Evidence map›Paper›PMID 35808545›Full record

ArticleSensors (Basel, Switzerland)2022

Estimation of Leaf Area Index with a Multi-Channel Spectral Micro-Sensor for Wireless Sensing Networks.

Laura Maria Comella, Florian Bregler, Eiko Hager, Markus Anys, Johannes Klueppel, Stefan J Rupitsch, Christiane Werner, Peter Woias

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Laura Maria ComellaDepartment of Microsystems Engineering-IMTEK, University of Freiburg, 79110 Freiburg, Germany.
Florian BreglerDepartment of Microsystems Engineering-IMTEK, University of Freiburg, 79110 Freiburg, Germany.
Eiko HagerDepartment of Microsystems Engineering-IMTEK, University of Freiburg, 79110 Freiburg, Germany.
Markus AnysHydrology, Faculty of Environment and Natural Resources, University of Freiburg, Friedrichstraße 39, 79085 Freiburg, Germany.ORCID 0000-0001-9643-9939
Johannes KlueppelDepartment of Microsystems Engineering-IMTEK, University of Freiburg, 79110 Freiburg, Germany.
Stefan J RupitschDepartment of Microsystems Engineering-IMTEK, University of Freiburg, 79110 Freiburg, Germany.
Christiane WernerEcosystem Physiology, Faculty of Environment and Natural Resources, University of Freiburg, Georges-Koehler-Allee 53/54, 79110 Freiburg, Germany.ORCID 0000-0002-7676-9057
Peter WoiasDepartment of Microsystems Engineering-IMTEK, University of Freiburg, 79110 Freiburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The leaf area index (LAI) is a key parameter in the context of monitoring the development of tree crowns and plants in general. As parameters such as carbon assimilation, environmental stress on carbon, and the water fluxes within tree canopies are correlated to the leaves surface, this parameter is essential for understanding and modeling ecological processes. However, its continuous monitoring using manual state-of-the-art measurement instruments is still challenging. To address this challenge, we present an innovative sensor concept to obtain the LAI based on the cheap and easy to integrate multi-channel spectral sensor AS7341. Additionally, we present a method for processing and filtering the gathered data, which enables very high accuracy measurements with an nRMSE of only 0.098, compared to the manually-operated state-of-the-art instrument LAI-2200C (LiCor). The sensor that is embedded on a sensor node has been tested in long-term experiments, proving its suitability for continuous deployment over an entire season. It permits the estimation of both the plant area index (PAI) and leaf area index (LAI) and provides the first wireless system that obtains the LAI solely powered by solar cells. Its energy autonomy and wireless connectivity make it suitable for a massive deployment over large areas and at different levels of the tree crown. It may be upgraded to allow the parallel measurement of photosynthetic active radiation (PAR) and light quality, relevant parameters for monitoring processes within tree canopies.

Indexed as

CarbonPhotosynthesisPlant DevelopmentPlant LeavesPlant Physiological PhenomenaPlantsSeasonsTreesWaterWireless TechnologyCarbonWaterleaf area indexlong term deploymentwireless sensor network

Identifiers

PMID35808545
PMCPMC9269822

What OpenQuestion holds

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LicenceCC BY
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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.