Evidence map›Paper›PMID 34576101›Full record

ReviewInternational journal of molecular sciences2021

An Overview of Near Infrared Spectroscopy and Its Applications in the Detection of Genetically Modified Organisms.

Soo-In Sohn, Subramani Pandian, Young-Ju Oh, John-Lewis Zinia Zaukuu, Hyeon-Jung Kang, Tae-Hun Ryu, Woo-Suk Cho, Youn-Sung Cho, Eun-Kyoung Shin, Byoung-Kwan Cho

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Discrimination ofInternational journal of molecular sciences · 2022
    Article
  8. Discrimination of Transgenic Canola (International journal of molecular sciences · 2021
    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

10 authors.

Soo-In SohnDepartment of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Korea.ORCID 0000-0001-8819-7247
Subramani PandianDepartment of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Korea.ORCID 0000-0002-1445-8122
Young-Ju OhInstitute for Future Environmental Ecology Co., Ltd., Jeonju 54883, Korea.
John-Lewis Zinia ZaukuuDepartment of Measurements and Process Control, Szent István University, H-1118 Budapest, Hungary.ORCID 0000-0002-2058-4416
Hyeon-Jung KangDepartment of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Korea.
Tae-Hun RyuDepartment of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Korea.
Woo-Suk ChoDepartment of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Korea.
Youn-Sung ChoDepartment of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Korea.
Eun-Kyoung ShinDepartment of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Korea.
Byoung-Kwan ChoDepartment of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Korea.ORCID 0000-0002-8397-9853

Funding

Research Program for Agricultural Science & Technology Development and 2021 Post-doctoral Fellowship Program Project No. PJ014943012021
6 · The paper itself

Abstract

Near-infrared spectroscopy (NIRS) has become a more popular approach for quantitative and qualitative analysis of feeds, foods and medicine in conjunction with an arsenal of chemometric tools. This was the foundation for the increased importance of NIRS in other fields, like genetics and transgenic monitoring. A considerable number of studies have utilized NIRS for the effective identification and discrimination of plants and foods, especially for the identification of genetically modified crops. Few previous reviews have elaborated on the applications of NIRS in agriculture and food, but there is no comprehensive review that compares the use of NIRS in the detection of genetically modified organisms (GMOs). This is particularly important because, in comparison to previous technologies such as PCR and ELISA, NIRS offers several advantages, such as speed (eliminating time-consuming procedures), non-destructive/non-invasive analysis, and is inexpensive in terms of cost and maintenance. More importantly, this technique has the potential to measure multiple quality components in GMOs with reliable accuracy. In this review, we brief about the fundamentals and versatile applications of NIRS for the effective identification of GMOs in the agricultural and food systems.

Indexed as

Spectroscopy, Near-InfraredCrops, AgriculturalFoodPlants, Genetically Modifiedchemometric analysisdeep learningenvironmental riskgenetically modified organismsnear-infraredspectroscopy

Identifiers

PMID34576101
PMCPMC8469702

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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.