Results 211 to 220 of about 91,296 (293)

Non-destructive yield estimation of onion and garlic using UAV-based hyperspectral imaging and hybrid machine learning models. [PDF]

BMC Plant Biol
Su Y, Long J, Chen J, Zhou R, Liu Z, Deng H, Yuan Y.   +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

Hyperspectral Image Classification Based on an Improved Octopus Optimization Algorithm. [PDF]

Biomimetics (Basel)
Xu Y, Jiang L, Zhang 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

Fully Quantized Training vs. Post-Training Quantization for a Small Hyperspectral Transformer Model for Pixel-Level Foreign Plastic Object Classification. [PDF]

Sensors (Basel)
Khan Z, Yoon SC, Bhandarkar SM.
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

Pre-Visual Detection of Pine Wilt Disease Using an Optimized PSRI Derived from Hyperspectral Drone Imagery. [PDF]

Plants (Basel)
Yu R, Weng H, Guo D, Weng M, You Z, Zhang F, Wu S.   +6 more
europepmc   +1 more source

Combining phenomic and genomic selection for pea breeding improvement

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Pea (Pisum sativum L.) is a strategic crop in the development of sustainable agriculture. However, the genetic gain remains limited despite advances in breeding. Genomic selection holds promise to accelerate varietal improvement, but its high implementation cost restricts its use in crops.
Anthony Klein, Virgilio Freitas, Abdou Wade, Grégoire Aubert, Myriam Naudet‐Huart, Michael Touratier, Jennifer Régulier, Jean‐François Herbommez, Catherine Kraut, Guillaume Roullet, Aude Carlier‐Lézie, Nadim Tayeh, Renaud Rincent, Philippe Dufour, Judith Burstin, Gaëtan Touzy   +15 more
wiley   +1 more source

Deciphering the genetic basis of yield components in wheat by integrating hyperspectral-based phenomes. [PDF]

Plant Phenomics
Kunwar S, Babar MA, Ampatzidis Y, Khan N, Acharya JP, McBreen J, Adewale S, Shahi D, Brown-Guedira G.   +8 more
europepmc   +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