Evidence map›Paper›PMID 28674844›Full record

Review3 Biotech2017

Current perspectives on genetically modified crops and detection methods.

Madhu Kamle, Pradeep Kumar, Jayanta Kumar Patra, Vivek K Bajpai

Open access · bronzeAbstract readReview
In one paragraph

Review in 3 Biotech, 2017. 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
10.1field-weighted citation impact, top 2% 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

18 citing papers in PubMed, 78 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Digital PCR-Based Characterization of aFoods (Basel, Switzerland) · 2022
    Article
  7. Article
  8. Review
  9. Review
  10. Review
  11. Article
  12. Review
  13. Review
  14. EngineeringFrontiers in bioengineering and biotechnology · 2020
    Article
  15. Article
  16. Review
  17. Article
  18. 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

4 authors at 3 institutions in 2 countries.

Madhu KamleDepartment of Forestry, North Eastern Regional Institute of Science and Technology (Deemed University), Nirjuli, Arunachal Pradesh, 791109, India.
Pradeep KumarDepartment of Forestry, North Eastern Regional Institute of Science and Technology (Deemed University), Nirjuli, Arunachal Pradesh, 791109, India. pkbiotech@gmail.com.ORCID http://orcid.org/0000-0002-0892-5425
Jayanta Kumar PatraResearch Institute of Biotechnology and Medical Converged Science, Dongguk University-Seoul, Ilsandong-gu, Gyeonggido, 10326, Korea.
Vivek K BajpaiDepartment of Applied Microbiology and Biotechnology, Microbiome Laboratory, Yeungnam University, Gyeongsan, Gyeongbuk, 38541, Korea. vbiotech04@gmail.com.
North Eastern Regional Institute of Science and Technology · INDongguk University · KRYeungnam University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetically modified (GM) crops are the fastest adopted commodities in the agribiotech industry. This market penetration should provide a sustainable basis for ensuring food supply for growing global populations. The successful completion of two decades of commercial GM crop production (1996-2015) is underscored by the increasing rate of adoption of genetic engineering technology by farmers worldwide. With the advent of introduction of multiple traits stacked together in GM crops for combined herbicide tolerance, insect resistance, drought tolerance or disease resistance, the requirement of reliable and sensitive detection methods for tracing and labeling genetically modified organisms in the food/feed chain has become increasingly important. In addition, several countries have established threshold levels for GM content which trigger legally binding labeling schemes. The labeling of GM crops is mandatory in many countries (such as China, EU, Russia, Australia, New Zealand, Brazil, Israel, Saudi Arabia, Korea, Chile, Philippines, Indonesia, Thailand), whereas in Canada, Hong Kong, USA, South Africa, and Argentina voluntary labeling schemes operate. The rapid adoption of GM crops has increased controversies, and mitigating these issues pertaining to the implementation of effective regulatory measures for the detection of GM crops is essential. DNA-based detection methods have been successfully employed, while the whole genome sequencing using next-generation sequencing (NGS) technologies provides an advanced means for detecting genetically modified organisms and foods/feeds in GM crops. This review article describes the current status of GM crop commercialization and discusses the benefits and shortcomings of common and advanced detection systems for GMs in foods and animal feeds.

Indexed as

DetectionELISAGenetically modified cropsNext-generation sequencingReal-time PCRTransgenic

Identifiers

PMID28674844
PMCPMC5495694
OpenAlexW2734152508

What OpenQuestion holds

Textmetadata
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.