Evidence map›Paper›PMID 40431075›Full record

ReviewPlants (Basel, Switzerland)2025

Smart Chip Technology for the Control and Management of Invasive Plant Species: A Review.

Qaiser Javed, Mohammed Bouhadi, Smiljana Goreta Ban, Dean Ban, David Heath, Babar Iqbal, Jianfan Sun, Marko Černe

Abstract readReview
In one paragraph

Review in Plants (Basel, Switzerland), 2025. 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. Review
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

8 authors.

Qaiser JavedInstitute of Agriculture and Tourism, Karla Huguesa 8, 52440 Poreč, Croatia.
Mohammed BouhadiInstitute of Agriculture and Tourism, Karla Huguesa 8, 52440 Poreč, Croatia.ORCID 0000-0002-1887-9768
Smiljana Goreta BanInstitute of Agriculture and Tourism, Karla Huguesa 8, 52440 Poreč, Croatia.ORCID 0000-0003-0350-5074
Dean BanInstitute of Agriculture and Tourism, Karla Huguesa 8, 52440 Poreč, Croatia.
David HeathJožef Stefan Institute, Jamova Cesta 39, 1000 Ljubljana, Slovenia.
Babar IqbalSchool of the Environment and Safety Engineering, Jiangsu University, Zhenjiang 212013, China.ORCID 0000-0002-2115-8494
Jianfan SunSchool of the Environment and Safety Engineering, Jiangsu University, Zhenjiang 212013, China.ORCID 0000-0002-8361-1848
Marko ČerneInstitute of Agriculture and Tourism, Karla Huguesa 8, 52440 Poreč, Croatia.ORCID 0000-0002-0949-0638

Funding

Croatian Science Foundation HRZZ- IPS-2022-02-2099
6 · The paper itself

Abstract

Invasive plant species threaten biodiversity, disrupt ecosystems, and are costly to manage. Standard control methods, such as mechanical and chemical (herbicides), are usually ineffective and time-consuming and negatively affect the environment, especially in the latter case. This review explores the potential of smart chip technology (SCT) as a sustainable, precision approach tool for invasive species management. Integrating microchip sensors with artificial intelligence (AI) into the Internet of Things (IoT) and remote sensing technology allows for real-time monitoring, predictive modelling, and focused action, significantly improving management effectiveness. As one of many examples discussed herein, AI-driven decision-making systems can process real-time data from IoT-enabled environmental sensors to optimize invasive species detection. Smart chip technology also offers real-time monitoring of invasive species' life processes, spread, and environmental effects, enabling artificial intelligence-powered eco-friendly control strategies that minimize herbicide usage and lessen collateral ecosystem damage. Despite the potential of SCT, challenges remain, including cost, biodegradability, and regulatory constraints. However, recent advances in biodegradable electronics and AI-driven automation offer promising solutions to many identified obstacles. Future research should focus on scalable deployment, improved predictive analytics, and interdisciplinary collaboration to drive innovation. Using SCT can help make invasive species control more sustainable while supporting biodiversity and strengthening agricultural systems.

Indexed as

artificial intelligencebiosensorsinternet of thingsinvasive plant controlprecision agricultureremote sensingsustainable ecosystem management

Identifiers

PMID40431075
PMCPMC12114904

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.