55 channels.
One plant.
The complete physiological picture.
Syntheflora attaches directly to the plant — not to the environment around it. Every channel reads a different dimension of what the plant is doing: how water is moving, where stress is building, how fast it is growing, what it is pulling from the soil. Measured continuously. In the plant. In real time.
What it measures.
Most instruments describe the crop from the outside. Syntheflora reads it from within. The sensor array attaches to leaf, stem, root zone, and canopy and measures the physiological processes that determine how a plant is actually doing — not how its environment appears to be treating it.
What the plant is feeling before you can see it.
Tissue impedance and biopotentials in the stem change before visible stress symptoms appear in leaves. The system detects these shifts continuously, in vivo — not through a proxy measurement like canopy temperature or NDVI, which describe symptoms after stress has already developed.
When leaf turgor pressure drops, transpiration rate changes, or the electrochemical profile of the stem shifts, the system records it. You receive an alert when the plant crosses a physiological threshold. The leaf has not wilted. The chlorophyll has not changed colour. But the data has already told you what is coming.
Not whether the soil is wet. Whether the plant is hydrated.
Sap flow measures the rate at which water moves through the xylem — upward from root to canopy. Tissue impedance tracks the fluid content of stem tissue electrochemically. Together, these channels describe the entire water journey: from soil to root uptake to stem transport to leaf transpiration.
Phloem and xylem flows can be distinguished electrochemically using time-frequency EIS — upflow carrying water and minerals reads differently from downflow carrying photosynthates. The system tracks both. This is where deficit irrigation precision begins.
Actual growth rate. Measured. Not modelled.
Above-ground biomass is measured continuously using dielectric spectroscopy at 0.5–3 MHz. The sensor detects changes in the dielectric properties of plant tissue as it grows — providing a real-time growth rate curve rather than a snapshot taken at harvest or weekly manual measurement.
When growth rate changes — accelerating after an optimal irrigation event, slowing under nutrient stress, recovering after a deficit cycle — the system records the moment it happened, not the result three weeks later.
What the plant is pulling from the soil versus what you are putting into it.
Chlorophyll and flavonoid content are measured optically via external spectroscopy at the leaf. Chlorophyll is the primary indicator of photosynthetic capacity and nitrogen status. Flavonoids reflect UV-screening responses and secondary metabolite production — the phenolic compounds that define quality in wine grapes, tomatoes, and specialty crops.
Electrochemical impedance spectroscopy in the stem differentiates between photosynthates flowing downward and minerals moving upward. This gives a real-time picture of the plant's metabolic state that no soil test or foliar analysis can match.
The context in which everything above is happening.
Physiological data is most valuable when it can be read against the environmental conditions that produced it. Light intensity, air temperature, air humidity, CO₂ concentration, and spectral light quality are recorded continuously alongside every biological channel.
At the canopy level, photosynthetically active radiation (PAR) and the spectral reflectance sensor measure the light environment actually reaching the canopy — not the light output of the fixture, which tells you nothing about what the plant is absorbing.
The complete technical specification — full sensor list, firmware parameters, and output channel definitions — is available as a downloadable PDF.
Download Full Technical Specifications →Before Gemini, interpreting this data required a specialist.
The physiological parameters measured by Syntheflora — tissue impedance, sap flow, biopotentials, electrochemical spectroscopy, root dynamics, and environmental channels — do not yield useful agronomic insight individually. Their value is in the relationships between them, observed simultaneously, across the full sensor array, over time. Understanding those relationships in real time has historically required a plant physiologist with specific expertise in electrophysiology and biophysical data interpretation. That expertise does not exist at commercial scale in most growing operations.
Syntheflora integrates Google Gemini AI directly into the data pipeline. All active channels are processed simultaneously. The output is delivered in plain language: what the plant's physiological state indicates, what that means for irrigation timing, nutrient delivery, and environmental control, and what the priority action is.
A vineyard manager in Rioja, a greenhouse operator in the Netherlands, a vertical farm manager in Singapore receives the same quality of interpretation that previously required a plant physiologist in Stuttgart.
The Gemini integration is not a chatbot layer added to a dashboard. It is the analytical core of the system. Without it, the sensor data is rich but specialist-dependent. With it, the sensor data becomes actionable for any technically literate grower.
One device. Three configurations.
The hardware is identical across all three configurations — the same sensor suite, the same measurement unit, the same Gemini integration. What differs is the wiring specification, the scope of data access, and the support structure. A result published by a university research team using the Research Configuration is directly comparable to data from a Commercial Agriculture deployment. The instrument is the same.
| Commercial Agriculture | Outdoor Conventional | University Research | |
|---|---|---|---|
| Best suited for | Indoor, vertical farm, greenhouse, controlled-environment operations | Outdoor field crops, vineyards, orchards, open-ground horticulture | Academic plant science, agronomy research, phenotyping, published R&D |
| Hardware | Full sensor suite | Full sensor suite | Full sensor suite |
| Wiring | B2B commercial-grade indoor wiring | Field-grade weatherproofing, UV-resistant cabling | Research-grade, lab and field compatible |
| Analytics output | Real-time Gemini agronomic interpretation, plain language | Real-time Gemini agronomic interpretation, plain language | Full raw data export, Python API, Gemini integration |
| Actuation | 3× 220V relay, 3× 12V PWM | 3× 220V relay, 3× 12V PWM | Full actuation suite + experimental control protocols |
| Support | Agronomy and data science team, deployment guidance, ongoing advisory | Agronomy team, deployment guidance | Full technical support, publication review, CYBRES team access |
| Pricing | Consultation-based | Consultation-based | Near-cost research program |
| Request a Consultation → | Request a Consultation → | Apply for the Research Program → |
From plant signal to agronomic action. Four layers.
Biological sensor array
The phytosensor reads from within the plant tissue — electrodes inserted into phloem and xylem, sensors fixed to leaf and stem surfaces, biomass sensors monitoring root zone and above-ground growth. The plant is not a data source to be sampled. It is a continuous transmitter.
Up to 45 real biological channels. Continuous sampling at 1–99 second intervals. Electrodes, optical sensors, thermal sensors, and impedance arrays operating simultaneously.
On-device signal processing
Digital signal processing and physiological model calculation happen on the measurement unit, not in the cloud. Threshold-based controllers operate on real-time data channels — if tissue impedance crosses a set value, the irrigation relay activates. Embedded timers manage scheduled protocols.
The edge layer is critical for operations with intermittent cloud connectivity and where actuation speed matters. The plant does not wait for a server response before it wilts.
Intelligence layer
Processed physiological data is transmitted to Google Gemini AI, which interprets all active channels simultaneously. Gemini identifies correlations across channels that no single-parameter rule set would catch, generates structured agronomic interpretation in plain language, and issues actuation recommendations.
This layer is where the intelligence lives. The edge layer executes. Gemini reasons. Without it, the sensor data is rich but specialist-dependent. With it, the data becomes actionable for any technically literate grower.
Physical control outputs
Three 220V/110V relay outputs and three 12V PWM driver outputs connect to irrigation valves, variable-spectrum LED grow lights, fertigation dosing pumps, aeration fans, and climate control systems.
Human-in-the-loop controls remain active at all times. The system recommends and the grower decides — or the grower sets thresholds and the system acts within them. Full automation and advisory modes are both supported.
Integration and data access.
Syntheflora is designed to export data to wherever your operation already processes it.
| Local connection | USB, COM port (ASCII data output) |
| Programming interface | Python API (named pipe, Windows) · COM port ASCII stream (Linux / embedded) |
| Real biological channels | Up to 45 |
| Synthetic EIS channels | Up to 35 (with EIS statistics package) |
| Total simultaneous channels | Up to 80 |
| Commercial deployment | 55–60 channels (standard configuration) |
| Sampling rate | 1–99 seconds per cycle (configurable in init.ini) |
| Real-time analytics | Regression, spectral analysis, correlation, statistical package |
| Cloud integration | Google Gemini AI |
| Raw data export | Full export, all channels — CSV and ASCII formats |
| ERP / LIMS compatibility | Export-ready structured data; API available |
| Operating systems | Windows (full feature set) · Linux · Embedded devices |
| Power management | <3.5 kW total |
| 220V / 110V relay outputs | 3× (controllable) |
| 12V PWM outputs | 3× (PWM-capable — water pumps, air fans, lighting) |
| Firmware version | ≥ 1189.49 |
Data collected by the Syntheflora system belongs to the grower or institution operating it. CYBRES and Vertical Green do not hold rights to operational data. Aggregated and anonymised findings from research deployments may contribute to published research under agreed attribution protocols.
Seen enough to want to talk?
The best way to understand what Syntheflora would mean for your specific operation — your crops, your region, your infrastructure — is a direct conversation with an agronomist who knows the system.