Results 141 to 150 of about 521,689 (245)

UAV‐based deep transfer learning to improve grain yield prediction in winter wheat across temporal and spatial variability

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Accurate prediction of grain yield (GY) remains a major challenge in plant breeding due to complex interactions between genotype, environment, and management (G × E × M) factors. Remote sensing data from unmanned aerial vehicles (UAVs) equipped with multispectral sensors have emerged as a pivotal resource for high‐throughput phenotyping.
Swas Kaushal, Mohammad Maruf Billah, Mandeep Singh, Dante Koupal, Pradeep Raj Sitaula, Jyotirmoy Halder, Jagdeep Sidhu, Maitiniyazi Maimaitijiang, Sunish K. Sehgal   +8 more
wiley   +1 more source

Sources of uncertainty in vicarious calibration: understanding calibration target reflectance

, 2003
A field experiment investigated the hypothesis that the nadir reflectance of calibration surface substrates (asphalt and concrete) remains stable over a range of time-scales.
Milton, E.J., Anderson, K., Rollin, E.M.
core   +1 more source

Data Processing and Quality Control of the CW193 Sun Photometer Network and Evaluation of Satellite Aerosol Products

Remote Sensing
Reliable ground-based aerosol observations are essential for evaluating satellite aerosol products across heterogeneous surfaces and aerosol regimes.
Miao Song, Xiuqing Hu, Jibiao Zhu, Yupeng Wang, Li Li, Yidan Si, Tianlei Yu, Lin Chen, Na Xu, Xiangang Zhao, Peng Zhang   +10 more
doaj   +1 more source

Bayesian optimized color filter: A fast method for segmentation of plant phenotypes from 3D point cloud images

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Multispectral three‐dimensional (3D) imaging offers substantial potential for plant phenotyping, yet manual segmentation of plant organs remains a bottleneck in breeding programs. We developed a color‐based filtering workflow for faba bean (Vicia faba L.) point clouds that optimizes lower and upper thresholds of spectral indices and broadband ...
Lennart Scheer, Benjamin Wittkop, Andreas Stahl, Olaf Sass, Gregor Welna, Hanna Tietgen, Rod J. Snowdon   +6 more
wiley   +1 more source

Canola yield prediction and genotype selection using uncrewed aerial system multispectral imagery and machine learning models

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Evaluation and selection of canola breeding lines across multiple years and locations are vital for variety development. However, accurately measuring canola (Brassica napus L.) yield under field conditions is challenging due to end‐of‐season events such as rain, windstorms, and hail, as well as variability in plant maturity and pod shattering.
Mohammad Jony, Cristhian Perdigon, Md Fahad Hasan, Paulo Flores, Mukhlesur Rahman   +4 more
wiley   +1 more source

A new methodology for in-flight radiometric calibration of the MIVIS imaging sensor

, 2006
Sensor radiometric calibration is of great importance in computing physical values of radiance of the investigated targets, but often airborne scanners are not equipped with any in-flight radiometric calibration facility.
Lechi, G., Gianinetto, M.
core   +1 more source

High‐throughput assessment of plant stand establishment, seedling vigor, and light interception in peanut using UAV‐based RGB and multispectral imagery

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract In peanut (Arachis hypogaea L.), plant stand establishment, seedling vigor, and canopy growth are key determinants of crop performance; yet traditional ground‐based assessment methods can be destructive, labor‐intensive, and limited in throughput.
Ved Parkash, Jessie H. Adams, Javier Rodriguez‐Sanchez, John L. Snider, Phillip L. Vines, Brian M. Schwartz, Nino Brown   +6 more
wiley   +1 more source

Evaluation of uncrewed aerial system‐derived vegetation indices for forage trait phenomic prediction in oat–pea intercrop breeding trials

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Accelerating genetic gain in intercrop forage breeding requires scalable phenotyping approaches that can capture both yield and quality variation across complex genotype combinations. This study evaluated the use of uncrewed aerial system (UAS)‐derived multispectral vegetation indices (VIs) for predicting forage yield and nutritive quality in ...
Milcah Kigoni, Raysa Gevartosky, Lucas B. Munaro, Tim Mies, Luis Gehrke, Jessica Rutkoski, Juan David Arbelaez   +6 more
wiley   +1 more source

Radar Instrument Calibration of TerraSAR-X [PDF]

, 2008
TerraSAR-X is a high resolution synthetic aperture radar (SAR) satellite launched in 2007. Its active phased array X-Band antenna hosts 384 transmit/receive modules (TRMs) controlling the beam steering in azimuth and eleva-tion.
Benjamin Bräutigam, Hueso González, Jaime, Markus Bachmann, Jaime Hueso González, Schwerdt, Marco, Bachmann, Markus, Bräutigam, Benjamin, Marco Schwerdt   +7 more
core  

Genomic and phenomic prediction models improve selection accuracy for complex traits in alfalfa

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Predictive breeding has been proposed as an effective approach to accelerate genetic gain for complex traits. Genomic prediction (GP) models have been developed in alfalfa (Medicago sativa L.) for key traits in the last decade. More recently, phenomic prediction (PP) models have been proposed as a low‐cost, high‐throughput alternative to GP in
Pablo Sipowicz, Ayush K. Sharma, Mario H. Andrade, Claudio C. Fernandes Filho, L. Felipe V. Ferrão, Aditya Singh, Anju Biswas, Charlie Messina, Esteban Rios   +8 more
wiley   +1 more source