Training in agricultural technologies: a new prerequisite for smart farming
| Autor: | Simon Ritz, Rizzo, Davide D., Fatma Fourati-Jamoussi, Jérôme Dantan, Anne Combaud, Dubois, Michel J. F. |
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| Přispěvatelé: | UniLaSalle, Innovation, Territoire, Agriculture et Agro-industrie, Connaissance et Technologie (INTERACT), Rizzo, Davide |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | 3rd Rendez-Vous Techniques AXEMA 3rd Rendez-Vous Techniques AXEMA, Feb 2019, Villepinte, France HAL |
| Popis: | Most of the technological innovations in agriculture enter the farm through agricultural equipment. Expressed commitments of the equipment manufacturers are to ease farmers’ decision-making processes with the support of agricultural technologies. Informed decision-making is required to overcome current agricultural challenges: optimizing yields while minimizing inputs, diversifying the crop rotations, protecting the environment, considering the possibilities of plant breeding, lessening work drudgery, and becoming autonomous in energy. The ultimate goal is to adjust the cropping to the nearest needs of each crop, in each specific environment with a fair workload for the farmer and social acceptance. New technologies aim to contribute to achieving this goal. The emergence and multiplication of sensors and processors are common even on the simplest equipment. Data are feeding precision agriculture. However, “data deluge” is radically changing the human-machine interactions in multiple sectors. In agriculture, the increasing data availability and the associated digitalization of decision-making is opening new opportunities (and challenges) for all the actors, from the machines producers to the farmers, for better use of natural resources to reduce farming trade-offs, thus meeting the society's expectations for sustainable development. All actors in connection with agricultural equipment are therefore required to expand their knowledge so as to master digital machine control, embedded sensors and processors, robotics, IoT, and big data management. From the farm’s perspective, this demands well equipped and trained farmers, strongly involved in the development of the processed information relevant for their decision making. These challenges require farmers to expand their knowledge to be able to master these innovations, from field manager to data manager. Farmers’ level of education and information becomes crucial. Training and learning centres with adapted training courses and equipment are necessary. On the other hand, from the manufacturers’ perspective, the multiplication of technological solutions generates a complexification of the communication between equipment manufacturers and farmers. Recent innovations proposed on the market, although technically viable, did not raise expected interest in the farming community. Further exploration revealed that little to no agronomic added value of the innovation was perceived by the farmers. A need for reconnection between technological solutions and their use on the farm is arising. Altogether, this new data-intensive farming requires a positive, inventive and integrated vision for the appropriate use of all technical and scientific means. Eventually, this vision of tomorrow’s agriculture will allow for the emergence of digitally augmented farmers. Such an approach is already being explored by some machinery manufacturers. For instance, AGCO adopted the use of augmented reality devices to expand the operators’ skills across the different stages of machinery construction and maintenance. This is the moment to undertake a technical revolution and to promote collaboration between farmers, engineering schools, students and experts in agronomy, ICT, and research, with a culture of innovation and entrepreneurship. Vocational training and professional development is key aspect of this revolution. How to help today and tomorrow’s farmers and agricultural equipment manufacturers to realize their new technical and digital transition? This paper will discuss some roadmaps/guidelines and available tools in France. |
| Databáze: | OpenAIRE |
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