Development and Validation of a Low-Cost DAQ for Agriculture

Strategic Insights -

Researchers from the University of Pisa have developed and validated a low-cost data acquisition (DAQ) system for agriculture, addressing the high cost barrier to widespread adoption of electromagnetic induction (EMI) devices. The open-source DAQ system employs a Raspberry Pi 4 model and various components to monitor soil bulk properties, nutrient status, and non-invasive soil salinity measurements. The system's performance is comparable to a proprietary CR1000 system, with a strong correlation (R[superscript]2 = 0.98) observed between the data collected from both systems.

Key Takeaways:

  • The researchers developed a cost-effective, easy-to-use, open-source DAQ system, transferable to the end user, utilizing a Raspberry Pi 4 model and various components.
  • The DAQ system successfully extracts the analogical signal from the EM38 device, which is strongly responsive to the variation in the soil's physical properties.
  • The low-cost DAQ system provides performance comparable to the proprietary system in terms of its geospatial data and ECb measurements.
  • The researchers revealed similar patterns in the ECb data and Normalized Difference Vegetation Index (NDVI) map, suggesting that soil physical characteristics contribute to variability in crop vigor.
  • The developed web application enables real-time data monitoring and visualization.
  • Future enhancements will focus on integrating additional sensors for plant vigor and soil temperature, as well as refining the web application.

Statistics:

  • The DAQ system was able to collect data with a strong correlation (R[superscript]2 = 0.98) between the data collected from the open-source DAQ system and the proprietary CR1000 system.
  • The system was able to monitor soil bulk properties, nutrient status, and non-invasive soil salinity measurements.
  • The DAQ system was compared to the proprietary CR1000 system with similar patterns observed in the ECb data and Normalized Difference Vegetation Index (NDVI) map.

Sources:

  • NewsRx. Researchers from University of Pisa Detail New Studies and Findings in the Area of Agriculture (Development and Validation of a Low-Cost DAQ for the Detection of Soil Bulk Electrical Conductivity and Encoding of Visual Data). Agriculture Week. October 16, 2025; p 693.
  • Development and Validation of a Low-Cost DAQ for the Detection of Soil Bulk Electrical Conductivity and Encoding of Visual Data. AgriEngineering, 2025,7(9):279.
  • MDPI AG. AgriEngineering.
  • doi-org.sdpl.idm.oclc.org/10.3390/agriengineering7090279