#Industry News
Non-Invasive Identification and Early Detection of Plant Disease?
Hyperspectral imaging and SPAD measurement for plant health monitoring and disease detection using image processing techniques
The challenges of timely and reliable identification of plant diseases in agriculture is important for early detection and an effective intervention. Conventional methods relying on manual observation and destructive sampling are labour-intensive, time-consuming, and often limited to the late stages of infection, leading to potential yield losses. The growing interest in automated and objective approaches reaches beyond the visible spectrum where newer technologies play a big role: hyperspectral and RGB imaging, machine learning, and high-throughput phenotyping, for non-invasive disease detection.
The adoption of advanced technologies holds promise for improving crop management practices, enabling early disease detection, and facilitating precise resource allocation. Hyperspectral imaging, a cutting-edge technology, captures detailed reflectance information beyond human vision, allowing for the identification of subtle changes in plant growth and the early accumulation of stress indicators like anthocyanin. The Specim IQ, a handheld hyperspectral camera, is introduced as a user-friendly solution, providing simplicity and portability for both lab and field use.
The benefits of hyperspectral imaging relies in its non-destructive nature, early detection capabilities, and the ability to quantify the percentage of affected leaf area.
The Chlorophyl Meter SPAD-502 Plus is also adequate for non-destructive testing of crop health, correlating SPAD readings with chlorophyll concentration for optimizing fertilization.
In conclusion, automated disease identification technologies offer non-invasive, early intervention, and targeted chemical application, reducing environmental impact and improving overall crop health and productivity.
