Results 121 to 130 of about 5,433 (245)

Drone‐based phenotyping of maize for multiple disease resistance and yield in breeding field trials

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Improving selection for multiple disease resistance (MDR) and yield in maize (Zea mays L.) requires high‐throughput, objective phenotyping tools, particularly under field conditions where several foliar diseases co‐occur. We evaluated drone‐based multispectral vegetation indices (VIs) for predicting resistance to northern leaf blight (NLB ...
Danilo E. Moreta, Nina Blahut, Nicholas Kaczmar, Judith M. Kolkman, Gary Bergstrom, Margaret Smith, Michael A. Gore, Rebecca Nelson   +7 more
wiley   +1 more source

UAV‐based deep transfer learning to improve grain yield prediction in winter wheat across temporal and spatial variability

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Accurate prediction of grain yield (GY) remains a major challenge in plant breeding due to complex interactions between genotype, environment, and management (G × E × M) factors. Remote sensing data from unmanned aerial vehicles (UAVs) equipped with multispectral sensors have emerged as a pivotal resource for high‐throughput phenotyping.
Swas Kaushal, Mohammad Maruf Billah, Mandeep Singh, Dante Koupal, Pradeep Raj Sitaula, Jyotirmoy Halder, Jagdeep Sidhu, Maitiniyazi Maimaitijiang, Sunish K. Sehgal   +8 more
wiley   +1 more source

Unmanned Aerial Vehicle Surveillance of Rooftop Aedes Breeding Sites Before Dengue Season - Dongguan City, Guangdong Province, China, 2024-2025. [PDF]

China CDC Wkly
Huang Z, He S, Xu G, Wang W, Li D, Zhong Y, Xie W, Xu L.   +7 more
europepmc   +1 more source

AGIcam: An open‐source Internet of Things–based camera system for automated in‐field phenotyping and yield prediction

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Continuous, high‐frequency monitoring is essential to capture rapid phenological transitions and dynamic crop responses to the environment. However, most phenotyping platforms lack the temporal resolution and automation required for consistent, season‐long trait assessment.
Worasit Sangjan, Nisit Pukrongta, Trevor Buchanan, Arron H. Carter, Michael O. Pumphrey, Sindhuja Sankaran   +5 more
wiley   +1 more source

New frontiers for unmanned aerial vehicles in planetary health research. [PDF]

BMC Glob Public Health
Bramante JT, Tarpenning MS, Woo KE, Chamberlin AJ, Coombe KD, Rosser JI.   +5 more
europepmc   +1 more source

Automatic measurement of rice tiller angle from unmanned aerial vehicle images

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Rice (Oryza sativa L.) tiller angle is an important trait that influences plant architecture, canopy light interception, and yield potential. In this study, we proposed a deep learning‐based pipeline for automated measurement of rice tiller angle and plant base width using unmanned aerial vehicle (UAV) imagery.
Tan‐Hanh Pham, Yubin Yang, Jing Zhang, Sanai Li, Stanley Omar P. B. Samonte, Fugen Dou, Darlene Sanchez, Lloyd T. Wilson, Tanumoy Bera, Jing Wang, Kim‐Doang Nguyen   +10 more
wiley   +1 more source

An Ultralight Launch-and-Recovery System for Tethered Micro Unmanned Aerial Vehicles on Small Unmanned Ground Vehicles. [PDF]

Sensors (Basel)
Liu Y, Shen Z, Xu J, Chen S, Zhang B, Xu S.   +5 more
europepmc   +1 more source

Bayesian optimized color filter: A fast method for segmentation of plant phenotypes from 3D point cloud images

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Multispectral three‐dimensional (3D) imaging offers substantial potential for plant phenotyping, yet manual segmentation of plant organs remains a bottleneck in breeding programs. We developed a color‐based filtering workflow for faba bean (Vicia faba L.) point clouds that optimizes lower and upper thresholds of spectral indices and broadband ...
Lennart Scheer, Benjamin Wittkop, Andreas Stahl, Olaf Sass, Gregor Welna, Hanna Tietgen, Rod J. Snowdon   +6 more
wiley   +1 more source

Research progress on precision orchard yield estimation based on multi-source information perception sensors. [PDF]

Front Plant Sci
Rong Z, Ru Y, Zhang X, Fang S, Zhou H, Jiang X.   +5 more
europepmc   +1 more source

High‐throughput assessment of plant stand establishment, seedling vigor, and light interception in peanut using UAV‐based RGB and multispectral imagery

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract In peanut (Arachis hypogaea L.), plant stand establishment, seedling vigor, and canopy growth are key determinants of crop performance; yet traditional ground‐based assessment methods can be destructive, labor‐intensive, and limited in throughput.
Ved Parkash, Jessie H. Adams, Javier Rodriguez‐Sanchez, John L. Snider, Phillip L. Vines, Brian M. Schwartz, Nino Brown   +6 more
wiley   +1 more source