ArticlePlant methods2023
Monitoring of drought stress and transpiration rate using proximal thermal and hyperspectral imaging in an indoor automated plant phenotyping platform.
Article in Plant methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.
- A systematic review of multi-mode analytics for enhanced plant stress evaluation.Frontiers in plant science · 2025Pooled it
- Hyperspectral imaging-based early stress and disease detection for sustainable crop management.Planta · 2026Review
- Thermal image segmentation in weedy fields via synthetic RGB-trained models and GAN-based cross-modality alignment.Plant phenomics (Washington, D.C.) · 2026Article
- Design of a Distance-Compensated Infrared Thermometer for Canopy Temperature Monitoring.Sensors (Basel, Switzerland) · 2026Article
- Harnessing artificial intelligence in plant breeding: innovations in digital phenotyping and breeding methodologies.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Review
- Molecular Mechanisms and Experimental Strategies for Understanding Plant Drought Response.Plants (Basel, Switzerland) · 2026Review
- Drought Response and Genetic Variation in Scots Pine Seedlings' Provenances: Insights From High-Throughput Phenotyping for Climate-Resilient Forestry.Evolutionary applications · 2025Article
- Harnessing Multi-Omics and Predictive Modeling for Climate-Resilient Crop Breeding: From Genomes to Fields.Genes · 2025Review
- Integrating sensor fusion with machine learning for comprehensive assessment of phenotypic traits and drought response in poplar species.Plant biotechnology journal · 2025Article
- MADI: A multispectral automated dynamic imager to monitor plant health.Plant phenomics (Washington, D.C.) · 2025Article
- Determining water status of walnut orchards using the crop water stress index and canopy temperature measurements.Plant methods · 2025Article
- Recent Methods for Evaluating Crop Water Stress Using AI Techniques: A Review.Sensors (Basel, Switzerland) · 2024Review
- Infrared Thermography Monitoring of Durum and Common Wheat for Adaptability Assessing and Yield Performance Prediction.Plants (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 3 institutions in 4 countries.
Funding
Abstract
backgroundThermography is a popular tool to assess plant water-use behavior, as plant temperature is influenced by transpiration rate, and is commonly used in field experiments to detect plant water deficit. Its application in indoor automated phenotyping platforms is still limited and mainly focuses on differences in plant temperature between genotypes or treatments, instead of estimating stomatal conductance or transpiration rate. In this study, the transferability of commonly used thermography analysis protocols from the field to greenhouse phenotyping platforms was evaluated. In addition, the added value of combining thermal infrared (TIR) with hyperspectral imaging to monitor drought effects on plant transpiration rate (E) was evaluated.
resultsThe sensitivity of commonly used TIR indices to detect drought-induced and genotypic differences in water status was investigated in eight maize inbred lines in the automated phenotyping platform PHENOVISION. Indices that normalized plant temperature for vapor pressure deficit and/or air temperature at the time of imaging were most sensitive to drought and could detect genotypic differences in the plants' water-use behavior. However, these indices were not strongly correlated to stomatal conductance and E. The canopy temperature depression index, the crop water stress index and the simplified stomatal conductance index were more suitable to monitor these traits, and were consequently used to develop empirical E prediction models by combining them with hyperspectral indices and/or environmental variables. Different modeling strategies were evaluated, including single index-based, machine learning and mechanistic models. Model comparison showed that combining multiple TIR indices in a random forest model can improve E prediction accuracy, and that the contribution of the hyperspectral data is limited when multiple indices are used. However, the empirical models trained on one genotype were not transferable to all eight inbred lines.
conclusionOverall, this study demonstrates that existing TIR indices can be used to monitor drought stress and develop E prediction models in an indoor setup, as long as the indices normalize plant temperature for ambient air temperature or relative humidity.
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.