Optimizing Medicinal Plant Cultivation: A Case Study on Shishir Tulsi in a Controlled Glasshouse Environment
CSIR- CIMAP
UN SDG 12 - Responsible Consumption and Production
Lucknow, Uttar Pradesh
Pain Points
Researchers struggled to control variables due to inconsistent moisture data and labor-intensive irrigation.
Manual Irrigation Complexity
Watering in milliliters (ml) manually for each plant was labor-intensive and prone to variation.
Lack of Temperature Stability
Maintaining precise ambient and root-zone temperatures was critical for controlled study.
Inconsistent Moisture Levels
Difficulty in varying soil moisture accurately across test groups for behavioural research.
Our Offerings
We enabled automated irrigation using real-time soil moisture data, cutting manual effort and ensuring uniform conditions.
Soil & moisture Sensors
Deployed sensors for EC, temperature, and moisture to monitor root-zone conditions.
Automated Irrigation in ml
Enabled automatic ml-level irrigation based on configurable moisture and temperature limits.
Indoor Ambience Sensing
Provided ambient air sensing for light, humidity, and room temperature within the glasshouse.
thingZmate® Data Platform
Live data access for researchers to analyze soil-climate-plant interaction with custom irrigation cycles.
Outcomes
High Precision Plant Study
Enabled study of Mentha arvensis at varied temperature, EC, and moisture levels with consistent control.
Reduced Manual Labor
Irrigation in ml was automated, eliminating human error and effort in watering routines.
Controlled Environment Maintained
Glasshouse ambience maintained accurately for plant response tracking in pilot trials.
Pilot Validated for Scale
Pilot success confirmed feasibility of precision climate-agronomy for larger greenhouse deployments.
Our research now runs hands-free with complete control over plant variables.
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