Results 241 to 250 of about 1,910,400 (338)

A highly accurate, low‐cost method for detecting and quantifying soybean leaf flipping phenotype during drought stress

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract A genome‐wide association study (GWAS) using digital images was conducted to delineate regions of the genome that govern the leaf flipping quantitative trait in soybean (Glycine max (L.) Merr). However, converting the digital data to numerical scores for downstream analyses was challenging.
Mohammad Anisur Rahaman, Atit Parajuli, Adnan Hossain Khan, Liang Dong, Madan K Bhattacharyya   +4 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

High‐throughput phenotyping for the prediction and quantification of flower‐related traits in sugarcane

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Sugarcane (Saccharum spp.), a C4 plant, is a vital renewable biofuel and sugar source for industries worldwide. However, synchronizing flowering between parental lines often poses challenges for breeders, hindering effective crossbreeding efforts.
Paulo H. da Silva Santos, João R. Vieira Manechini, Carlos Augusto Dias Kanthack Jr., Mauro Alexandre Xavier, Samira Domingues Carlin, Dilermando Perecin, Thiago G. Marconi, Leandro G. Marconi, Elisson Antonio da Costa Romanel, Stephen Derek Jackson, Marcos. G. A. Landell, Luciana R. Pinto   +11 more
wiley   +1 more source

A Hybrid <i>θ</i>*-APF-Q Framework for Energy-Aware Path Planning of Unmanned Surface Vehicles Under Wind and Current. [PDF]

Sensors (Basel)
Sun X, Dong Z, Chen X, Sun L, An Y.
europepmc   +1 more source

Spatial and temporal scales in plant phenotyping for crop water stress assessment: A review

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Water stress is a major limiting factor for crop productivity worldwide, and its impacts are intensifying due to climate variability and increasing water scarcity. This review focuses on the spatial and temporal scales in plant phenotyping as a critical approach to improving crop water‐stress assessment and supporting precision water ...
Daniel Kingsley Cudjoe, Yazhou Sun, Sanai Li, Wenxuan Guo   +3 more
wiley   +1 more source

Insights into biomass accumulation and challenges in grain yield prediction of elite breeding materials using UAV‐based vegetation indices in soft red winter wheat

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract High‐throughput phenotyping (HTP) techniques have brought new opportunities to understand and evaluate key traits in plant breeding programs. Combining multiple measures through time and random regression models permits a more comprehensive understanding of the genetic and environmental effects on trait expression over time. This study aims to
Felipe Sabadin, Amelia Loeb, Francis Reith, Alexis Perry, Sunilda Frias, Demetrius Ragland, Limei Liu, Wynse Brooks, Ranjita Thapa, Julie Hansen, Christopher Pierce, Virginia M. Moore, Gina Brown‐Guedira, Ian Ray, Michael A. Gore, Kelly Robbins, Nicholas Santantonio   +16 more
wiley   +1 more source

An integrated multi-criteria decision-making model for long-term planning of UAVs in disaster management. [PDF]

PLoS One
Bakir ME, Kasimoglu F.
europepmc   +1 more source

Predicting soybean aboveground biomass in the short‐season region of Canada: Integrating vegetative cover and canopy height

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Aboveground biomass (ABM) is a key determinant of soybean (Glycine max [L.] Merr.) yield and can be used to select for stress‐resilient cultivars. The objective of our study was to develop a predictive model describing ABM in short‐season soybean from vegetative cover (VC) and canopy height (CH).
Malcolm J. Morrison, Thomas L. Hotte, A. Claire Gahagan, Nathaniel W. W. Ort, Elroy R. Cober   +4 more
wiley   +1 more source

UAV‐based RGB and multispectral vegetation indices as alternatives to light box‐derived dark green color index for turfgrass color assessment

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Traditionally, turfgrass color has been assessed through visual ratings or light box‐based digital image analysis, methods that are either subjective or labor‐intensive. In this study, we evaluated the potential of unmanned aerial vehicle (UAV)‐based multispectral and red‐green‐blue (RGB) imagery as a high‐throughput alternative for capturing ...
Ved Parkash, Phillip L. Vines, Sameer Khanal, Jing Zhang, Joann Conner, Susana R. Milla‐Lewis, Nino Brown, David Jespersen, Jodi Johnson‐Maynard, Brian M. Schwartz   +9 more
wiley   +1 more source

Structural Vibration Analysis of UAVs Under Ground Engine Test Conditions. [PDF]

Sensors (Basel)
González-Cabrera SI, Camacho-Zamora N, Rojas-Ramirez SR, Gonzalez-Aguilar AM, Vigueras-Zuniga MO, Tejeda-Del-Cueto ME.   +5 more
europepmc   +1 more source