ArticlePlant phenomics (Washington, D.C.)2024
Using UAV-Based Temporal Spectral Indices to Dissect Changes in the Stay-Green Trait in Wheat.
Article in Plant phenomics (Washington, D.C.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Improving Nitrogen Use Efficiency in Wheat: Integrating Agronomic, Genomics, and Remote Sensing for Sustainable Production.Plant, cell & environment · 2026Review
- Deciphering the genetic basis of yield components in wheat by integrating hyperspectral-based phenomes.Plant phenomics (Washington, D.C.) · 2026Article
- Genetic dissection of a key dynamic growth period QTL for source-sink-related traits and its breeding application potential in wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Phenotypic and Physiological Changes Associated with Senescence in Stay-GreenPlants (Basel, Switzerland) · 2026Article
- Synthetic-augmented multimodal deep learning fuses dual-angle RGB images and phenology to unlock genotype-informative canopy structural trait in wheat.Plant phenomics (Washington, D.C.) · 2026Article
- Predictions of wheat phenotypic variability by integrating high-throughput phenotyping observations into a crop growth model.Plant phenomics (Washington, D.C.) · 2026Article
- Genome-wide association mapping and candidate genes analysis of high-throughput image descriptors for wheat frost tolerance.Stress biology · 2025Article
- UAV-LiDAR high-throughput time-series phenotyping and genome-wide association analysis reveal the genetic basis of plant height in peanut (Plant phenomics (Washington, D.C.) · 2025Article
- UAV-based multispectral image analysis revealed stay-green haplotypes in wheat specific for different soil nitrogen levels.BMC plant biology · 2025Article
- Winter wheat yield prediction using UAV-based multivariate time series data and variate-independent tokenization.Plant phenomics (Washington, D.C.) · 2025Article
- Mapping of a Quantitative Trait Locus for Stay-Green Trait in Common Wheat.Plants (Basel, Switzerland) · 2025Article
- Integrated diagnostics and time series sensitivity assessment for growth monitoring of a medicinal plant (Frontiers in plant science · 2025Article
- High-throughput phenotyping using hyperspectral indicators supports the genetic dissection of yield in durum wheat grown under heat and drought stress.Frontiers in plant science · 2024Article
Corrections and comments
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Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Stay-green (SG) in wheat is a beneficial trait that increases yield and stress tolerance. However, conventional phenotyping techniques limited the understanding of its genetic basis. Spectral indices (SIs) as non-destructive tools to evaluate crop temporal senescence provide an alternative strategy. Here, we applied SIs to monitor the senescence dynamics of 565 diverse wheat accessions from anthesis to maturation stages over 2 field seasons. Four SIs (normalized difference vegetation index, green normalized difference vegetation index, normalized difference red edge index, and optimized soil-adjusted vegetation index) were normalized to develop relative stay-green scores (RSGS) as the SG indicators. An RSGS-based genome-wide association study identified 47 high-confidence quantitative trait loci (QTL) harboring 3,079 single-nucleotide polymorphisms associated with SG and 1,085 corresponding candidate genes. Among them, 15 QTL overlapped or were adjacent to known SG-related QTL/genes, while the remaining QTL were novel. Notably, a set of favorable haplotypes of SG-related candidate genes such as
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