Results 111 to 120 of about 4,964 (232)

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

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

Convolutional Neural Networks for Image-Based High-Throughput Plant Phenotyping: A Review

Plant Phenomics, 2020
Plant phenotyping has been recognized as a bottleneck for improving the efficiency of breeding programs, understanding plant-environment interactions, and managing agricultural systems.
Yu Jiang, Changying Li
doaj   +1 more source

The Use of Low-Cost Drone and Multi-Trait Analysis to Identify High Nitrogen Use Lines for Wheat Improvement

Agronomy
Breeding for nitrogen use efficiency (NUE) is becoming more important as global uncertainty makes the production and application of nitrogen (N) fertilizers more expensive and environmentally unfriendly.
Liyan Shen, Greg Deakin, Guohui Ding, Mujahid Ali, Jie Dai, Zhenjie Wen, Felipe Pinheiro, Ji Zhou, Robert Jackson   +8 more
doaj   +1 more source

Molecular Chaperone Networks in Plants: Maintaining Proteostasis and Enhancing Stress Resilience for Crop Improvement

Plant, Cell &Environment, EarlyView.
ABSTRACT Molecular chaperones play a central role in the plant proteostasis machinery by aiding the folding of nascent proteins, preventing aggregation, and repairing or degrading damaged proteins. These functions are especially essential during abiotic and biotic stress, which can destabilise cellular proteins and disrupt metabolic homoeostasis.
Mingfang Yang, Anqin Gao, Tsz‐Yan Chan, Hafiz Mamoon Rehman, Sehar Nawaz, Sehrish Bashir, Noman Mahmood, Muhammad Wajid Ullah, Chunlin Long, Hon‐Ming Lam, Muhammad Arif   +10 more
wiley   +1 more source

A Perspective on Plant Phenomics: Coupling Deep Learning and Near-Infrared Spectroscopy. [PDF]

Front Plant Sci, 2022
Vasseur F, Cornet D, Beurier G, Messier J, Rouan L, Bresson J, Ecarnot M, Stahl M, Heumos S, Gérard M, Reijnen H, Tillard P, Lacombe B, Emanuel A, Floret J, Estarague A, Przybylska S, Sartori K, Gillespie LM, Baron E, Kazakou E, Vile D, Violle C.   +22 more
europepmc   +1 more source

Time‐series multi‐omics analysis of micronutrient stress in Sorghum bicolor reveals iron and zinc crosstalk and regulatory network conservation

Plant Biology, EarlyView.
Overlap between Fe and Zn responsive gene regulatory networks (GRNs) were found, indicative of micronutrient crosstalk, and conservation of root and leaf GRNs and genes suggests strong constraint on homeostasis networks in plants. Abstract Micronutrient stress impacts growth, biomass production, and grain yield in crops.
A. Mishra, A. Bhat, S. Kumari, R. Sharma, J. Braynen, D. Tadesse, S. El Alaoui, S. Seaver, N. Grosjean, D. Ware, M. Xie, T. Paape   +11 more
wiley   +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

Comparative conventional and phenomics approaches to assess symbiotic effectiveness of Bradyrhizobia strains in soybean (Glycine max L. Merrill) to drought

Scientific Reports, 2017
Symbiotic effectiveness of rhizobitoxine (Rtx)-producing strains of Bradyrhizobium spp. in soybean (cultivar NRC-37/Ahilya-4) under limited soil moisture conditions was evaluated using phenomics tools such as infrared(IR) thermal and visible imaging. Red,
Venkadasamy Govindasamy, Priya George, Lalitkumar Aher, Shunmugiah V. Ramesh, Arunachalam Thangasamy, Sivalingam Anandan, Susheel Kumar Raina, Mahesh Kumar, Jagadish Rane, Kannepalli Annapurna, Paramjit Singh Minhas   +10 more
doaj   +1 more source

Model-based plant phenomics on morphological traits using morphometric descriptors. [PDF]

Breed Sci, 2022
Noshita K, Murata H, Kirie S.
europepmc   +1 more source