Agrisensors Stem Flow (Sap Flow) Cloud Monitoring Platform
| Brand | Dynamax |
|---|---|
| Origin | USA |
| Manufacturer Type | Authorized Distributor |
| Product Origin | Imported |
| Model | Agrisensors |
| Pricing | Available Upon Request |
Overview
The Agrisensors Stem Flow Cloud Monitoring Platform is a web-based, secure SaaS infrastructure engineered for continuous, remote acquisition, visualization, and analysis of plant sap flow dynamics in field and greenhouse environments. Built on a scalable cloud architecture, it serves as the central data hub for Dynamax’s SapIP family of wireless sensor nodes—including SapIP stem flow probes, SapIP-IRT infrared leaf temperature sensors, SapIP-MICRO micro-meteorological stations, and DEX fruit/tree stem diameter variation sensors. The platform operates on the principle of thermal dissipation (TDP), heat pulse (HP), or compensation heat pulse (CHP) methodologies—depending on the connected probe type—to quantify real-time xylem sap velocity and volumetric flow rates. Data are transmitted via LoRaWAN or cellular gateways to encrypted AWS-hosted servers, enabling time-synchronized multi-parameter correlation across physiological, environmental, and phenological domains.
Key Features
- Interactive GIS dashboard with georeferenced mapping of all SapIP sensor nodes and gateway locations; supports zoom, pan, custom placemarks, and site-level annotations
- Remote configuration interface for real-time node status monitoring, sensor type assignment, channel calibration parameters, sampling intervals, and firmware updates
- Multi-layer time-series visualization: overlay sap flow (g·h⁻¹ or L·day⁻¹), canopy temperature (°C), net radiation (W·m⁻²), vapor pressure deficit (kPa), soil volumetric water content (m³·m⁻³), and reference evapotranspiration (ET₀, mm·day⁻¹)
- Dynamic charting engine supporting user-defined temporal windows—from hourly resolution over 72 hours to monthly aggregates spanning multiple growing seasons—with hover-triggered tooltips displaying timestamped raw values and metadata
- Stress index computation: automated Ks (stress coefficient) derivation via ratio of measured sap flow to potential transpiration under non-limiting water conditions, aligned with FAO-56 methodology
- Role-based access control (RBAC) with audit logs compliant with GLP-aligned data integrity requirements; exportable CSV/JSON datasets include full provenance tracking (sensor ID, UTC timestamp, QC flag, unit conversion factor)
Sample Compatibility & Compliance
The Agrisensors platform is agnostic to plant species and growth form, supporting deployment across woody perennials (e.g., Vitis vinifera, Prunus persica, Eucalyptus globulus), herbaceous crops (Zea mays, Solanum lycopersicum), and native ecological stands. All connected hardware—including SapIP probes and DEX dendrometers—complies with IEC 60529 IP67 ingress protection standards and operates within USDA ARS-recommended thermal stability ranges (−20 °C to +60 °C ambient). Data workflows align with ISO 18400-101 (soil quality—sampling principles) and ASTM E2911 (standard guide for plant water status measurement), while audit trail functionality satisfies traceability expectations under FDA 21 CFR Part 11 for research-grade environmental physiology studies.
Software & Data Management
Accessed via modern HTML5 browsers (Chrome, Firefox, Edge) without plugin dependencies, the platform delivers TLS 1.3–encrypted sessions and OAuth 2.0 authentication. Raw sensor data undergo on-server validation: outlier detection using Tukey’s fences (IQR × 1.5), gap-filling via piecewise cubic Hermite interpolation for short-duration dropouts (30% over 48 h) with email/SMS notifications. All datasets are archived in immutable object storage with versioned backups retained for ≥7 years—supporting reproducibility requirements in peer-reviewed publications and long-term ecological research networks (e.g., NEON, TERENO).
Applications
- Irrigation scheduling optimization in viticulture and orchard systems through Ks-guided deficit irrigation protocols
- Quantifying drought response phenotypes across germplasm trials under controlled stress gradients
- Validating stomatal conductance models (e.g., Ball-Berry, Medlyn) using direct sap flow-derived transpiration estimates
- Integrating tree water use into watershed-scale hydrological models (e.g., SWAT, MIKE SHE)
- Monitoring diurnal carbon-water coupling in climate change manipulation experiments (e.g., FACE, T-FACE)
- Supporting certification of sustainable water stewardship (AWS Standard 3.0) through auditable, high-temporal-resolution water use reporting
FAQ
Does Agrisensors support integration with third-party weather stations or SCADA systems?
Yes—via RESTful API endpoints (JSON/HTTPS) and Modbus TCP bridging modules; documented integration guides available for Campbell Scientific CR1000X, Davis Vantage Pro2, and Siemens Desigo CC platforms.
What is the typical latency between sensor measurement and dashboard visualization?
Median end-to-end latency is 92 seconds under standard LoRaWAN configuration; sub-30-second latency achievable with LTE-M gateways and edge preprocessing enabled.
Can historical data be reprocessed if calibration coefficients are updated?
Yes—users may trigger batch reprocessing of stored raw voltage/time series using revised probe-specific thermal conductivity or wound correction factors; original and recalibrated versions are preserved with lineage metadata.
Is offline data collection supported during network outages?
All SapIP nodes feature onboard SD card logging (up to 12 months at 15-min intervals); data auto-syncs upon gateway reconnection with conflict-free vector clock reconciliation.
How does the platform handle sensor drift or failure detection?
Automated diagnostics compare inter-channel consistency, baseline thermal noise profiles, and diurnal pattern entropy; alerts escalate from warning (yellow) to critical (red) based on ISO 5725-2 repeatability thresholds.
