Welcome to the Agrobotics Research Lab at ICAR-CTCRI
Pioneering smart farming, crop simulation models, robotics, and IoT for tuber crops and beyond.
About the Lab
Transforming Agriculture Through Automation & Intelligence
The Agrobotics Research Lab at ICAR - Central Tuber Crops Research Institute (ICAR-CTCRI), Thiruvananthapuram, is a hub of technological innovation aimed at modernizing farming practices.
Our mission is to empower farmers, researchers, and agricultural stakeholders with scalable, automated, and intelligent solutions that increase crop yield, reduce manual labor, optimize resource usage, and protect crops from pests and diseases.
Leadership
Meet the Scientist in Charge
Dr. V.S. Santhosh Mithra
Principal Scientist & Head, Agrobotics Research Lab
ICAR - Central Tuber Crops Research Institute
With decades of expertise in agricultural technology, crop modeling, and digital agriculture, Dr. V.S. Santhosh Mithra leads the lab's mission to develop groundbreaking automated, simulation, and robotic tools designed specifically for tropical tuber crops and sustainable farming systems.
eCrop – Smart Precision Agriculture Solution
Our Patented Commercialized Innovation
eCrop is a patented electronic crop advisory and simulation system developed by the Agrobotics Research Lab at ICAR-CTCRI. Built to simulate real-time crop growth, eCrop delivers hyper-local soil and climate insights to enable data-driven precision farming.
Key Features of eCrop:
- Real-time Crop Advisory: Microprocessor-based weather and crop monitoring system that delivers automated, localized farming advice.
- Smart Resource Management: Optimizes irrigation, fertilizer application (NPK monitoring), and plant protection based on field data.
- Field-Tested Reliability: Built to handle varied agro-climatic conditions and enhance yield efficiency.
Commercialization Partners:
- Precision Grow Pvt. Ltd.: Manufacturing and commercial scale-up of eCrop hardware solutions.
- AgriPilot: Scaling AI-driven digital platform integration and farm management services. Learn more at AgriPilot.ai.
Crop Simulation & Modeling
Digital Twin & Crop Growth Simulation Models
Our lab specializes in developing mathematical and physiological crop simulation models tailored for tropical tuber and spice crops. These dynamic computer models simulate plant growth processes—such as photosynthesis, biomass accumulation, water uptake, and nutrient response—under changing weather and soil conditions.
Supported Crop Models:
| Crop | What we model |
|---|---|
| Cassava Manihot esculenta | Canopy expansion, root tuberization, and drought response to forecast yield and optimize harvest timelines. |
| Sweet Potato Ipomoea batatas | Crop development stages, vine growth vs. storage root accumulation, and nutrient uptake efficiency. |
| Elephant Foot Yam Amorphophallus paeoniifolius | Corm growth dynamics, canopy duration, and irrigation requirements for maximum yield. |
| Ginger Zingiber officinale | Rhizome development, soil moisture sensitivity, and micro-climate responses for yield prediction. |
Applications of Our Models:
- Yield Forecasting: Predict regional and field-level harvest yields ahead of time.
- Climate Change Impact Analysis: Assess crop performance under elevated temperatures and altered rainfall patterns.
- Precision Advisory Integration: Power digital decision-support platforms (like eCrop) with automated fertilization and irrigation schedules.
Ongoing Research & Projects
We are actively developing future-ready technologies to address pressing agricultural challenges:
1. Automated Cassava Mosaic Disease (CMD) Detection
The Challenge: Cassava Mosaic Disease (CMD) causes devastating yield losses in cassava crops.
Our Solution: Developing AI/ML-powered vision systems and automated sensor setups for early-stage, non-destructive detection of CMD in field conditions, enabling rapid intervention and disease control.
2. Smart Nutri-Garden
The Challenge: Ensuring household nutritional security with minimal manual effort and urban/semi-urban space constraints.
Our Solution: An automated, IoT-driven Smart Nutri-Garden system that manages irrigation, nutrient delivery, and environmental monitoring automatically to promote effortless crop cultivation at home.
3. Robotic Solutions for Weed Removal
The Challenge: High labor costs and hazardous chemical weedicides in tuber crop cultivation.
Our Solution: Autonomous field robotics equipped with computer vision to identify, target, and mechanically remove weeds without damaging main crops, promoting sustainable and organic farming.
Facilities & Capabilities
- Crop Modeling & Simulation Station: Computing infrastructure for crop simulation execution, data assimilation, and climate scenario testing.
- AI & Computer Vision Lab: Image processing and deep learning setups for crop disease diagnostics and weed identification.
- IoT & Embedded Systems Bench: Hardware prototyping for smart field sensors, automated irrigation controllers, and data loggers.
