Results 141 to 150 of about 16,742 (260)

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

Hyperspectral image and chemometrics. A step beyond classical spectroscopic PAT tools. [PDF]

Anal Bioanal Chem
de Juan A, de Oliveira RR.
europepmc   +1 more source

Assessing functional diversity and composition using multispectral images in Atlantic Forest restoration sites

Restoration Ecology, EarlyView.
Abstract Introduction By focusing on the specific functional traits of species, we can better understand how ecosystems function and respond to environmental change. However, field measurements of functional traits can be time‐consuming and costly, whereas remote sensing data can serve as viable alternatives for studying biodiversity at larger scales ...
Júlia Ayres de Oliveira, Ângelo Mantovani Amorim de Freitas Oliveira, André Quintão de Almeida, Catherine Torres de Almeida, Eric Bastos Gorgens, Vinicius Nunes Henrique Silva, Luiz Fernando Duarte de Moraes, Gustavo Bastos Lyra, Jerônimo Boelsums Barreto Sansevero   +8 more
wiley   +1 more source

SGFNet: Redundancy-Reduced Spectral-Spatial Fusion Network for Hyperspectral Image Classification. [PDF]

Entropy (Basel)
Wang B, Cao C, Kong D.
europepmc   +1 more source

Hyperspectral image denoising

, 2020
Šiame darbe analizavome hiperspektrinius vaizdus, hiperspektrinias vaizdavimo technologijas ir triukšmo kilmę hiperspektriniuose vaizduose. Mes ištyrėme ir įgyvendinome kelis HSI triukšmo vertinimo metodus: koreliacijos koeficientų suradimo metodikas (R1 ir R2) ir tiesinės regresijos metodikas (LMLSD ir SSDC).
openaire   +1 more source

Viable but Nonculturable State, a Survival Strategy for Salmonella in Aquatic Environments

Water and Environment Journal, EarlyView.
Transition of Salmonella from a culturable state to a viable but nonculturable state under various environmental stresses and current methods for detecting viable Salmonella in environmental samples. ABSTRACT In the relentless battle for survival, Salmonella has evolved mechanisms to withstand harsh conditions such as extreme temperatures, fluctuating ...
Sanelisiwe Thinasonke Duze, Musa Marimani, Katlego Mamabolo, Mrudula Patel   +3 more
wiley   +1 more source

Semantic-Aware Co-Parallel Network for Cross-Scene Hyperspectral Image Classification. [PDF]

Sensors (Basel)
Li X, Jin C, Tang Y, Xing K, Yu X.
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

Tri branch attention enhanced 3DUNet for remote sensing based hyperspectral image classification. [PDF]

Sci Rep
Ashraf M, Abbas T, Iqbal S, Sayyed A, Asghar MN, Alaulamie A.   +5 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