Evidence map›Paper›PMID 36915503›Full record

ReviewHeliyon2023

Advanced visual sensing techniques for on-site detection of pesticide residue in water environments.

Eliasu Issaka, Mary Adumo Wariboko, Nana Adwoa Nkuma Johnson, Ofosuhemaa Nyame-do Aniagyei

Abstract readReview
In one paragraph

Review in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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.

Eliasu IssakaSchool of Environmental Science and Engineering, Jiangsu University, Zhenjiang 212013, PR China.
Mary Adumo WaribokoSchool of Medicine, Faculty of Dermatology and Venereology, Jiangsu University, Zhenjiang 212013, PR China.
Nana Adwoa Nkuma JohnsonSchool of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China.
Ofosuhemaa Nyame-do AniagyeiSchool of Medicine, Kwame Nkrumah University of Science and Technology, Kumasi 00233, Ghana.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pesticide usage has increased to fulfil agricultural demand. Pesticides such as organophosphorus pesticides (OPPs) are ubiquitous in world food production. Their widespread usage has unavoidable detrimental consequences for humans, wildlife, water, and soil environments. Hence, the development of more convenient and efficient pesticide residue (PR) detection methods is of paramount importance. Visual detecting approaches have acquired a lot of interest among different sensing systems due to inherent advantages in terms of simplicity, speed, sensitivity, and eco-friendliness. Furthermore, various detections have been proven to enable real-life PR surveillance in environment water. Fluorometric (FL), colourimetric (CL), and enzyme-inhibition (EI) techniques have emerged as viable options. These sensing technologies do not need complex operating processes or specialist equipment, and the simple colour change allows for visual monitoring of the sensing result. Visual sensing techniques for on-site detection of PR in water environments are discussed in this paper. This paper further reviews prior research on the integration of CL, FL, and EI-based techniques with nanoparticles (NPs), quantum dots (QDs), and metal-organic frameworks (MOFs). Smartphone detection technologies for PRs are also reviewed. Finally, conventional methods and nanoparticle (NPs) based strategies for the detection of PRs are compared.

Indexed as

ElectrochemistryEnzyme-inhibition (EI)On-site detectionPesticides residues (PRs)Smartphone detectionVisual sensing

Identifiers

PMID36915503
PMCPMC10006482

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.