Product overview
8 in 1 soil sensor is a set of environmental parameters detection in one of the intelligent agricultural equipment, real-time monitoring of soil temperature, humidity, conductivity (EC value), pH value, nitrogen (N), phosphorus (P), potassium (K) content, salt and other key indicators, suitable for smart agriculture, precision planting, environmental monitoring and other fields. Its highly integrated design solves the pain points of traditional single sensor requiring multi-device deployment and greatly reduces the cost of data acquisition.
Detailed explanation of technical principles and parameters
Soil moisture
Principle: Based on the dielectric constant method (FDR/TDR technology), the water content is calculated by the propagation speed of electromagnetic waves in the soil.
Range: 0~100% Volumetric Water Content (VWC), accuracy ±3%.
Soil temperature
Principle: High precision thermistor or digital temperature chip (such as DS18B20).
Range: -40℃~80℃, accuracy ±0.5℃.
Electrical conductivity (EC value)
Principle: The double electrode method measures the ion concentration of soil solution to reflect the salt and nutrient content.
Range: 0~20 mS/cm, resolution 0.01 mS/cm.
pH value
Principle: Glass electrode method to detect soil pH.
Range: pH 3~9, accuracy ± 0.2pH.
Nitrogen, phosphorus and potassium (NPK)
Principle: Spectral reflection or ion selective electrode (ISE) technology, based on specific wavelengths of light absorption or ion concentration to calculate the nutrient content.
Range: N (0-500 ppm), P (0-200 ppm), K (0-1000 ppm).
salinity
Principle: Measured by EC value conversion or special salt sensor.
Range: 0 to 10 dS/m (adjustable).
Core advantage
Multi-parameter integration: A single device replaces multiple sensors, reducing cabling complexity and maintenance costs.
High precision and stability: Industrial grade protection (IP68), corrosion resistant electrode, suitable for long-term field deployment.
Low-power design: Support solar power supply, with LoRa/NB-IoT wireless transmission, endurance of more than 2 years.
Data fusion analysis: Support cloud platform access, can combine meteorological data to generate irrigation/fertilization recommendations.
Typical application case
Case 1: Smart farm precision irrigation
Scene: A large wheat planting base.
Applications:
Sensors monitor soil moisture and salinity in real time, and automatically trigger the drip irrigation system and push fertilizer recommendations when humidity falls below a threshold (such as 25%) and salinity is too high.
Results: 30% water saving, 15% increase in yield, salinization problem alleviated.
Case 2: Greenhouse water and fertilizer integration
Scene: Tomato soilless cultivation greenhouse.
Applications:
Through EC value and NPK data, the ratio of nutrient solution was dynamically regulated, and the photosynthetic conditions were optimized with temperature and humidity monitoring.
Results: Fertilizer utilization rate increased by 40%, fruit sugar content increased by 20%.
Case 3: Intelligent maintenance of urban greening
Scene: Municipal park lawn and trees.
Applications:
Monitor soil pH and nutrients and link sprinkler systems to prevent root rot caused by overwatering.
Results: The cost of afforestation maintenance is reduced by 25%, and the plant survival rate is 98%.
Case 4: Desertification control monitoring
Scene: Ecological restoration project in arid area of northwest China.
Applications:
The changes of soil moisture and salinity were tracked for a long time, the sand-fixing effect of vegetation was evaluated, and the replanting strategy was guided.
Data: Soil organic matter content increased from 0.3% to 1.2% in 3 years.
Deployment and implementation recommendations
Installation depth: Adjusted according to crop root distribution (such as 10~20cm for shallow root vegetables, 30~50cm for fruit trees).
Calibration maintenance: pH/EC sensors need to be calibrated with standard liquid every month; Clean electrodes regularly to avoid fouling.
Data platform: It is recommended to use Alibaba Cloud IoT or ThingsBoard platform to realize multi-node data visualization.
Future trend
AI prediction: Combine machine learning models to predict the risk of soil degradation or the cycle of crop fertilization.
Blockchain traceability: Sensor data is linked to provide a credible basis for organic agricultural product certification.
Shopping guide
Agricultural users: Preferentially choose a strong anti-interference EC/pH sensor with a localized data analysis App.
Research institutions: Select high-precision models that support RS485/SDI-12 interfaces and are compatible with laboratory equipment.
Through multi-dimensional data fusion, the 8-in-1 soil sensor is reshaping the decision-making model of agricultural and environmental management, becoming the “soil stethoscope” of the digital agro-ecosystem.
Post time: Feb-10-2025