Loconsole et al. (2025) Soil Moisture Sensing Technologies: Principles, Applications, and Challenges in Agriculture

Identification

• Journal: Agronomy
• Year: 2025
• Date: 2025-12-03
• Authors: Danilo Loconsole, Michele Elia, Giulia Conversa, Barbara De Lucia, Giuseppe Cristiano, Antonio Elia
• DOI: 10.3390/agronomy15122788

Research Groups

• Department of Agriculture, Food, Natural Resources and Engineering (DAFNE), University of Foggia, Foggia, Italy
• Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, Bari, Italy

Short Summary

This review comprehensively evaluates invasive and non-invasive soil moisture sensing technologies, discussing their principles, applications, strengths, and limitations in agriculture. It highlights recent innovations and identifies key challenges to widespread adoption, particularly for smallholder farmers, while proposing strategies for future development.

Objective

• To provide a comprehensive review and critical analysis of advancements in invasive and non-invasive soil moisture sensing technologies, including their operating principles, comparative performance, emerging trends, and practical applications in agriculture, while also identifying challenges to widespread adoption.

Study Configuration

• Spatial Scale: Covers point-scale measurements (e.g., individual sensors), field-scale monitoring (e.g., automated networks, ground-penetrating radar, electromagnetic induction), and large-scale remote sensing (e.g., cosmic-ray neutron sensors with footprints of hundreds of meters in diameter, satellite platforms like Sentinel-1, SMAP, SMOS with resolutions from 10 meters to 1000 meters).
• Temporal Scale: Discusses technologies for real-time, continuous, and long-term monitoring, with response times ranging from rapid (1-2 minutes for neutron probes) to delayed (30-60 minutes for hydrogel sensors, over 4 hours for cosmic ray sensors).

Methodology and Data

• Models used: Brutsaert model (for acoustic/seismic waves), Topp empirical formula (for Time-Domain Transmittometry validation), heat-strength model (for heat-pulse sensors), Grey Wolf Optimiser (for Ground-Penetrating Radar inversion).
• Data sources: Systematic narrative review of scientific literature, including peer-reviewed articles and reviews from the Scopus database (1980-2025), as well as technical reports and books. The review synthesizes information from various sensing technologies, including satellite, observation, and reanalysis data.

Main Results

• Soil moisture sensing technologies are broadly categorized into invasive (e.g., dielectric, matric potential, heat-pulse, microstructured optical fiber, neutron probe, RFID, hydrogel, thermal dissipation, MEMS, biodegradable) and non-invasive (e.g., gamma-ray, microwave, radio/acoustic/seismic waves, seismoelectric, cosmic ray, electromagnetic induction, near-infrared optical, ground-penetrating radar, GPS interferometric reflectometry). Each category encompasses diverse operating principles, strengths, and limitations.
• Key performance factors across all sensor types include installation methodology, environmental sensitivity (salinity, temperature, soil type), spatial representativeness, and integration with decision-support systems.
• Invasive sensors offer high-resolution data but require careful installation and calibration. Dielectric sensors (TDR, FDR, TDT, FDT, ADR, SWR, capacitance, resistance) vary in accuracy, cost, and sensitivity to soil properties; TDR offers high precision but is expensive, while capacitance sensors are affordable but require calibration. Tensiometers and resistive sensors are user-friendly and cost-effective but offer lower precision and require frequent maintenance. Microstructured optical fiber, fiber optic, and neutron probe sensors are less affected by soil type. MEMS and RFID-based sensors show promise for Internet of Things (IoT) integration. Neutron probes are highly accurate (±1–2% volumetric water content) but costly, complex, and pose radiation risks, limiting widespread use.
• Non-invasive sensors enable large-scale monitoring without disturbing the soil. Gamma-ray and cosmic ray sensors provide high accuracy and broad coverage (260–600 m radius) but are expensive, power-intensive, and require specialized expertise and safety protocols. Microwave-based and electromagnetic induction (EMI) sensors offer a balanced profile for real-time data and IoT integration. Seismoelectric and acoustic/seismic wave methods are experimental, facing challenges in complexity and scalability. Near-infrared optical and Ground-Penetrating Radar (GPR) systems offer high accuracy but demand advanced interpretation and significant power. GPS interferometric reflectometry (GPS-IR) is low-cost but limited to shallow depths (approximately 0.05 m) and primarily used for geospatial monitoring.
• Recent innovations include biodegradable sensors, Micro–Electro–Mechanical Systems (MEMS), and the integration of IoT platforms and artificial intelligence (AI) for enhanced data analytics and sensor calibration.
• Despite demonstrated benefits in irrigation efficiency and yield improvement, widespread adoption of soil moisture sensors is hindered by high costs, calibration complexities, data integration issues, and limited accessibility, particularly for smallholder farmers. Environmental factors such as soil heterogeneity, salinity (e.g., >1 dS m−1 for GPR), and temperature fluctuations (e.g., for capacitance sensors) also significantly impact sensor performance and reliability.

Contributions

This comprehensive review synthesizes the current state of soil moisture sensing technologies, critically evaluating both invasive and non-invasive methods, their operating principles, comparative performance, and practical applications in agriculture. It highlights recent innovations (e.g., biodegradable sensors, MEMS, IoT, AI integration) and identifies key research gaps and barriers to widespread adoption, particularly for smallholder farmers. The review also proposes strategies for future development and implementation to foster more resource-efficient and climate-resilient agricultural practices.

Funding

• European Union under the Italian National Recovery and Resilience Plan (NRRP) of Next-GenerationEU
• Agritech National Research Center (NRRP—Mission 4 Component 2, Investment 1.4—D.D. 1032 17 June 2022, CN00000022)

Citation

@article{Loconsole2025Soil,
  author = {Loconsole, Danilo and Elia, Michele and Conversa, Giulia and Lucia, Barbara De and Cristiano, Giuseppe and Elia, Antonio},
  title = {Soil Moisture Sensing Technologies: Principles, Applications, and Challenges in Agriculture},
  journal = {Agronomy},
  year = {2025},
  doi = {10.3390/agronomy15122788},
  url = {https://doi.org/10.3390/agronomy15122788}
}