Evidence map›Paper›PMID 29581726›Full record

ArticlePlant methods2018

Estimation of leaf traits from reflectance measurements: comparison between methods based on vegetation indices and several versions of the PROSPECT model.

Jingyi Jiang, Alexis Comar, Philippe Burger, Pierre Bancal, Marie Weiss, Frédéric Baret

Abstract read
In one paragraph

Article in Plant methods, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
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

6 authors.

Jingyi Jiang1EMMAH UMR 1114, INRA, UAPV, 84914 Avignon, France.
Alexis ComarHIPHEN, Avignon, France.
Philippe Burger3AGIR UMR 1248, INRA, Toulouse, France.
Pierre BancalUMR ECOSYS, INRA, Grignon, France.
Marie Weiss1EMMAH UMR 1114, INRA, UAPV, 84914 Avignon, France.
Frédéric Baret1EMMAH UMR 1114, INRA, UAPV, 84914 Avignon, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLeaf biochemical composition corresponds to traits related to the plant state and its functioning. This study puts the emphasis on the main leaf absorbers: chlorophyll a and b ([Formula: see text]), carotenoids ([Formula: see text]), water ([Formula: see text]) and dry mater ([Formula: see text]) contents. Two main approaches were used to estimate [[Formula: see text] [Formula: see text], [Formula: see text], [Formula: see text]] in a non-destructive way using spectral measurements. The first one consists in building empirical relationships from experimental datasets using either the raw reflectances or their combination into vegetation indices (VI). The second one relies on the inversion of physically based models of leaf optical properties. Although the first approach is commonly used, the calibration of the empirical relationships is generally conducted over a limited dataset. Consequently, poor predictions may be observed when applying them on cases that are not represented in the training dataset, i.e. when dealing with different species, genotypes or under contrasted environmental conditions. The retrieval performances of the selected VIs were thus compared to the ones of four PROSPECT model versions based on reflectance data acquired at two phenological stages, over six wheat genotypes grown under three different nitrogen fertilizations and two sowing density modalities. Leaf reflectance was measured in the lab with a spectrophotometer equipped with an integrating sphere, the leaf being placed in front of a white Teflon background to increase the sensitivity to leaf biochemical composition. Destructive measurements of [[Formula: see text] [Formula: see text], [Formula: see text], [Formula: see text]] were performed concurrently.

resultsThe destructive measurements demonstrated that the carotenoid, [Formula: see text], and chlorophyll, [Formula: see text], contents were strongly correlated (r

conclusionsPROSPECT model inversion and empirical VI approach provide similar retrieval performances and are useful methods to estimate leaf biochemical composition from spectral measurements. However, the PROSPECT model inversion gives potential access to additional traits on surface reflectivity and leaf internal structure. This study suggests that non-destructive estimation of leaf chlorophyll and water contents is a relevant method to provide leaf traits with relatively high throughput.

Indexed as

Carotenoid contentChlorophyll contentDry matter contentLeafPhenotypingRadiative transfer modelReflectanceTransmittanceWater contentWheat

Identifiers

PMID29581726
PMCPMC5861673

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.