Evidence map›Paper›PMID 38254535›Full record

ReviewFoods (Basel, Switzerland)2024

Intelligent Biosensors Promise Smarter Solutions in Food Safety 4.0.

Yuehua Chen, Yicheng Wang, Yiran Zhang, Xin Wang, Chen Zhang, Nan Cheng

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Foods (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

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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

6 authors.

Yuehua ChenSchool of Electrical and Information, Northeast Agricultural University, Harbin 150030, China.
Yicheng WangSchool of Food Science, Northeast Agricultural University, Harbin 150030, China.
Yiran ZhangCollege of Food Science & Nutritional Engineering, China Agricultural University, Beijing 100083, China.
Xin WangCollege of Food Science & Nutritional Engineering, China Agricultural University, Beijing 100083, China.
Chen ZhangCollege of Food Science & Nutritional Engineering, China Agricultural University, Beijing 100083, China.
Nan ChengCollege of Food Science & Nutritional Engineering, China Agricultural University, Beijing 100083, China.ORCID 0000-0003-2907-978X

Funding

China Agricultural University and Chinese Universities Scientific Fund 2023TC115
6 · The paper itself

Abstract

Food safety is closely related to human health. However, the regulation and testing processes for food safety are intricate and resource-intensive. Therefore, it is necessary to address food safety risks using a combination of deep learning, the Internet of Things, smartphones, quick response codes, smart packaging, and other smart technologies. Intelligent designs that combine digital systems and advanced functionalities with biosensors hold great promise for revolutionizing current food safety practices. This review introduces the concept of Food Safety 4.0, and discusses the impact of intelligent biosensors, which offer attractive smarter solutions, including real-time monitoring, predictive analytics, enhanced traceability, and consumer empowerment, helping improve risk management and ensure the highest standards of food safety.

Indexed as

advanced functionalitydigital technologyFood Safety 4.0food safety risksInternet of Thingssmart packaging

Identifiers

PMID38254535
PMCPMC10815208

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.