Evidence map›Paper›PMID 35804712›Full record

ReviewFoods (Basel, Switzerland)2022

Emerging Approach for Fish Freshness Evaluation: Principle, Application and Challenges.

Zhepeng Zhang, Ying Sun, Shangyuan Sang, Lingling Jia, Changrong Ou

Abstract readReview
In one paragraph

Review in Foods (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 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

5 authors.

Zhepeng ZhangDepartment of Food Science and Engineering, Ningbo University, Ningbo 315211, China.
Ying SunDepartment of Food Science and Engineering, Ningbo University, Ningbo 315211, China.
Shangyuan SangDepartment of Food Science and Engineering, Ningbo University, Ningbo 315211, China.ORCID 0000-0001-9487-6289
Lingling JiaDepartment of Food Science and Engineering, Ningbo University, Ningbo 315211, China.
Changrong OuDepartment of Food Science and Engineering, Ningbo University, Ningbo 315211, China.ORCID 0000-0003-1631-2773

Funding

the National Key Research and Development Program under Grant 2019YFD0901705
6 · The paper itself

Abstract

Affected by micro-organisms and endogenous enzymes, fish are highly perishable during storage, processing and transportation. Efficient evaluation of fish freshness to ensure consumer safety and reduce raw material losses has received an increasing amount of attention. Several of the conventional freshness assessment techniques have plenty of shortcomings, such as being destructive, time-consuming and laborious. Recently, various sensors and spectroscopic techniques have shown great potential due to rapid analysis, low sample preparation and cost-effectiveness, and some methods are especially non-destructive and suitable for online or large-scale operations. Non-destructive techniques typically respond to characteristic substances produced by fish during spoilage without destroying the sample. In this review, we summarize, in detail, the principles and applications of emerging approaches for assessing fish freshness including visual indicators derived from intelligent packaging, active sensors, nuclear magnetic resonance (NMR) and optical spectroscopic techniques. Recent developments in emerging technologies have demonstrated their advantages in detecting fish freshness, but some challenges remain in popularization, optimizing sensor selectivity and sensitivity, and the development of algorithms and chemometrics in spectroscopic techniques.

Indexed as

active sensorsfish freshnessnondestructivespectroscopic techniquesvisual indicators

Identifiers

PMID35804712
PMCPMC9265959

What OpenQuestion holds

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Registered trials

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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.