Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Classification and prediction of drought and salinity stress tolerance in barley using GenPhenML.

Scientific reports - 29 Jul 2024

Akbari Mahjoubeh, Sabouri Hossein, Sajadi Sayed Javad, Yarahmadi Saeed, Ahangar Leila

Abstract excerpt

Genetic and agronomic advances consistently lead to an annual increase in global barley yield. Since abiotic stresses (physical environmental factors that negatively affect plant growth) reduce barley yield, it is necessary to predict barley resistance. Artificial intelligence and machine learning (ML) models are new and powerful tools for predicting product resilience. Considering the research gap in the use of...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Droughts
Share to Hordeum
Share to Machine Learning

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Neural Networks, Computer

Share to Salinity

Share to Salt Stress

Share to Salt Tolerance

Share to Stress, Physiological

Source

Open in PubMed Open full text

Identifiers

PMID: 39075223
DOI: 10.1038/s41598-024-68392-w
PMCID: PMC11286739

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Classification and prediction of drought and salinity stress tolerance in barley using GenPhenML.PMID 39075223Read ↗

Agro-morphological, biochemical, and molecular markers of barley genotypes grown under salinity stress conditions.Semantic proximity Read ↗

Screening for drought tolerance and genetic diversity of wheat varieties using agronomic and molecular markers.Semantic proximity Read ↗

Improvement of prediction ability by integrating multi-omic datasets in barley.Semantic proximity Read ↗

LOS2 gene plays a potential role in barley (Hordeum vulgare L.) salinity tolerance as a hub geneSemantic proximity Read ↗

Physiological and Molecular Responses of Barley Genotypes to Salinity Stress.Semantic proximity Read ↗

Prediction of drought-resistant genes in Arabidopsis thaliana using SVM-RFE.Semantic proximity Read ↗

Dissecting the resilience of barley genotypes under multiple adverse environmental conditions.Semantic proximity Read ↗

A comprehensive web-based platform for calculation of abiotic stress tolerance indices in plant breeding.Semantic proximity Read ↗

Physiological and morphological responses of different spring barley genotypes to water deficit and associated QTLs.Semantic proximity Read ↗

Genomic Prediction of Manganese Efficiency in Winter Barley.Semantic proximity Read ↗

Integrating AMMI, Bayesian-AMMI, BLUP, and GGE biplot models to improve the identification of high-yielding and stable barley genotypes.Semantic proximity Read ↗

OptimGS: a dual integrative genomic prediction framework for improving cold stress tolerance in wheat.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.