Protecting tea plants from devastating diseases is crucial for maintaining yield and quality. This study utilized ECDet and MobileNetv3 networks to detect and assess the severity of tea leaf blight by using remote sensing images captured by an unmanned aerial vehicle. The proposed method achieved an impressive detection precision and high accuracy in assessing leaf damage severity, offering a promising and efficient solution with broader implications for improved disease management in tea production.

This study assessed haploid induction and doubled-haploid (DH) formation efficiency through inter-generic hybridisation, by using maize and Imperata cylindrica across hexaploid and tetraploid wheat varieties, and wheat × rye derivatives (BC₁F₃). I. cylindrica proved to be a more effective pollen source than maize in producing DHs in hexaploid wheat and exhibited at par seed setting frequency of first-generation DHs with the parental lines. These results highlighted the role of I. cylindrica in facilitating efficient and reliable DH production in wheat.