ArticleG3 (Bethesda, Md.)2016
Field-Based High-Throughput Plant Phenotyping Reveals the Temporal Patterns of Quantitative Trait Loci Associated with Stress-Responsive Traits in Cotton.
Article in G3 (Bethesda, Md.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.
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Who cites it
47 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A meta-analysis of quantitative trait loci for abiotic and biotic stress resistance in tetraploid cotton.Molecular genetics and genomics : MGG · 2017Pooled it
- Genetic dynamics drive maize growth and breeding.Genome biology · 2026Article
- Predictive modeling, pattern recognition, and spatiotemporal representations of plant growth in simulated and controlled environments: A comprehensive review.Plant phenomics (Washington, D.C.) · 2025Review
- Integration of crop modeling and sensing into molecular breeding for nutritional quality and stress tolerance.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Review
- Cotton under heat stress: a comprehensive review of molecular breeding, genomics, and multi-omics strategies.Frontiers in genetics · 2025Review
- Converging functional phenotyping with systems mapping to illuminate the genotype-phenotype associations.Horticulture research · 2024Article
- Field-based high-throughput phenotyping enhances phenomic and genomic predictions for grain yield and plant height across years in maize.G3 (Bethesda, Md.) · 2024Article
- Yield prediction in a peanut breeding program using remote sensing data and machine learning algorithms.Frontiers in plant science · 2024Article
- Cotton morphological traits tracking through spatiotemporal registration of terrestrial laser scanning time-series data.Frontiers in plant science · 2024Article
- Unraveling the genetic and molecular basis of heat stress in cotton.Frontiers in genetics · 2024Review
- Field phenotyping for African crops: overview and perspectives.Frontiers in plant science · 2023Review
- Capturing crop adaptation to abiotic stress using image-based technologies.Open biology · 2022Review
- Phenomic data-facilitated rust and senescence prediction in maize using machine learning algorithms.Scientific reports · 2022Article
- Mapping QTLs for spring green-up, plant vigor, and plant biomass in two lowland switchgrass populations.Molecular breeding : new strategies in plant improvement · 2022Article
- Plant Genotype to Phenotype Prediction Using Machine Learning.Frontiers in genetics · 2022Review
- Genome-Wide Dissection of the Genetic Basis for Drought Tolerance inFrontiers in plant science · 2022Article
- Bottlenecks and opportunities in field-based high-throughput phenotyping for heat and drought stress.Journal of experimental botany · 2021Review
- Unoccupied aerial systems discovered overlooked loci capturing the variation of entire growing period in maize.The plant genome · 2021Article
- Scaling up high-throughput phenotyping for abiotic stress selection in the field.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021Review
- Dynamics of Maize Vegetative Growth and Drought Adaptability Using Image-Based Phenotyping Under Controlled Conditions.Frontiers in plant science · 2021Article
Corrections and comments
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The application of high-throughput plant phenotyping (HTPP) to continuously study plant populations under relevant growing conditions creates the possibility to more efficiently dissect the genetic basis of dynamic adaptive traits. Toward this end, we employed a field-based HTPP system that deployed sets of sensors to simultaneously measure canopy temperature, reflectance, and height on a cotton (Gossypium hirsutum L.) recombinant inbred line mapping population. The evaluation trials were conducted under well-watered and water-limited conditions in a replicated field experiment at a hot, arid location in central Arizona, with trait measurements taken at different times on multiple days across 2010-2012. Canopy temperature, normalized difference vegetation index (NDVI), height, and leaf area index (LAI) displayed moderate-to-high broad-sense heritabilities, as well as varied interactions among genotypes with water regime and time of day. Distinct temporal patterns of quantitative trait loci (QTL) expression were mostly observed for canopy temperature and NDVI, and varied across plant developmental stages. In addition, the strength of correlation between HTPP canopy traits and agronomic traits, such as lint yield, displayed a time-dependent relationship. We also found that the genomic position of some QTL controlling HTPP canopy traits were shared with those of QTL identified for agronomic and physiological traits. This work demonstrates the novel use of a field-based HTPP system to study the genetic basis of stress-adaptive traits in cotton, and these results have the potential to facilitate the development of stress-resilient cotton cultivars.
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