Introduction
In the face of mounting agricultural challenges—including climate variability, soil degradation, and the urgent need for sustainable practices—accurate and timely soil health assessment has become more critical than ever. However, the tools currently available on the market fall short of capturing the full biological complexity of soil ecosystems.
Modern soil sensors use a range of technologies to measure key physical and chemical parameters. Common models assess volumetric moisture content through dielectric properties, soil tension via electrical resistance, and nutrient concentrations using electrochemical or optical methods. Some specialise in monitoring soil temperature with thermistors, electrical conductivity to evaluate salinity and fertility, and pH through ion-selective electrodes. Advanced multi-parameter sensors combine these functions into a single unit, offering comprehensive soil diagnostics. Despite their utility, these tools have several limitations. They lack biological resolution and cannot detect microbial activity, fungal dynamics, or organic matter decomposition. Most rely on point-based measurements, which may misrepresent broader soil conditions due to spatial variability. Biological indicators such as microbial diversity or fungal presence still require laboratory testing, including DNA sequencing, culturing, or respiration analysis, making the process time-consuming and resource-intensive.
Fungi play a foundational role in soil health. They drive nutrient cycling and organic matter decomposition, form symbiotic relationships with plants (such as mycorrhizae), and respond sensitively to pollutants, compaction, and biodiversity shifts. Fungal mycelium, in particular, serves as a powerful bioindicator due to its direct involvement in key soil processes. It contributes to nutrient cycling by breaking down organic matter and releasing essential elements like nitrogen and phosphorus. Its hyphal networks help form soil structure by binding particles and improving porosity and aeration. Mycorrhizal fungi enhance water and nutrient uptake in plants, while some fungal species suppress disease by outcompeting pathogens or producing anti-fungal compounds. Additionally, fungal biomass plays a role in long-term carbon sequestration.
When soil conditions deteriorate due to pollution, drought, or nutrient imbalance, mycelial activity declines. These changes can be detected through shifts in electrical signalling. A biosensor system based on live fungal species offers a biologically intelligent alternative to conventional sensors. By observing fungal metabolic responses to soil, such a system can infer soil vitality and nutrient richness, detect pollutants or heavy metals, assess microbial diversity and nutrient cycling efficiency, and reveal changes in soil structure and biodiversity. This approach removes the need for complex laboratory protocols and enables real-time, in situ biological sensing, offering a more holistic understanding of soil health.
There is no known patent that directly covers a fungal-based soil health sensor system that uses mycelial bioelectric signalling as the primary sensing mechanism. That said, there are related technologies in the broader space of soil sensing and microbial interfaces (please see references section).
Advantages of a Fungal Biosensor System:
- Biological Activity Monitoring: Conventional sensors are unable to measure microbial or fungal dynamics, limiting their capacity to assess biological processes. In contrast, a fungal biosensor could actively track phenomena such as mycelial growth and metabolism, offering a direct window into living systems.
- Pollutant Detection: While conventional sensors rely on indirect chemical indicators to infer pollution levels, a fungal biosensor could detect pollutants through biological responses. These include stress signalling and metabolic shifts, providing a more nuanced and responsive detection method.
- Soil Biodiversity Sensitivity: Conventional sensors lack sensitivity to microbial diversity and ecological changes, making them ineffective for biodiversity monitoring. Fungal biosensors, however, could respond to shifts in biodiversity, delivering ecological insights that conventional tools overlook.
- Laboratory Dependence: Many conventional sensors require laboratory testing—such as DNA sequencing—to obtain biological data. Fungal biosensors would bypass this need by enabling direct, in situ biological sensing, eliminating the dependency on lab protocols.
- Real-Time, In Situ Sensing: Conventional sensors are typically limited to measuring physical and chemical parameters, which may not reflect biological health. Fungal biosensors would provide immediate feedback on soil conditions through live fungal responses, enabling real-time ecological assessment.
- Affordability for Smallholders: The cost and complexity of conventional sensors often make them inaccessible to small-scale farmers. Fungal biosensors can be constructed as modular, low-tech, and designed for affordability, making them suitable for deployment in diverse agricultural and environmental settings.
Soil Health Metrics Detectable via Mycelial Sensors:
- Moisture: Fungal biosensors will respond to moisture through changes in hyphal conductivity and ion transport. These physiological shifts manifest as electrical signal variations, including voltage spikes or drops and impedance fluctuations, offering a dynamic readout of hydration levels.
- pH: Variations in pH influence fungal membrane potential and enzyme activity. These biochemical responses translate into altered electrical signals, typically seen as changes in spike frequency or amplitude within the biosensor’s output.
- Nutrient Levels: Fungal growth rate and metabolic activity are sensitive indicators of nutrient availability. As these biological processes intensify or diminish, the biosensor can reflects the change through increased signal complexity and frequency modulation.
- Heavy Metals / Toxins: Exposure to heavy metals or toxins suppresses fungal enzyme function and triggers stress signalling pathways. These disruptions lead to dampened electrical signals and reduced spike activity, serving as a biological alert system for contamination.
- Microbial Diversity: Fungal biosensors would engage in symbiotic and competitive interactions with surrounding microbes. These ecological dynamics produce distinct signal patterns and heightened noise complexity, revealing shifts in microbial diversity.
- Temperature: Temperature fluctuations affect fungal metabolic rates and ion channel behaviour. These physiological changes result in amplitude shifts and delayed signal responses, enabling the biosensor to track thermal conditions in real time.
What Fungal Bioelectric Signals Look Like:
- Fungal Electrical Signalling: Fungal mycelium produces low-voltage electrical pulses in response to environmental stimuli. These signals often take the form of voltage spikes or bursts, resembling action potentials observed in neurons. Additionally, the amplitude of these signals may oscillate over time, reflecting underlying metabolic rhythms. Impedance shifts are also common, typically resulting from ion transport and variations in moisture content.
- Voltage Amplitude: Signal strength typically ranges from approximately 100 microvolts to 10 millivolts. This amplitude varies depending on the fungal species involved and the specific soil conditions in which the biosensor operates.
- Frequency: Signal frequency spans from about 0.1 Hz to 10 Hz. This includes both slow oscillatory patterns and rapid bursts, offering a dynamic profile of fungal activity.
- Duration: Individual spikes generally last between 1 and 10 seconds. These durations tend to be irregular and are closely tied to the nature and intensity of environmental stimuli.
- Impedance: Electrical impedance within fungal biosensors ranges from roughly 10 kilo-ohms to 1 mega-ohm. These values are influenced by factors such as moisture levels and the concentration of ions in the surrounding medium.
Based on studies and reviews (please see the references section), three simulated scenarios are outlined below: