Most precision agriculture systems measure the environment around the plant. Syntheflora measures the plant itself — from inside its tissues, in real time. The distinction determines whether precision irrigation is genuinely precise or merely scheduled.
La industria de sensores agrícolas ha producido monitoreo sofisticado de condiciones ambientales.
Syntheflora in-vivo plant intelligence sensors address this limitation directly. By measuring dielectric properties, stem tissue impedance, sap flow rates, and leaf turgor pressure — measurements that come from within plant tissues rather than from surrounding conditions — Syntheflora enables precision deficit irrigation con un nivel de precisión que los sistemas basados en el entorno no pueden alcanzar. Resultados: hasta 40% de ahorro de agua. 40% water reduction, 24–30% higher Brix, y un contenido fenólico elevado que refleja PAL enzyme upregulation triggered by precisely calibrated water stress.
What Syntheflora Measures
Syntheflora deploys a suite of sensor types, each capturing a distinct dimension of plant physiology. Together they provide a comprehensive real-time portrait of the plant's internal state — information that determines whether irrigation should occur, when it should occur, and how much should be delivered.
Espectroscopía Dieléctrica — Estado Real del Agua en la Planta
La espectroscopía dieléctrica mide la permitividad eléctrica de los tejidos vegetales a través de múltiples frecuencias. El contenido de agua de la planta cambia las propiedades dieléctricas de los tejidos de una manera medible y específica de la especie. Esto permite la medición no destructiva en tiempo real de:
- Actual plant water content (as opposed to substrate moisture, which doesn't directly report plant status)
- Biomass accumulation rate — changes in tissue dry matter relative to water content
- Estado de estrés — detección temprana de déficit hídrico o de nutrientes antes de signos visibles.
- Momento óptimo de riego — el instante preciso en que el déficit desencadena la respuesta sin daño.
Impedancia del Tejido del Tallo
Bioelectrical impedance of stem tissue changes measurably as the plant's water status changes. Cell membrane integrity, turgor pressure, and vascular flow rates all contribute to tissue impedance. Syntheflora stem impedance sensors detect:
- Early warning of water deficit — impedance changes precede visible wilting by hours in most species
- Actividad vascular en tiempo real — la eficiencia del sistema de transporte de agua de la planta.
- Confirmación de respuesta — cambio de impedancia medible después del riego confirma la absorción.
Flujo de Savia
Los sensores de flujo de savia miden la tasa de movimiento de agua y nutrientes en el sistema vascular.
- Tasa de transpiración — cuánta agua está extrayendo la planta de la zona radicular.
- Confirmación de riego — si la humedad de la zona radicular está siendo absorbida por el sistema vascular.
- Detección de anomalías — cambios repentinos en el flujo de savia que indican enfermedad, daño radicular o eventos de estrés ambiental
Presión de Turgencia Foliar
Leaf turgor — the hydrostatic pressure of water within leaf cells — is the earliest and most sensitive indicator of plant water status. Turgor loss precedes measurable changes in most other water status indicators. Syntheflora leaf turgor sensors detect:
- La señal más temprana de estrés hídrico — horas antes de que la impedancia del tallo muestre cambios.
- Magnitud del déficit en tiempo real — el grado de estrés hídrico relativo al umbral óptimo.
- Recovery confirmation after irrigation — turgor restoration time as an indicator of root-zone water availability
Capa de Soporte Experto y Análisis
Raw sensor data from plant tissues is physiologically meaningful but requires interpretation to become agronomic decisions. Syntheflora's analytics infrastructure handles this translation, converting continuous sensor streams into actionable irrigation and management signals for the CoFarmer AI sistema de gestión agrícola.
La capa de análisis proporciona:
- Arquitectura de datos compatible con ESG y GMP — los registros de sensores cumplen requisitos de trazabilidad para botánicos de grado farmacéutico.
- Integración ERP y LIMS — exportación de datos estructurados a sistemas ERP y LIMS vía API estándar.
- Detección de anomalías y alertas — las desviaciones de líneas base fisiológicas activan alertas antes de que sean pérdidas de cultivo.
- Harvest timing optimisation — las curvas de acumulación de Brix y picos de metabolitos secundarios informan la programación de cosecha.
Resultados del Riego Deficitario de Precisión
El mecanismo por el cual el riego deficitario mejora la calidad: déficit hídrico leve activa PAL. biological stress vías de respuesta incluyendo regulación PAL. El resultado: sólidos solubles concentrados (mayor Brix).
The precision element is critical. Irrigation deficit is beneficial at mild levels and damaging at severe levels. The threshold between "productive stress" and "growth-inhibiting stress" varies between species, cultivars, growth stages, and ambient conditions. Without in-plant measurement, the only way to apply deficit irrigation conservatively is to err on the side of over-irrigation — which eliminates the quality benefit. Syntheflora removes this uncertainty, enabling deficit irrigation at the precise threshold where stress response fires without yield compromise.
Aplicaciones Documentadas
| Crop Type | Water Reduction | Quality Outcome |
|---|---|---|
| Wine grapes | 25–40% | 0–10% de cambio en el rendimiento; mejora en la concentración de polifenoles y antocianinas |
| Tomatoes | 20–35% | Lycopene increase, Brix improvement, intensified flavour |
| Medical cannabis | Variable | GMP-compliant traceability; precise canopy-stage water management |
| Medicinal botanicals | 30–40% | Elevated essential oil content, terpene concentration improvement |
| Leafy greens (Bio-Mimetic) | Up to 40% | +24–30% Brix, elevated phenolics, +57% Vitamin C (combined system) |
Resumen Técnico del Conjunto de Sensores
| Sensor Type | Measurement | Primary Application |
|---|---|---|
| Dielectric spectroscopy | Tissue water content, biomass, stress status | Irrigation timing, growth monitoring |
| Stem impedance electrodes | Vascular activity, water status | Early deficit detection |
| Sap flow sensor | Transpiration rate, water movement | Irrigation confirmation, anomaly detection |
| Leaf turgor clip | Cell hydrostatic pressure | Earliest stress indicator, real-time deficit magnitude |
| Optical leaf sensor | Chlorophyll, anthocyanin fluorescence | Nutritional status, harvest timing |
Preguntas Frecuentes
Adult plant sensors use non-destructive contact methods that attach without cutting or wounding the plant. Leaf clip sensors attach to the leaf blade using gentle spring clips similar to those used in scientific leaf area measurement. Surface-contact turgor sensors use pressure-balanced contact pads against the leaf surface. Stem-contact impedance electrodes use conductive contact against the stem epidermis without penetrating the tissue. Root zone dielectric sensors are placed adjacent to the root system rather than inserted through it. Each approach is designed to produce no wound response that would confound the stress signal data being collected.
Syntheflora uses a representative sampling approach — sensors are placed on indicator plants whose physiological state characterise the broader zone's status. In a GrowBlox GreenShelter deployment, indicator plants are selected at statistically representative positions within each growing zone. CoFarmer AI uses the indicator plant data to make irrigation decisions that apply across the full zone. Full sensor coverage of every plant is not required and would be economically impractical at scale.
Yes. The Syntheflora analytics infrastructure exports structured data to ERP and LIMS systems via standard data formats, enabling integration with existing business management and quality management systems. For Vertical Green Farming Bio-Mimetic CEA™ deployments, Syntheflora integrates natively with CoFarmer AI — which uses the real-time plant physiological data to manage irrigation events, flag anomalies, and maintain crop recipe compliance across multiple independent growing zones simultaneously.
El retorno se captura por dos canales: reducción de costos de agua (40%) y mejora de calidad.