JUST PUBLISHED: AI Runner Recognition in Strawberry Plants

JUST PUBLISHED: "A Two-Step Deep Semantic Segmentation and Object Detection Approach for Runner Recognition in Strawberry Plants" by Mojtaba Ahmadi, Abbas Atefi, Mohammadreza Ramzanpour, and John Lin. Strawberry farming in California faces a costly challenge: removing runners that divert plant resources away from fruit production towards producing daughter plants. Traditionally cut by hand, this labor-intensive task adds up to significant costs for farmers.

In collaboration with the California Strawberry Commission, this study introduces a two-step deep learning framework that combines semantic segmentation and object detection to accurately identify runners in strawberry fields. Successfully tested on three different cultivars, the AI system demonstrated high accuracy in runner recognition. This innovative technology paves the way for autonomous pruning robots, potentially reducing labor costs, increasing efficiency and boosting productivity for strawberry growers.

Read the paper here:
https://www.tandfonline.com/doi/full/10.1080/15538362.2024.2397438