Evidence map›Paper›PMID 37384557›Full record

ReviewEnvironmental science & technology2023

Glyphosate Separating and Sensing for Precision Agriculture and Environmental Protection in the Era of Smart Materials.

Jarosław Mazuryk, Katarzyna Klepacka, Włodzimierz Kutner, Piyush Sindhu Sharma

Open access · hybridAbstract readReview
In one paragraph

Review in Environmental science & technology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
3.3field-weighted citation impact, top 7% 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

6 citing papers in PubMed, 46 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

4 authors at 1 institution in 2 countries.

Jarosław MazurykDepartment of Electrode Processes, Institute of Physical Chemistry, Polish Academy of Sciences, 01-224 Warsaw, Poland.ORCID 0000-0003-3311-7136
Katarzyna KlepackaFunctional Polymers Research Team, Institute of Physical Chemistry, Polish Academy of Sciences, 01-224 Warsaw, Poland.ORCID 0000-0002-2003-0181
Włodzimierz KutnerFaculty of Mathematics and Natural Sciences. School of Sciences, Cardinal Stefan Wyszynski University in Warsaw, 01-938 Warsaw, Poland.ORCID 0000-0003-3586-5170
Piyush Sindhu SharmaFunctional Polymers Research Team, Institute of Physical Chemistry, Polish Academy of Sciences, 01-224 Warsaw, Poland.ORCID 0000-0002-7729-8314
Institute of Physical Chemistry · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present article critically and comprehensively reviews the most recent reports on smart sensors for determining glyphosate (GLP), an active agent of GLP-based herbicides (GBHs) traditionally used in agriculture over the past decades. Commercialized in 1974, GBHs have now reached 350 million hectares of crops in over 140 countries with an annual turnover of 11 billion USD worldwide. However, rolling exploitation of GLP and GBHs in the last decades has led to environmental pollution, animal intoxication, bacterial resistance, and sustained occupational exposure of the herbicide of farm and companies' workers. Intoxication with these herbicides dysregulates the microbiome-gut-brain axis, cholinergic neurotransmission, and endocrine system, causing paralytic ileus, hyperkalemia, oliguria, pulmonary edema, and cardiogenic shock. Precision agriculture, i.e., an (information technology)-enhanced approach to crop management, including a site-specific determination of agrochemicals, derives from the benefits of smart materials (SMs), data science, and nanosensors. Those typically feature fluorescent molecularly imprinted polymers or immunochemical aptamer artificial receptors integrated with electrochemical transducers. Fabricated as portable or wearable lab-on-chips, smartphones, and soft robotics and connected with SM-based devices that provide machine learning algorithms and online databases, they integrate, process, analyze, and interpret massive amounts of spatiotemporal data in a user-friendly and decision-making manner. Exploited for the ultrasensitive determination of toxins, including GLP, they will become practical tools in farmlands and point-of-care testing. Expectedly, smart sensors can be used for personalized diagnostics, real-time water, food, soil, and air quality monitoring, site-specific herbicide management, and crop control.

Indexed as

HerbicidesSmart MaterialsAgricultureAnimalsConservation of Natural ResourcesGlyphosatePlants, Genetically ModifiedGlyphosateHerbicidesSmart Materialsengineered nanomaterialsenvironmental pollutionglyphosate-based herbicideslab-on-a-chipprecision agriculturesmart material-based sensors

Identifiers

PMID37384557
PMCPMC10339735
OpenAlexW4382602851

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.