Results 171 to 180 of about 4,953 (252)

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

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

Phenology-Dependent Sex Identification in Mature <i>Ginkgo biloba</i> Using Hyperspectral Imaging. [PDF]

Plants (Basel)
Zhao Z, Zhang J, Wang T, Liu S, Yi Z, Wang X, Chen X, Sun Q, Sun H.   +8 more
europepmc   +1 more source

Determination of dry bean physiological maturity from UAS RGB time series using a stacking ensemble of color‐derived spectral features

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Evaluating physiological maturity is an important trait in dry bean breeding (Phaseolus vulgaris L.), but field scoring can be inaccurate, subjective, and a persistent bottleneck in multi‐environment trials. To address this, we developed a low‐cost, high‐throughput pipeline that predicts plot‐level days after planting at maturity from time ...
Aliasghar Bazrafkan, Lovepreet Singh, John Hawkins, Evan M. Wright, Valerio Hoyos‐Villegas   +4 more
wiley   +1 more source

Integrating hyperspectral features and physiological parameters for quantitative estimation of fig rust severity. [PDF]

Front Plant Sci
Li Y, Chen X, Din Y, Liu H, Wang Y, Cao B, Fang X, Wang Y, Zhang Z.   +8 more
europepmc   +1 more source

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

Coupling critical nitrogen dilution curve with hyperspectral feature optimization and machine learning for inversion of nitrogen nutrition index in greenhouse cucumber. [PDF]

Front Plant Sci
Zhao T, Li J, Hu C, Zhang D, Zhang G, Xu Y, Xiu W.   +6 more
europepmc   +1 more source

Early‐life stage phenomic prediction of field agronomic traits across breeding cycles in intermediate wheatgrass

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Perennial grains represent a promising frontier for sustainable agriculture, but breeding progress is constrained by the accessibility of genotyping and the difficulty of evaluating complex traits expressed for multiple years after establishment across heterogeneous environments.
Zachary N. Harris, Jackson Braley, Eric Cassetta, Jared Crain, Lee DeHaan, David Van Tassel, Allison Miller, Matthew J. Rubin   +7 more
wiley   +1 more source

Wave frequency selection method for hyperspectral hyperspectral remote sensing image based on SSGIE-KFCM algorithm. [PDF]

PLoS One
He D, Ning C, Li H.
europepmc   +1 more source