A couple of years ago, I had a chance to contribute to a book on automation in tree fruit production. I carried out an in-depth review of precision sensor technologies for pest and disease monitoring. Considering the fact that this is an area of active research and development for DurUntash Lab, in a series of blog articles, I’ll be sharing parts of my original drafts before it was modified to become part of the book. The following paragraphs summarize what is to come.
Pest management in the absence of a proper monitoring method usually leads to an excessive use of pesticides. Scouting is currently the main approach for monitoring health in trees. Conventional methods for monitoring pests and disease are costly, labor-intensive, and time-consuming. Scientific pests and disease management could alleviate these challenges by providing techniques that enable the continuous monitoring of insects’ activity and health issues in tree crops.
Emerging technologies such as pheromone-baited insect traps (smart traps) integrated into WSNs and advanced microclimatic monitoring systems with high spatial and temporal resolution have opened up new doors to an era of automatic pest monitoring. Advanced platforms for detecting crop diseases such as space-based satellite imagery, airborne remote sensing, ground-based sensor systems and a broad range of non-invasive radiometric-based sensors are available today.
Other pest monitoring techniques such as biosensors (electronic tongue), imaging and spectroscopy, and VOC profiling (electronic nose) are currently in development. There is a need for large-scale real-time plant disease detection tools that, under field conditions, are rapid, cost-effective, specific to a particular disease, and sensitive for detection at the early onset of the symptoms.
More research needs to be devoted to advanced general and image processing algorithms for the discrimination of concurrent diseases and other plant stresses. Besides algorithms and sensing techniques, current research in insects and disease monitoring also include electronic applications for smartphones, web-based decision support systems integrated with WSN systems and sensor integration with autonomous vehicles and robots that monitor and control other aspects of crop and soil management as well.