ArticleJournal of experimental botany2021
Field-based remote sensing models predict radiation use efficiency in wheat.
Article in Journal of experimental botany, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- 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
- Beyond high-throughput: leveraging plant phenotyping to improve understanding and prediction of plant growth through process-based models.The New phytologist · 2026Review
- Phenotyping the hidden half: combining UAV phenotyping and machine learning to predict barley root traits in the field.Journal of experimental botany · 2025Article
- Integration of physiological and remote sensing traits for improved genomic prediction of wheat yield.The plant genome · 2025Article
- Enhanced radiation use efficiency and grain filling rate as the main drivers of grain yield genetic gains in the CIMMYT elite spring wheat yield trial.Scientific reports · 2024Article
- Climate change impacts on crop breeding: Targeting interacting biotic and abiotic stresses for wheat improvement.The plant genome · 2024Article
- Reviving grain quality in wheat through non-destructive phenotyping techniques like hyperspectral imaging.Food and energy security · 2023Review
- Estimating yield-contributing physiological parameters of cotton using UAV-based imagery.Frontiers in plant science · 2023Article
- A 'wiring diagram' for source strength traits impacting wheat yield potential.Journal of experimental botany · 2023Review
- Applications of a Hyperspectral Imaging System Used to Estimate Wheat Grain Protein: A Review.Frontiers in plant science · 2022Review
- Phosphite treatment can improve root biomass and nutrition use efficiency in wheat.Frontiers in plant science · 2022Article
- Prediction of Photosynthetic, Biophysical, and Biochemical Traits in Wheat Canopies to Reduce the Phenotyping Bottleneck.Frontiers in plant science · 2022Article
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Authors and funding
6 authors.
Funding
Abstract
Wheat yields are stagnating or declining in many regions, requiring efforts to improve the light conversion efficiency, known as radiation use efficiency (RUE). RUE is a key trait in plant physiology because it links light capture and primary metabolism with biomass accumulation and yield, but its measurement is time consuming and this has limited its use in fundamental research and large-scale physiological breeding. In this study, high-throughput plant phenotyping (HTPP) approaches were used among a population of field-grown wheat with variation in RUE and photosynthetic traits to build predictive models of RUE, biomass, and intercepted photosynthetically active radiation (IPAR). Three approaches were used: best combination of sensors; canopy vegetation indices; and partial least squares regression. The use of remote sensing models predicted RUE with up to 70% accuracy compared with ground truth data. Water indices and canopy greenness indices [normalized difference vegetation index (NDVI), enhanced vegetation index (EVI)] are the better option to predict RUE, biomass, and IPAR, and indices related to gas exchange, non-photochemical quenching [photochemical reflectance index (PRI)] and senescence [structural-insensitive pigment index (SIPI)] are better predictors for these traits at the vegetative and grain-filling stages, respectively. These models will be instrumental to explain canopy processes, improve crop growth and yield modelling, and potentially be used to predict RUE in different crops or ecosystems.
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