In cotton processing, computer vision models based on YOLOv5—a type of AI capable of distinguishing objects in images and videos in real time—are already achieving up to 95% accuracy in identifying contaminants, such as leaves and other impurities.  

During this process, the fibres pass through cameras installed on the processing lines, which capture images at high speed. These images are sent to a computer, where the model analyses each frame and automatically identifies impurities.

Based on this detection, automated systems can separate clean material from contaminated material, ensuring greater purity and uniformity of the product. Not surprisingly, industries that have adopted this type of intelligent sorting have recorded increases of up to 30% in productivity and a reduction in losses. 

In a market that rewards quality, including in the context of exports, the ability to automatically classify batches by variables such as fibre thickness and strength allows for higher prices. The system objectively proves the quality of the product, allowing superior batches to be directed to buyers willing to pay more.

With the use of these tools, Brazilian agribusiness will be able to take new leaps in productivity. It is worth remembering that AI is already part of the daily routine of the most profitable farms—and should reach more rural producers.