Results 181 to 190 of about 101,587 (311)

A Red Triploid Seedless Grape ‘Red Dream’

HortScience, 2022
Young-Sik Park, Je-Chang Lee, Haet-Nim Jeong, Nam-Yong Um, Jae-Yun Heo   +4 more
doaj   +1 more source

Effects of Temperature on Growth, Pathogenicity, and Fungicide Sensitivity of Two <i>Coniella</i> Species Causing Grape White Rot. [PDF]

J Fungi (Basel)
Yuan L, Liu B, Li T, Yin X, Liu Q, Jiang X, Han X, Wang C, Ji T, Li N, Wei Y.   +10 more
europepmc   +1 more source

Seed Storage Conditions for Zostera muelleri Restoration: Effects of Temperature, Salinity and Sterilisation on Seed Contamination, Viability and Seedling Emergence

New Zealand Journal of Marine and Freshwater Research, Volume 60, Issue 4, December 2026.
The decline of seagrass meadows is a continuing global concern, and seed‐based restoration provides a scalable approach to recovering lost and degraded meadows. Such approaches require large quantities of seed to be collected, processed, and often stored for months until deployment.
Kelsie J. Fractal, Jeffrey T. Wright, Madeline E. Green, Elizabeth L. Andrews, M. A. Strain Elisabeth   +4 more
wiley   +1 more source

Experimental Investigation of the Effects of 'Nigella sativa' and 'Vitis vinifera' on Intraoral Wound Healing. [PDF]

Oral Health Prev Dent
Tekbaş İ, Çalişir M, Annaç E, Bozgeyik İ, Çinar Z.   +4 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

Histological Evidence of the Antifibrotic Effect of Polyphenolic Extracts from the Berries <i>Vaccinium uliginosum</i>, <i>Vaccinium oxycoccos</i>, and <i>Vaccinium vitis-idaea</i> in a Model of Pulmonary Fibrosis. [PDF]

Biomedicines
Shulgau Z, Kamyshanskiy Y, Sergazy S, Kovalenko L, Baurzhan M, Kairgeldina S, Gulyayev A.   +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

A systematic color correction pipeline for controlled‐environment imaging

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
ABSTRACT We present a stepwise color correction (CC) pipeline for controlled imaging environments. The workflow integrates flat‐field correction (FFC), gamma correction, and white‐balance correction, followed by a color‐mapping (CM) stage using machine‐learning regression—linear, partial least squares, and neural networks (NNs)—to deliver reliable CC ...
Collins Wakholi, Michael A. Hardigan, Jungmin Lee, Scott B. Lukas, Max J. Feldman, Kayla R. Altendorf, Jeffrey L. Neyhart, Devin A. Rippner   +7 more
wiley   +1 more source

Hardware-aware knowledge-distilled CNN for real-time classification of plaque-associated angiographic findings on FPGA. [PDF]

Front Digit Health
Pravalika N, Afthab J, Rajamani V.
europepmc   +1 more source

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