ArticleJournal of experimental botany2020
Plot-level rapid screening for photosynthetic parameters using proximal hyperspectral imaging.
Article in Journal of experimental botany, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
47 citing papers in PubMed, 102 citations in OpenAlex.
- Unraveling plant phenotype to genotype associations with daily hyperspectral traits inPlant 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
- Transferable spectral models for high-throughput estimation of winter wheat net photosynthetic rate: a cross-scale approach using leaf and UAV hyperspectral data.Frontiers in plant science · 2026Article
- Exploring prediction mechanisms for temperature-induced variation in maximum carboxylation rate from spectral reflectance across 450-850 nm in cucumber leaves.Photosynthetica · 2026Article
- Monitoring and Risk Prediction of Low-Temperature Stress in Strawberries through Fusion of Multisource Phenotypic Spatial Variability Features.Plant phenomics (Washington, D.C.) · 2025Article
- High-Throughput Field Phenotyping Using Unmanned Aerial Vehicles (UAVs) for Rapid Estimation of Photosynthetic Traits.Plant phenomics (Washington, D.C.) · 2025Article
- Proximal remote sensing: an essential tool for bridging the gap between high-resolution ecosystem monitoring and global ecology.The New phytologist · 2025Review
- Increasing Rubisco as a simple means to enhance photosynthesis and productivity now without lowering nitrogen use efficiency.The New phytologist · 2025Review
- From spectrum to yield: advances in crop photosynthesis with hyperspectral imaging.Photosynthetica · 2025Review
- Evaluating Photosynthetic Light Response Models for Leaf Photosynthetic Traits in Paddy Rice (Plants (Basel, Switzerland) · 2024Article
- Exploring natural genetic diversity in a bread wheat multi-founder population: dual imaging of photosynthesis and stomatal kinetics.Journal of experimental botany · 2024Article
- Deep learning-enabled exploration of global spectral features for photosynthetic capacity estimation.Frontiers in plant science · 2024Article
- Tools for Measuring Photosynthesis at Different Scales.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Phenotyping cotton leaf chlorophyll viaFrontiers in plant science · 2024Article
- Utilizing VSWIR spectroscopy for macronutrient and micronutrient profiling in winter wheat.Frontiers in plant science · 2024Article
- Hyperspectral imaging and artificial intelligence enhance remote phenotyping of grapevine rootstock influence on whole vine photosynthesis.Frontiers in plant science · 2024Article
- Monitoring of drought stress and transpiration rate using proximal thermal and hyperspectral imaging in an indoor automated plant phenotyping platform.Plant methods · 2023Article
- Plant optics: underlying mechanisms in remotely sensed signals for phenotyping applications.AoB PLANTS · 2023Review
- TSWIFT: Tower Spectrometer on Wheels for Investigating Frequent Timeseries for high-throughput phenotyping of vegetation physiology.Plant methods · 2023Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Photosynthesis is currently measured using time-laborious and/or destructive methods which slows research and breeding efforts to identify crop germplasm with higher photosynthetic capacities. We present a plot-level screening tool for quantification of photosynthetic parameters and pigment contents that utilizes hyperspectral reflectance from sunlit leaf pixels collected from a plot (~2 m×2 m) in <1 min. Using field-grown Nicotiana tabacum with genetically altered photosynthetic pathways over two growing seasons (2017 and 2018), we built predictive models for eight photosynthetic parameters and pigment traits. Using partial least squares regression (PLSR) analysis of plot-level sunlit vegetative reflectance pixels from a single visible near infra-red (VNIR) (400-900 nm) hyperspectral camera, we predict maximum carboxylation rate of Rubisco (Vc,max, R2=0.79) maximum electron transport rate in given conditions (J1800, R2=0.59), maximal light-saturated photosynthesis (Pmax, R2=0.54), chlorophyll content (R2=0.87), the Chl a/b ratio (R2=0.63), carbon content (R2=0.47), and nitrogen content (R2=0.49). Model predictions did not improve when using two cameras spanning 400-1800 nm, suggesting a robust, widely applicable and more 'cost-effective' pipeline requiring only a single VNIR camera. The analysis pipeline and methods can be used in any cropping system with modified species-specific PLSR analysis to offer a high-throughput field phenotyping screening for germplasm with improved photosynthetic performance in field trials.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.