Results 161 to 170 of about 17,773 (259)

Advanced hyperspectral image processing and machine learning approaches for early detection of wheat stem rust. [PDF]

Front Plant Sci
Fedotov A, Eremenko D, Kuznetsova D, Baranova O, Terentev A.   +4 more
europepmc   +1 more source

A Computer Vision‐Based Methodology to Estimate Fruit Colour Diversity in Ornamental Pepper (Capsicum spp.)

Plant Breeding, EarlyView.
ABSTRACT Fruit colour diversity within different ripening stages confers ornamental value for pepper plants. Using images can be helpful in analysing the fruit colour‐related genetic diversity and enable selecting accessions for ornamental purposes by avoiding subjectiveness.
Marcos Bruno da Costa Santos, Raylson de Sá Melo, Victor Eduardo de Carvalho Sousa, Artur Mendes Medeiros, Angela Maria dos Santos Pessoa, Silvokleio da Costa Silva, Antonia Maiara Marques do Nascimento, Priscila Alves Barroso   +7 more
wiley   +1 more source

ELDGG: an end-to-end LiDAR-dynamic-guided GAN for hyperspectral image hierarchical reconstruction and classification. [PDF]

Sci Rep
Zhang X, Chen M, Li S, Hu X, Duan Z, Luo Y, Xie C, Xiong X.   +7 more
europepmc   +1 more source

Enhancing Predictive Ability of Agronomic and Quality Traits in Ethiopian Malting Barley (Hordeum vulgare L.) Using Spectral Variable Selection Methods

Plant Breeding, EarlyView.
ABSTRACT Phenomic selection (PS) offers a cost‐effective, breeder‐friendly approach for public breeding programmes with limited access to genotyping or restricted financial resources for laboratory infrastructure. Since PS relies on high‐throughput phenotyping data, which is often derived from near‐infrared spectroscopy (NIRS) of harvested seeds ...
Tigist Tadesse, Peer Wilde, Wondimu Ejerso, Dorothea Borchardt, Patrick Thorwarth, Thomas Miedaner   +5 more
wiley   +1 more source

Hyperspectral Image Denoising via Quasi-Recursive Spectral Attention and Cross-Layer Feature Fusion. [PDF]

Sensors (Basel)
Xiao Y, Zhou H, Li W, Yang L, Wang K.
europepmc   +1 more source

FieldDino: Rapid In‐Field Stomatal Anatomy and Physiology Phenotyping

Plant, Cell &Environment, EarlyView.
ABSTRACT Stomatal anatomy and physiology define CO2 availability for photosynthesis and regulate plant water use. Despite being key drivers of yield and dynamic responsiveness to abiotic stresses, conventional measurement techniques of stomatal traits are laborious and slow, limiting adoption in plant breeding.
Edward Chaplin, Guy Coleman, Andrew Merchant, William Salter   +3 more
wiley   +1 more source

Cross-range self-attention single hyperspectral image super-resolution method based on U-Net architecture. [PDF]

Sci Rep
Wang H, Zheng W, Huo L, Zhang K, Yang T, Li P.   +5 more
europepmc   +1 more source

Robustness of high‐throughput prediction of leaf ecophysiological traits using near infrared spectroscopy and poro‐fluorometry

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Water scarcity is a major threat to crop production and quality. Improving drought tolerance through variety selection requires a deeper understanding of plant ecophysiological responses, but large‐scale phenotyping remains a bottleneck. This study assessed the potential of high‐throughput tools (spectroscopy and poro‐fluorometry) to predict ...
Eva Coindre, Romain Boulord, Laurine Chir, Virgilio Freitas, Maxime Ryckewaert, Thomas Laisné, Virginie Bouckenooghe, Maëlle Lis, Llorenç Cabrera‐Bosquet, Agnès Doligez, Thierry Simonneau, Benoît Pallas, Aude Coupel‐Ledru, Vincent Segura   +13 more
wiley   +1 more source

Progressive multi-scale multi-attention fusion for hyperspectral image classification. [PDF]

Sci Rep
Wang H, Quan S, Liu J, Xiao H, Peng Y, Wang Z, Li H.   +6 more
europepmc   +1 more source

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