Results 181 to 190 of about 1,432,316 (279)

Phenotype imputation using high‐throughput phenotyping produces a new secondary trait for further selection modeling

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Data from high‐throughput phenotyping (HTP) could be used for phenotype imputation to enhance genomic selection (GS) or gene discovery, but this has not been explored in crop species. Three machine learning models: multiple linear regression (MLR), missForest, and k‐nearest neighbors, were evaluated for grain yield (GY) phenotype imputation in
Raysa Gevartosky, Lucas Berger Munaro, Jessica E. Rutkoski   +2 more
wiley   +1 more source

Rate-distortion trade-off analysis of the power-domain ISAC waveform for the unmanned aerial vehicle. [PDF]

Sci Rep
Li G, Xiao L, Du J, Sun Y, Ni D, Wu Y, Wang J, Guo Y, Lian J, Wu P.   +9 more
europepmc   +1 more source

Multipurpose Unmanned Aerial Vehicle Design

The work contains the analysis of the design methodology of an unmanned aerial vehicle design (AUV), which is able to carry out environmental monitoring, define the location of various objects and targets with high accuracy, map the seats of fire and ...
Urbahs, Aleksandrs, Savkovs, Konstantins, Bulanovs, Vladimirs, Jakovļevs, Aleksandrs, Petrovs, Vladimirs   +4 more
core  

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 payload technology applications in agriculture and other low-altitude scenarios: a review. [PDF]

Front Plant Sci
Yao W, Liu C, Liu Y, Zheng Q, Wang J, Yu H, Chen C, Guo S.   +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

Occupational health, risk factors, and protection among unmanned aerial vehicle operator in the high-altitude region of China: an observational study. [PDF]

Front Public Health
Shu P, Zheng Y, Yan X, Wang P, Li W, Jia H, Yang M.   +6 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

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

Scaling up soybean breeding: Satellite imagery delivers accurate maturity estimation across plot sizes

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Accurate and scalable phenotyping is essential for accelerating genetic gain in soybean (Glycine max (L.) Merr.) breeding programs. Traditional methods for estimating physiological maturity are labor‐intensive and prone to subjectivity, limiting throughput and consistency. This study evaluates the potential of high‐resolution satellite imagery
Anastasios Mazis, Sarah Anderson, Guilherme Simiqueli, Adam Barbeau, Sara Tirado Tolosa, Julien Linares, Nathan Coles   +6 more
wiley   +1 more source