Evidence map›Paper›PMID 25288935›Full record

ArticleThe plant pathology journal2013

Feasibility Study for Detection of Turnip yellow mosaic virus (TYMV) Infection of Chinese Cabbage Plants Using Raman Spectroscopy.

Saetbyeol Kim, Sanguk Lee, Hee-Youn Chi, Mi-Kyeong Kim, Jeong-Soo Kim, Su-Heon Lee, Hoeil Chung

Open access · goldAbstract read
In one paragraph

Article in The plant pathology journal, 2013. 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
0.8field-weighted citation impact, top 16% of its field
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, 21 citations in OpenAlex.

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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

7 authors at 4 institutions in 1 country.

Saetbyeol KimDepartment of Chemistry, Hanyang University, Seoul 133-791, Korea.
Sanguk LeeDepartment of Chemistry, Hanyang University, Seoul 133-791, Korea.
Hee-Youn ChiSmarteome. Co., Ltd., Suwon 441-853, Korea.
Mi-Kyeong KimAgricultural Microbiology Division, National Academy of Agricultural Science, RDA, Suwon 441-707, Korea.
Jeong-Soo KimAgricultural Microbiology Division, National Academy of Agricultural Science, RDA, Suwon 441-707, Korea.
Su-Heon LeeSchool of Applied Biosciences, College of Agriculture & Life Scieneces, Kyungpook National University, Daegu 702-701, Korea.
Hoeil ChungDepartment of Chemistry, Hanyang University, Seoul 133-791, Korea.
Hanyang University · KRKyungpook National University · KRNational Academy of Agricultural Science · KRSuwon Research Institute · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Raman spectroscopy provides many advantages compared to other common analytical techniques due to its ability of rapid and accurate identification of unknown specimens as well as simple sample preparation. Here, we described potential of Raman spectroscopic technique as an efficient and high throughput method to detect plants infected by economically important viruses. To enhance the detection sensitivity of Raman measurement, surface enhanced Raman scattering (SERS) was employed. Spectra of extracts from healthy and Turnip yellow mosaic virus (TYMV) infected Chinese cabbage leaves were collected by mixing with gold (Au) nanoparticles. Our result showed that TYMV infected plants could be discriminated from non-infected healthy plants, suggesting the current method described here would be an alternative potential tool to screen virus-infection of plants in fields although it needs more studies to generalize the technique.

Indexed as

discriminationRaman spectroscopysurface enhanced Raman scattering (SERS)Turnip yellow mosaic virus (TYMV)virus detection

Identifiers

PMID25288935
PMCPMC4174782
OpenAlexW2075145442

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.