Evidence map›Paper›PMID 35393858›Full record

ReviewACS applied materials & interfaces2022

Metal-Organic Frameworks in Agriculture.

Sara Rojas, Antonio Rodríguez-Diéguez, Patricia Horcajada

Open access · hybridAbstract readReview
In one paragraph

Review in ACS applied materials & interfaces, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
11.2field-weighted citation impact, top 1% 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

29 citing papers in PubMed, 157 citations in OpenAlex.

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  14. COChemical science · 2025
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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

3 authors at 2 institutions in 1 country.

Sara RojasBiochemistry and Electronics as Sensing Technologies Group, Department of Inorganic Chemistry, University of Granada, Av. Fuentenueva s/n, 18071 Granada, Spain.ORCID 0000-0002-7874-2122
Antonio Rodríguez-DiéguezBiochemistry and Electronics as Sensing Technologies Group, Department of Inorganic Chemistry, University of Granada, Av. Fuentenueva s/n, 18071 Granada, Spain.ORCID 0000-0003-3198-5378
Patricia HorcajadaAdvanced Porous Materials Unit (APMU), IMDEA Energy, Av. Ramón de la Sagra, 3, 28935 Móstoles, Madrid, Spain.ORCID 0000-0002-6544-5911
Universidad de Granada · ESMadrid Institute for Advanced Studies · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Agrochemicals, which are crucial to meet the world food qualitative and quantitative demand, are compounds used to kill pests (insects, fungi, rodents, or unwanted plants). Regrettably, there are some important issues associated with their widespread and extensive use (e.g., contamination, bioaccumulation, and development of pest resistance); thus, a reduced and more controlled use of agrochemicals and thorough detection in food, water, soil, and fields are necessary. In this regard, the development of new functional materials for the efficient application, detection, and removal of agrochemicals is a priority. Metal-organic frameworks (MOFs) with exceptional sorptive, recognition capabilities, and catalytical properties have very recently shown their potential in agriculture. This Review emphasizes the recent advances in the use of MOFs in agriculture through three main views: environmental remediation, controlled agrochemical release, and detection of agrochemicals.

Indexed as

Metal-Organic FrameworksWater PurificationAdsorptionAgricultureAgrochemicalsAgrochemicalsMetal-Organic Frameworksagrochemicalscontrolled releasemetal−organic frameworksselective adsorption and degradationsensing

Identifiers

PMID35393858
PMCPMC9026272
OpenAlexW4224118936

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.