Evidence map›Paper›PMID 35788870›Full record

ArticleAnalytical and bioanalytical chemistry2022

A novel colorimetric sensor array for real-time and on-site monitoring of meat freshness.

Wengui Nie, Yifei Chen, Hua Zhang, Jinsen Liu, Zhengchun Peng, Yingchun Li

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Article in Analytical and bioanalytical chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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.

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Wengui Nie *Key Laboratory of Xinjiang Phytomedicine Resources for Ministry of Education, School of Pharmacy, Shihezi University, Shihezi, 832000, China.
Yifei Chen *Key Laboratory of Xinjiang Phytomedicine Resources for Ministry of Education, School of Pharmacy, Shihezi University, Shihezi, 832000, China.
Hua ZhangKey Laboratory of Xinjiang Phytomedicine Resources for Ministry of Education, School of Pharmacy, Shihezi University, Shihezi, 832000, China.
Jinsen LiuShenzhen ENCO Instrument Co., Ltd, Shenzhen, 518000, China.
Zhengchun PengSchool of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, 518060, China. zcpeng@szu.edu.cn.
Yingchun LiSchool of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, 518060, China. liyingchun@hit.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Food quality control is essential in industry and daily life. In this work, we developed a novel colorimetric sensor array composed of several pH-sensitive dyes for monitoring meat freshness. A color change in the sensor array was seen after exposure to volatile organic compounds (VOCs), and the images were captured for precise quantification of the VOCs. In conjunction with pattern recognition, meat freshness at different storage periods was readily discerned, revealing that the as-fabricated colorimetric sensor array possessed excellent discrimination ability. The linear range for quantitative analysis of volatiles related to meat spoilage was from 5 ppm to 100 ppm, with a limit of detection at the ppb level (S/N = 3). Furthermore, the testing results obtained by the sensor in assessing meat freshness were validated by a standard method for measuring the total volatile basic nitrogen (TVB-N). The sensing signals showed good agreement with the results obtained in TVB-N when measuring real food samples. The sensor also displayed good reproducibility (RSD < 5%) and long-term stability. The sensor was successfully used for on-site and real-time determination of volatiles emitted from rotting meat, demonstrating its potential application in monitoring the quality and safety of meat products.

Indexed as

ColorimetryVolatile Organic CompoundsFood QualityMeatNitrogenReproducibility of ResultsNitrogenVolatile Organic CompoundsBiogenic aminesMeat freshnessTVB-NVisualizationVolatile organic compounds (VOCs)

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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.