort, safety and modern automatic steering and driver assistance systems 5 . Digitization does not stop at agricultural engineering and will continue fur- ther in the future. “Deep Learning” and “Internet of Things” (IoT) have been around for a long time in agricultural research and are now being used in the first commercial products. Some examples of this in practice are smart phone apps for determining plant diseases and weeds 6 . Automated robotics solutions can now also be purchased and offer added value for the user (e.g. hoeing weeds in row crops). Robots in the field offer the opportunity to ex- tend digitization down to individual plants. Therefore, on the level of a “digital twin”, the development of the plants can be examined even more closely 7 . 1 Δ G. Johnson, “Agriculture and the Wealth of Nations” in Papers and Proceedings of the Hundred and Fourth Annal Meeting of the American Economic Association, 1997, vol. 87, no. 2, pp. 1–12. 2 Statista, “Landwirtschaft in Deutschland”, 2019. [Online]. Available: https://de.statista.com/statistik/studie/id/6455/ dokument/landwirtschaft-statista-dossier/. [Accessed: 04-Sep-2019] 3 P Pascher, U. Hemmerling and S. Naß, Situationsbericht 2018/19 „Trends und Fakten zur Landwirtschaft“. Deutscher Bauernverband e.V., 2018 4 M Kassler, “Agricultural Automation in the new Millennium” Comput. Electron. Agric., vol. 30, no. 1–3, pp. 237–240, Feb. 2001 5 J. N. Wilson, “Guidance of agricultural vehicles - a historical perspective” Comput. Electron. Agric., vol. 25, no. 1-2, pp. 3–9, Jan. 2000. 6 A Kamilaris and F. X. Prenafeta-boldú, “Deep learning in agriculture: A survey” Comput. Electron. Agric., vol. 147, no. February, pp. 70–90, 2018. 7 A Linz, J. Hertzberg and J. Roters, “„ Digitale Zwillinge “ als Werkzeug für die Entwicklung von Feldrobotern in land- wirtschaftlichen Prozessen Material und Methoden” in Lecture Notes in Informatics (LNI), Gesellschaft für Informatik, Bonn, 2019, pp. 125-130. 4
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