After mechanization, chemistry and biotechnology, agriculture is undergoing yet another revolution with digital agriculture — or agriculture 4.0. However, there is not just one but several digital agricultures: While they share the use of new technologies, they differ in their aims and means. These technologies can help farmers, consultants and researchers develop more resilient agroecosystems, with farms gaining more autonomy (less dependent on external inputs) and becoming more economical (by reducing costs).
Diversity of Digital Farming
Agriculture 4.0 combines a range of implementations to meet different needs.
Smart agriculture mainly uses Internet of things (IOT) technology. Various sensors placed on equipment or in the field provide data to a platform (cloud-based) allowing the creation of an information system for users (agro-supply professionals, farmers, consultants, researchers etc.) [1]. Examples include sensors embedded in machines using artificial intelligence to detect weeds that will be targeted for localised destruction.
Based on the same technology, climate-smart agriculture works towards a more sustainable agriculture, taking into account the challenges of climate change. Campbell, B.-M, et al. identify three main objectives: “increasing agricultural productivity to support increased incomes, food security and development; secondly, increasing adaptive capacity at multiple levels (from farm to nation); and thirdly, decreasing greenhouse gas emissions and increasing carbon sinks.” [2].
Geographic information systems (GIS) are another form of agriculture 4.0, which are characterised by a significant use of GPS technology. The latter allows plots to be mapped for increased precision during technical operations [3]. For example, mapping the nitrogen requirements of a plot allows the inputs to be tailored not just at plot-level but for different zones within it identified by satellite.
Another interesting area is co-farming — or mutual agricultural assistance. This term was developed by companies using digital platforms to help farmers link up with each other for commercial relationships without intermediaries (such as rental of equipment, sale of fodder, etc.) or to share knowledge and experience [4].
With these few examples, agriculture 4.0 seems to meet the needs of productivity, sustainability, efficiency or socio-economic issues.
Improving Farm Resilience
Agriculture 4.0 reduces the amount of inputs (fertilizers and plant health products) required, as well as optimising travel to reduce mechanisation loads thanks to greater precision. These technologies help reduce farm costs by making farms more economical at a time that farm income is trending downwards, is under the income of the average population and is highly dependent on [5].
The farmer also gains decision-making autonomy, thanks to tools that allow field surveys and access to some of the data on dedicated platforms. Like any new technology, agriculture 4.0 raises many questions among users. This fosters knowledge exchange and sharing among farmers in groups run by different networks: agricultural chambers of commerce, management centres, associations, trade unions etc.
In a nutshell, new technologies are not intended to replace agricultural consulting, but to provide it with new tools. While most of the data is used on the micro level (plot of land or head of cattle), the agronomist is still required to make use of the results in systemic analyses (agrarian systems, or livestock and cropping systems) integrated into the wider area around the farm.
While there are some challenges ahead, such as short-term concerns about the interoperability of various platforms or the ownership of data collected, agriculture 4.0 is a promising tool. It can refine the analysis and precision of technological solution provided by farmers, consultants, technical and research organizations, with the aim of achieving a more sustainable and resilient agriculture.
BIBLIOGRAPHY
[1] Tonk Ke, F., 2013. Smart Agriculture Based on Cloud Computing and IOT. Journal of Convergence Information Technology (JCIT). 8. 2. Online: link.
[2] Campbell, B. M., Thornton, P., Zougmoré, R., Van Asten, P., & Lipper, L. 2014. Sustainable intensification: What is its role in climate smart agriculture? Current Opinion in Environmental Sustainability, 8, 39-43. Online: link.
[3] Dekhinat, S. Sahli, M. 2009. Les SIG comme outils d’aide à la décision dans le domaine agricole. [GIS as tools for decision support in agriculture] In SIG 2009. ESRI Francophone Conference. 30 September and 1st October 2009. Versailles. Online: link.
[4] Farmleap. Not dated. Co-farming as a collaborative economy to advance agriculture. Farmleap. Online : link.
[5] Commission des comptes de la nation. [National Accounts Commission]. 2017. Les résultats économiques des exploitations agricoles en 2016 [The economic performance of farms in 2016.] Service de la statistique et de la prospective [Statistics and Forecasting Service]. Ministère de l’agriculture et de l’alimentation [Ministry of Agriculture and Food]. Online: link.
Related
This post is also available in: FR (FR)DE (DE)