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 and planning throughout the year, such as crop selection, rotation and understanding conditions conducive to pest and disease pressure.
The key steps to successful Integrated Pest Management are:
Identify and monitor disease
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 as well as the presence of pests and disease.
NDVI (Normalised Difference Vegetation Index) used to assess plant health alongside other analytical tools that are used to predict yields. Once a threshold of plant health and predicted yield is passed, the implementation of pest management strategies can be decided.
Mapping tools to determine a more timely and variable rate of application of chemicals.