Evidence map›Paper›PMID 36837948›Full record

ArticleMicromachines2023

Analysis of Electrochemically Active Substances in Malvaceae Leaves via Electroanalytical Sensing Technology for Species Identification.

Qiong Wang, Weiting Ye, Dongling Li, Jiangwei Zhu, Chenghang Liu, Chengte Lin, Li Fu, Zenglai Xu

Abstract read
In one paragraph

Article in Micromachines, 2023. 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. Review
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.

Qiong WangInstitute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China.
Weiting YeCollege of Materials and Environmental Engineering, Hangzhou Dianzi University, Hangzhou 310018, China.
Dongling LiInstitute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China.
Jiangwei ZhuCo-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China.
Chenghang LiuInstitute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China.
Chengte LinKey Laboratory of Marine Materials and Related Technologies, Zhejiang Key Laboratory of Marine Materials and Protective Technologies, Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy of Sciences, Ningbo 315201, China.ORCID 0000-0002-7090-9610
Li FuCollege of Materials and Environmental Engineering, Hangzhou Dianzi University, Hangzhou 310018, China.ORCID 0000-0002-5957-7790
Zenglai XuInstitute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China.

Funding

National Natural Science Foundation of China 22004026
6 · The paper itself

Abstract

Electrochemical analysis has become a new method for plant analysis in recent years. It can not only collect signals of electrochemically active substances in plant tissues, but can also be used to identify plant species. At the same time, the signals of electrochemically active substances in plant tissues can also be used to investigate plant phylogeny. In this work, we collected electrochemical finger patterns in Malvaceae leaves based on the established methodological strategy. After the second derivative treatment, the collected electrochemical fingerprints can show more obvious differences. Three different recognition models were used to attempt electrochemical fingerprinting. The results show that linear support vector classification can be used to identify species with high accuracy by combining the electrochemical fingerprint signals collected in the phosphoric acid buffer solution and acetic acid buffer solution. In addition, the fingerprint information collected by the electrochemical sensor is further used for phylogenetic investigation. The 18 species were divided into three clusters. Species of the same genus have been clustered together. Dendrogram obtained by electrochemical fingerprinting was used to compare previously reported results deduced from morphological and complete chloroplast genomes.

Indexed as

electrochemical fingerprintelectrochemical sensorpattern recognitionphylogeneticsphytochemistry

Identifiers

PMID36837948
PMCPMC9963770

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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.