Our study demonstrates the effectiveness of hyperspectral imaging combined with machine learning for identifying and classifying parasitic Cuscuta species. The findings highlight the potential of this approach for rapid, non-destructive field diagnostics and precision agriculture applications. As imaging hardware continues to improve and become more affordable, such integrated systems could be deployed in real-world crop monitoring and management to mitigate the impact of parasitic plants on global food production.

Vasili A. Balios, Samuel Ortega, Karsten Heia, Anna Avetisyan, Kirsten Krause

https://doi.org/10.1186/s13007-025-01498-y