Working together to limit herbicide resistant weeds
EMILI is working with Geco Engineering to assess the performance of their techniques for proactive weed management. Drone and satellite imagery allow us to predict kochia and wild oat populations and detect emerging herbicide resistance.
This project will enable farmers to detect, isolate and control herbicide resistant weeds earlier in-season while they are still young and easier to manage. In the future, digital agriculture technologies such as strategic weed targeting through AI will help limit yield losses and the spread of herbicide resistant weeds. This will increase both production and income for farmers worldwide
Using AI to predict herbicide resistant weed patches
We will be gathering an assortment of weed data with a particular interest in locations with recurring wild oat and kochia weed patches on Innovation Farms. Geco Engineering will use the data we collect to assess the performance of artificial intelligence (AI) in predicting the locations of herbicide resistant weeds. The AI will allow farmers to target specific weed patches, which reduces pesticide applications and promotes environmental health and sustainability while saving time and money.
If weed species are not eradicated early in the season, they can contribute to the weed seed bank in the field and drastically affect crop yields by competing for valuable sunlight, water, and nutrients. An integrated weed management approach combines cultural and chemical practices. The goal is to increase crop competition against weeds by using multiple modes of effective chemical action to limit the introduction or spread of resistant seeds. Preventing the spread of herbicide resistant weeds is critical to avoid further amplifying resistant populations.
