Evidence map›Paper›PMID 38895615›Full record

ArticleFrontiers in plant science2024

Thermal imaging can reveal variation in stay-green functionality of wheat canopies under temperate conditions.

Jonas Anderegg, Norbert Kirchgessner, Helge Aasen, Olivia Zumsteg, Beat Keller, Radek Zenkl, Achim Walter, Andreas Hund

Abstract read
In one paragraph

Article in Frontiers in plant science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Harnessing artificial intelligence in plant breeding: innovations in digital phenotyping and breeding methodologies.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Jonas AndereggPlant Pathology Group, Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland.
Norbert KirchgessnerCrop Science Group, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland.
Helge AasenEarth Observation of Agroecosystems Team, Research Division Agroecology and Environment, Agroscope, Zurich, Switzerland.
Olivia ZumstegCrop Science Group, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland.
Beat KellerCrop Science Group, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland.
Radek ZenklPlant Pathology Group, Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland.
Achim WalterCrop Science Group, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland.
Andreas HundCrop Science Group, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Canopy temperature (CT) is often interpreted as representing leaf activity traits such as photosynthetic rates, gas exchange rates, or stomatal conductance. This interpretation is based on the observation that leaf activity traits correlate with transpiration which affects leaf temperature. Accordingly, CT measurements may provide a basis for high throughput assessments of the productivity of wheat canopies during early grain filling, which would allow distinguishing functional from dysfunctional stay-green. However, whereas the usefulness of CT as a fast surrogate measure of sustained vigor under soil drying is well established, its potential to quantify leaf activity traits under high-yielding conditions is less clear. To better understand sensitivity limits of CT measurements under high yielding conditions, we generated within-genotype variability in stay-green functionality by means of differential short-term pre-anthesis canopy shading that modified the sink:source balance. We quantified the effects of these modifications on stay-green properties through a combination of gold standard physiological measurements of leaf activity and newly developed methods for organ-level senescence monitoring based on timeseries of high-resolution imagery and deep-learning-based semantic image segmentation. In parallel, we monitored CT by means of a pole-mounted thermal camera that delivered continuous, ultra-high temporal resolution CT data. Our results show that differences in stay-green functionality translate into measurable differences in CT in the absence of major confounding factors. Differences amounted to approximately 0.8°C and 1.5°C for a very high-yielding source-limited genotype, and a medium-yielding sink-limited genotype, respectively. The gradual nature of the effects of shading on CT during the stay-green phase underscore the importance of a high measurement frequency and a time-integrated analysis of CT, whilst modest effect sizes confirm the importance of restricting screenings to a limited range of morphological and phenological diversity.

Indexed as

deep learninghigh throughput field phenotypingphysiological breedingremote sensingsemantic segmentation

Identifiers

PMID38895615
PMCPMC11184164

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Registered trials

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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.