Our competences

Photo: Manuel Gutjahr

WG Proximal soil sensing

On many farms, the smallest management unit is conventionally the field. There, measures of fertilization, tillage or harvest are usually performed uniformly. However, within a field, a high spatial variability in soil properties can exist due to the underlying geology or landuse history of the site. A uniform management such as fertilization then leads to an over-fertilization of one part of the field which results in a waste of resources and environmental pollution. On other parts of the field, on the other hand, the yield potential is still not exploited. Particularly against the background of an ever stricter fertilizer ordinance, site-specific management enables the application doses to be specifically adapted to these small-scale differences in demand. Therefore, however, a high-resolution mapping of the spatial variability of soil characteristics is important. This high resolution of soil data cannot be achieved through costly and time-consuming laboratory analyzes alone. Soil mapping with sensors is a comparatively quick and cost-efficient alternative.

The working group “Proximal soil sensing” studies, develops and tests various sensor technologies regarding their applicability for mapping physical and chemical soil properties. Thereby, soil science, agronomics and engineering science work closely together.

The approaches used include:

  • Geoelectrics (ECa),
  • Geomagnetic (EMI),
  • Ion-selective electrodes (e.g. pH, NO3, NH4+, K+),
  • Optical spectroscopy in the visual, near infrared and mid infrared range (visNIRS, MIRS),
  • Terahertz spectroscopy (THz),
  • X-ray fluorescence spectroscopy (XRF),
  • laser-induced breakdown spectroscopy (LIBS),
  • Gamma spectroscopy,
  • Penetration resistance.

The development of these technologies for soil mapping is quite different. Some systems have not yet been tested on soil as a medium. Others are still partly laboratory-based or, as handheld devices or on mobile platforms, are already suitable for stop-and-go or on-the-go use in the field. An important goal is the fusion and integration of several sensor systems on mobile multi-sensor platforms which allow a simultaneous measurement of multiple yield-relevant soil properties with only one pass. For the evaluation of the resulting large amounts of data generated in this process, we work closely with the ATB junior research group “Data Science in Agriculture”. In order to be able to record subsoil properties, we furthermore develop a system for sensor-based soil profile measurements.

By combining the high-resolution soil data obtained in this working group with crop data from the “Precise Crop Monitoring” working group, it is also possible to examine the yield effects of individual soil properties on specific crops in more detail. In interaction, sensor-based soil mapping makes an important contribution to digital, resource-saving and yield-optimized precision agriculture.

Group leader

Dr. rer. nat. Vogel, Sebastian

Scientist, Group leader "Proximal Soil Sensing"


Department: Agromechatronics

Email: SVogel@spam.atb-potsdam.de

zum Profil

Cookies

We use cookies on our website to offer you the best possible content and functions and to anonymously analyze access to our website.

Please note that without your consent, some functionalities of the website may not be available.

You can view the cookie settings to give controlled consent.

Required required

Necessary cookies are absolutely essential for the proper functioning of the website. This category only includes cookies that ensure basic functionalities and security features of the website. These cookies do not store any personal information.

Cookie Duration Description
PHPSESSID Session Stores your current session with reference to PHP applications, ensuring that all features of the site can be displayed properly. The cookie is deleted when the browser is closed.
bakery 24 hours Stores your cookie preferences.
fe_typo_user Session Is used to identify a session ID when logging into the TYPO3 frontend.
__Secure-typo3nonce_xxx Session Security-related. For internal use by TYPO3.
Analytics

With cookies in this category, we learn from visitors' behavior on our website and can make relevant information even more accessible.

Cookie Duration Description
_pk_id.xxx 13 months Matomo - User ID (for anonymous statistical analysis of visitor traffic; determines which user is being tracked)
_pk_ses.xxx 30 minutes Matomo - Session ID (for anonymous statistical analysis of visitor traffic; determines which session is being tracked)