Meru University student Alex Kimuya explains how the pest and disease detection system works.
PHOTO | PHOEBE OKALL
In most cases, farmers discover disease and pest infestations too late to save the situation while others apply the wrong intervention.
Based on these challenges, students at the Meru University of Science and Technology have developed an automated pest and disease detector that gives real-time information to the farmer.
The system comprises of raspberry pi cameras that are linked to a computer programme designed capture images of the crops every 15 minutes before they are processed and information is transmitted through a Global System for Mobile (GSM) communication unit.
Alex Kimuya, a physics student, James Kariuki, a computer science student and Samuel Ntongai, a technician at the institution say the device identifies crop stress, process the information and notify a farmer through SMS.
He says they have tested the device on a tomato garden where it effectively helped to identify bacterial wilt disease.
“The system comprises a camera that captures images of the crops in the field periodically. The system can identify crop stress due to pest and diseases once the images are processed. When the system discovers changes in the crops, it automatically communicates to the farmer through SMS,” he explains.
Mr Kinyua says they are currently modifying the system to detect various diseases that mostly affect high value horticultural crops. “Besides disease and pest monitoring, the system can alert the farmer when to apply certain chemicals such as at flowering stage and the harvesting time,” he says.
Felix Muthamia, an agricultural supervisor at the institution, says the innovation could help cut cost on labour and chemical use in farming.
“Most farmers end up spending a lot of money on chemicals due to late detection of disease or pest,” he says.
“Besides, it will help in record keeping that largely lacks among many farmers. The system can also be used for surveillance in the farm.”
Meru University assistant lecturer Daniel Maitethia says they are currently improving the system’s efficiency.
“The university has committed Sh500,000 for the improvement of the system. We want to train it to detect as many diseases as possible. We also intend to approach the National Commission for Science Technology and Innovation to take the innovation further,” he said.
Besides the automated pest and disease detector, the lecturer has also developed an automatic irrigation system that turns water on and off based on moisture content in the soil.