Evidence map›Paper›PMID 38184781›Full record

ReviewPlant biotechnology journal2024

Wearable sensor supports in-situ and continuous monitoring of plant health in precision agriculture era.

Xiao-Hong Li, Meng-Zhao Li, Jing-Yi Li, Yang-Yang Gao, Chun-Rong Liu, Ge-Fei Hao

Abstract readReview
In one paragraph

Review in Plant biotechnology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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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

6 authors.

Xiao-Hong Li *National Key Laboratory of Green Pesticide, Key Laboratory of Green Pesticide and Agricultural Bioengineering, Ministry of Education, Center for Research and Development of Fine Chemicals, Guizhou University, Guiyang, China.
Meng-Zhao Li *National Key Laboratory of Green Pesticide, College of Chemistry, Central China Normal University, Wuhan, China.
Jing-Yi LiNational Key Laboratory of Green Pesticide, College of Chemistry, Central China Normal University, Wuhan, China.
Yang-Yang GaoNational Key Laboratory of Green Pesticide, Key Laboratory of Green Pesticide and Agricultural Bioengineering, Ministry of Education, Center for Research and Development of Fine Chemicals, Guizhou University, Guiyang, China.
Chun-Rong LiuNational Key Laboratory of Green Pesticide, College of Chemistry, Central China Normal University, Wuhan, China.
Ge-Fei HaoNational Key Laboratory of Green Pesticide, Key Laboratory of Green Pesticide and Agricultural Bioengineering, Ministry of Education, Center for Research and Development of Fine Chemicals, Guizhou University, Guiyang, China.ORCID https://orcid.org/0000-0003-4090-8411

Funding

National Natural Science Foundation of China 32125033National Natural Science Foundation of China 32260687Program of Introducing Talents of Discipline to Universities of China 111Program,D20023the Central Government Guides Local Science and Technology Development Fund Projects Qiankehezhongyindi(2023)001
6 · The paper itself

Abstract

Plant health is intricately linked to crop quality, food security and agricultural productivity. Obtaining accurate plant health information is of paramount importance in the realm of precision agriculture. Wearable sensors offer an exceptional avenue for investigating plant health status and fundamental plant science, as they enable real-time and continuous in-situ monitoring of physiological biomarkers. However, a comprehensive overview that integrates and critically assesses wearable plant sensors across various facets, including their fundamental elements, classification, design, sensing mechanism, fabrication, characterization and application, remains elusive. In this study, we provide a meticulous description and systematic synthesis of recent research progress in wearable sensor properties, technology and their application in monitoring plant health information. This work endeavours to serve as a guiding resource for the utilization of wearable plant sensors, empowering the advancement of plant health within the precision agriculture paradigm.

Indexed as

AgricultureWearable Electronic DevicesBiosensing TechniquesCrops, Agriculturalin‐situ and continuousmonitoringplant health informationprecision agriculturewearable sensors

Identifiers

PMID38184781
PMCPMC11123445

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.