Soil Fertility, Plant Nutrition and Soil Health

From the second half of the 2010s, much has been speculated about the use of sensors in agriculture, both directly in the field and in laboratories to replace traditional methods of analysis, which are more time-consuming and use chemical reagents. The application of sensors are the modernization of traditional soil analysis methods, which promote a drastic change in the current way in which agricultural analysis laboratories work.

This report has the central objective of deepening knowledge about the potential and limitations of using direct soil analysis sensors to diagnose soil fertility, understanding which are best for this application, and understanding how agronomic laboratories and consultancies have approached these technologies.

Research showed that there is a very large expansion of sensor applications in agriculture, which occurs mainly in countries with more technical agriculture. In general, the community linked to agricultural analysis laboratories is very interested in the application of sensors to lower cost and enable robust analysis directly in the field. However, there are not many companies that have ideas on how to apply sensors in a concrete and cost-effective way. In addition, there are not many soil analysis laboratories that make transparent combinations of sensors with traditional methods for assessing soil fertility. It is somewhat common to find companies that try to advance their marketing and publicity strategies, even before the complete development of the technology.

Public and/or private institutions need to seek partnerships and resources (e.g., via research support foundations) to develop procedures and soil spectral libraries using sensor data to enable the use and expansion of these technologies that benefit the entire chain. In summary, make easy-to-use equipment available for producers and resellers, embed sensors in robots and/or agricultural machines, among others. There will be advances in the integration of different sources of information (e.g., satellite, yield maps, fertility maps, etc.), enabling the development of libraries with large amounts of data that allow subsidising at the farm level (via on-farm experimentation) and decision-making to optimise the use of agricultural inputs.

This report is available to download in Portuguese.