Results 161 to 170 of about 16,752 (252)

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

open access: yesThe 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   +9 more
wiley   +1 more source

Unmanned aerial vehicle–based spatiotemporal phenotyping and growth modeling for forecasting potato yield

open access: yesThe Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Monitoring spatial variations in plant growth and forecasting yield before harvest provides valuable insights for optimizing agronomic decision‐making in potato (Solanum tuberosum L.) cultivation. Although unmanned aerial vehicle (UAV)‐based remote sensing has recently enabled the development of tuber fresh weight (TW) estimation models, their
Yuto Imachi   +7 more
wiley   +1 more source

Satellite-based drought assessment in major Sudan's mechanized rain-fed agriculture. [PDF]

open access: yesSci Rep
Adam AA   +12 more
europepmc   +1 more source

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

open access: yesThe 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   +7 more
wiley   +1 more source

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

open access: yesThe 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   +2 more
wiley   +1 more source

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

open access: yesThe 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   +5 more
wiley   +1 more source

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