Cereal plant heads must be identified precisely and effectively in a range of agricultural
applications, including yield estimation, disease detection, and breeding. Traditional …

While point clouds hold promise for measuring the geometrical features of 3D objects, their
application to plants remains problematic. Plants are three dimensional (3D) organisms …

Pruning is a time-consuming and labor-intensive practice for managing of dormant jujube
orchards, in which dormant pruning is still mainly dependent on manual operation …

Accurate rice panicle detection and growth stages recognition are crucial steps in rice field
phenotyping. However, conventional manual characterization of rice panicles is time …

Highlights•A new 3D point-based deep learning architecture for organ segmentation of
plants.•Attention-based modules for aggregation and propagation of features.•Exploiting …

Background Plant architecture can influence crop yield and quality. Manual extraction of
architectural traits is, however, time-consuming, tedious, and error prone. The trait estimation …

Wheat ears in unmanned aerial vehicles (UAV) orthophotos are characterized by occlusion,
small targets, dense distribution, and complex backgrounds. Rapid identification of wheat …

Machine learning (ML) within the edge internet of things (IoT) is instrumental in making
significant shifts in various industrial domains, including smart farming. To increase the …

Accurate and high-throughput plant phenotyping is important for accelerating crop breeding.
Spectral imaging that can acquire both spectral and spatial information of plants related to …

Introduction Nondestructive detection of crop phenotypic traits in the field is very important
for crop breeding. Ground-based mobile platforms equipped with sensors can efficiently and …