Results 201 to 210 of about 7,082,475 (293)

Artificial intelligence‐powered plant phenomics: Progress, challenges, and opportunities

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Artificial intelligence (AI), a key driver of the Fourth Industrial Revolution, is being rapidly integrated into plant phenomics to automate sensing, accelerate data analysis, and support decision‐making in phenomic prediction and genomic selection.
Xu Wang, Daeun Choi, Damian Adams, Jaehyun Ahn, Kelly Balmant, Raquel Dias, Carlos D. Messina, Rafael Muñoz‐Carpena, Vance M. Whitaker, Haipeng Yu, Ziwen Yu, Chang Zhao, Changying Li   +12 more
wiley   +1 more source

Greenness exposure across the cancer continuum: The role of coronary heart disease. [PDF]

Environ Epidemiol
Ashri S, Cohen G, Keinan-Boker L, Itzhaki Ben Zadok O, Shafran I, Broday DM, Steinberg DM, Bental T, Golan L, Moran M, Kornowski R, Gerber Y.   +11 more
europepmc   +1 more source

Multiple ortho‐mosaicking software pipelines produce comparable imagery‐derived wheat phenotypes

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Unmanned aerial systems (UAS) equipped with multispectral and RGB sensors offer valuable data for monitoring crop health and assessing disease severity. However, the wide range of available photogrammetric software complicates software selection for high‐throughput plant phenotyping.
Sanju Shrestha, Phillip D. Alderman, Grishma Ojha, Brett F. Carver   +3 more
wiley   +1 more source

Estimation of Grain Yield and Quality in Awned and Awnless Wheat Genotypes Using UAV and Proximal Multispectral Sensors. [PDF]

Plants (Basel)
Stević IM, Kandić Raftery V, Kostić M, Ljubičić N, Bošković B, Gligorević K, Pajić M, Dražić M.   +7 more
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

Analyzing the spatiotemporal dynamics of land use land cover change and its effects on land surface temperature in Weyib watershed, South Eastern Ethiopia. [PDF]

Sci Rep
Dararo KF, Tiye FS, Geleto DL.
europepmc   +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

Cellular integrity beyond xylem embolism underpins drought tolerance in zoysiagrasses. [PDF]

J Exp Bot
Oliveira LA, Oliveira D, Taggart M, Milla-Lewis SR, Clothier J, Cardoso AA.   +5 more
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

Widespread controls of precipitation sensitivity on drought recovery of global forests. [PDF]

Nat Commun
Hong Y, Petrie MD, Zhang Y, Chen Y, Huang H, Chen H.   +5 more
europepmc   +1 more source