Results 211 to 220 of about 36,270 (292)

Affordable Phenomics special topic—Foreword for The Plant Phenome Journal

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract The Affordable Phenomics special topic in The Plant Phenome Journal showcased recent advances that expand the accessibility, cost‐effectiveness, and scalability of plant phenotyping technologies. This collection of 15 articles presented innovative approaches, ranging from low‐cost sensors and open‐source analytical pipelines to artificial ...
Valerio Hoyos‐Villegas, Michael A. Gore   +1 more
wiley   +1 more source

Cross-Category Tea Polyphenols Evaluation Model Based on Feature Fusion of Electronic Nose and Hyperspectral Imagery. [PDF]

Sensors (Basel), 2019
Yang B, Qi L, Wang M, Hussain S, Wang H, Wang B, Ning J.   +6 more
europepmc   +1 more source

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

A Combined Quantitative Evaluation Model for the Capability of Hyperspectral Imagery for Mineral Mapping. [PDF]

Sensors (Basel), 2019
Li N, Huang X, Zhao H, Qiu X, Deng K, Jia G, Li Z, Fairbairn D, Gong X.   +8 more
europepmc   +1 more source

An object-based approach to quantity and quality assessment of heathland habitats in the framework of natura 2000 using hyperspectral airborne ahs images [PDF]

, 2010
Bertels, L., Delalieux, S., Haest, B., Kooistra, L., Mücher, C.A., Scheunders, P., Spanhove, T., Thoonen, G., Vanden Borre, J.   +8 more
core   +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

Variational Pansharpening for Hyperspectral Imagery Constrained by Spectral Shape and Gram⁻Schmidt Transformation. [PDF]

Sensors (Basel), 2018
Huang Z, Chen Q, Chen Q, Liu X.
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

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

Combining UAV-based hyperspectral imagery and machine learning algorithms for soil moisture content monitoring. [PDF]

PeerJ, 2019
Ge X, Wang J, Ding J, Cao X, Zhang Z, Liu J, Li X.   +6 more
europepmc   +1 more source