Results 191 to 200 of about 36,270 (292)

Decoding stress resilience in soybean: Regulatory networks and precision breeding under climate change

Journal of Integrative Plant Biology, EarlyView.
This review covers recent progress in the understanding of stress‐responsive regulatory networks in soybean and highlights emerging genomic and breeding strategies. Integrating molecular insights and precision breeding will help to accelerate the development of climate‐resilient soybean cultivars.
Ali Shahzad, Monan Sun, Shuangkang Pei, Xiaoyu Liu, Yinhe Zhang, Keheng Xu, Hongtao Gao, Yonggang Zhou, Haiyan Li   +8 more
wiley   +1 more source

Brain tissue classification in hyperspectral images using multistage diffusion features and transformer

Journal of Microscopy, EarlyView.
Abstract Brain surgery is a widely practised and effective treatment for brain tumours, but accurately identifying and classifying tumour boundaries is crucial to maximise resection and avoid neurological complications. This precision in classification is essential for guiding surgical decisions and subsequent treatment planning.
Neetu Sigger, Tuan T. Nguyen, Gianluca Tozzi   +2 more
wiley   +1 more source

Hierarchical Spatial-Spectral Feature Extraction with Long Short Term Memory (LSTM) for Mineral Identification Using Hyperspectral Imagery. [PDF]

Sensors (Basel), 2020
Zhao H, Deng K, Li N, Wang Z, Wei W.
europepmc   +1 more source

When biology meets materials science – Interdisciplinary applications of electron microscopy

Journal of Microscopy, EarlyView.
Abstract Research at the interface between biology and materials science creates challenges for electron microscopists. Everything from the sample preparation to the choice of imaging and analytical techniques and the interpretation of the resulting data refuses to sit comfortably within the domain of one discipline or the other.
Martin Saunders, Peta L. Clode, Enoch V. S. Wong, Anna‐Lee Jessop, Gerd E. Shröder‐Turk, Felix de Tombeur   +5 more
wiley   +1 more source

Sparse Feature Learning of Hyperspectral Imagery via Multiobjective-Based Extreme Learning Machine. [PDF]

Sensors (Basel), 2020
Fang X, Cai Y, Cai Z, Jiang X, Chen Z.
europepmc   +1 more source

Hyperspectral tomographic diffractive microscopy: Development and applications

Journal of Microscopy, EarlyView.
Abstract Tomographic Diffractive Microscopy (TDM) provides label‐free three‐dimensional imaging of transparent samples with resolution surpassing confocal limits. At IRIMAS, successive instrumental developments since 2009 have enhanced TDM capabilities through transmission, reflection, isotropic, polarisation‐sensitive, and dual‐view configurations ...
Leonardo Pestana Legori, Carlos Alberto Chacón Ávila, Matthieu Debailleul, Nicolas Verrier, Olivier Haeberlé   +4 more
wiley   +1 more source

Bridging data silos to holistically model plant macrophenology

New Phytologist, EarlyView.
Summary Phenological response to global climate change can impact ecosystem functions. There are various data sources from which spatiotemporal and taxonomic phenological data may be obtained: mobilized herbaria, community science initiatives, observatory networks, and remote sensing.
Lizbeth G. Amador, Tadeo H. Ramirez‐Parada, Isaac W. Park, Susan J. Mazer, Aaron M. Ellison, Margaret O'Brien, Eric R. Sokol, Colin A. Smith, Charles C. Davis, Sydne Record   +9 more
wiley   +1 more source

Prediction of End-Of-Season Tuber Yield and Tuber Set in Potatoes Using In-Season UAV-Based Hyperspectral Imagery and Machine Learning. [PDF]

Sensors (Basel), 2020
Sun C, Feng L, Zhang Z, Ma Y, Crosby T, Naber M, Wang Y.   +6 more
europepmc   +1 more source

Using reflectance spectra and Pl@ntNet to identify herbarium specimens: a case study with Lithocarpus

New Phytologist, EarlyView.
Summary The digitisation of plant collections is bringing large quantities of information into accessible electronic databases. However, in recent decades, traditional taxonomic work in collections has declined, meaning that more specimens are only determined to family or genus, particularly when lacking key identification structures.
Barbara M. Neto‐Bradley, Pierre Bonnet, Hervé Goëau, Alexis Joly, Jeannine Cavender‐Bares, David A. Coomes   +5 more
wiley   +1 more source

Observing the invisible: X‐ray CT for plant–microbe interactions

New Phytologist, EarlyView.
Utility of X‐ray computed tomography (X‐ray CT) for visualising belowground plant interactions between multiple spatial scales and focal planes. Summary Plant–microbe interactions are inherently spatial, yet the physical structure of the soil and rhizosphere is rarely treated as a mechanistic variable in experimental design.
Eric C. Pereira, Chris A. Bell
wiley   +1 more source