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

Persistent and transient QTLs underlying growth trajectory of plant height in sorghum.

Journal of experimental botany - 20 May 2026

Alladassi Boris M E, Mu Qi, Wei Jialu, Miguez Fernando E, Price Kevin, Li Xianran, Yu Jianming

Abstract excerpt

Genetic studies based on end-of-season measurements focus only on the outcome of a complex and dynamic process. Uncovering the genetic basis underlying the temporal dynamics of plant height will enhance our understanding of the genotype-to-phenotype relationship. Here, we conducted functional mapping to investigate the temporal dynamics of plant height using the time-series data extracted from unmanned aerial...

Read the complete abstract on PubMed

Topics

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

Share to Chromosome Mapping
Share to Genotype
Share to Phenotype

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Quantitative Trait Loci

Share to Sorghum

Source

Open in PubMed Open full text

Identifiers

PMID: 41669842
DOI: 10.1093/jxb/erag062
PMCID: PMC13187637

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Persistent and transient QTLs underlying growth trajectory of plant height in sorghum.PMID 41669842Read ↗

Functional QTL mapping and genomic prediction of canopy height in wheat measured using a robotic field phenotyping platform.Semantic proximity Read ↗

Temporal phenomic predictions from unoccupied aerial systems can outperform genomic predictions.Semantic proximity Read ↗

Crop growth model-enabled genetic mapping of biomass accumulation dynamics in photoperiod-sensitive sorghum.Semantic proximity Read ↗

Predicting Lodging Severity in Sorghum Breeding Trials Using UAV-Based Photogrammetrically Derived Height DataSemantic proximity Read ↗

Phenomic data-driven biological prediction of maize through field-based high-throughput phenotyping integration with genomic data.Semantic proximity Read ↗

Phenomics-derived temporal maize health and environmental index enhance physiology-informed genomic prediction of yield across environments.Semantic proximity Read ↗

Time series canopy phenotyping enables the identification of genetic variants controlling dynamic phenotypes in soybean.Semantic proximity Read ↗

Temporally resolved growth patterns reveal novel information about the polygenic nature of complex quantitative traits.Semantic proximity Read ↗

Phenotypic plasticity in plant height shaped by interaction between genetic loci and diurnal temperature range.Semantic proximity Read ↗

Genetic dissection of a key dynamic growth period QTL for source-sink-related traits and its breeding application potential in wheat.Semantic proximity Read ↗

A High-Throughput, Field-Based Phenotyping Technology for Tall Biomass Crops.Semantic proximity Read ↗

Genetic variation of growth dynamics in maize (Zea mays L.) revealed through automated non-invasive phenotyping.Semantic proximity Read ↗

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