There are a variety of AgTech tools available that allow growers to correctly identify pests, diagnose disease symptoms, and continuously monitor the health of their crops. Tools ranging from sensors and cameras equipped with diagnostic technology, machine learning and AI (Artificial Intelligence) can be used to prepare Integrated Pest Management (IPM) strategies.
The integration of key data from pest and disease management tools forms part of Whole Farm Management Software and aids key decision-making such as crop selection, agrichemical inventory management, MRL (Maximum Residue Limits) compliance, and understanding conditions conducive to pest and disease pressure.
The key steps to successful IPM are:
Identify and monitor disease and pest incursion
Assess economic damage
Implement IPM strategy
Evaluate success of IPM strategy
There are a number of technologies in this area that improve the accuracy and precision of each of these steps:
Sensors and cameras equipped with diagnostic technology use machine learning and AI to assess a plant’s health and monitor disease symptoms. As more data is captured on farm to form a database of information, these technologies will continue to improve in their crop management accuracy and predictability capabilities.
Software systems can predict yield losses and estimate a cost-benefit of taking action against pests and disease versus the underlying cost of control.
Smartphone apps make constructing pest and disease management strategies more simply and user-friendly.
Satellite, drones or robots can capture and evaluate images to determine plant health, presence of pests and disease, flowering and fruit load, as well as predict yields on a plant-by-plant basis.
