Freshness Evaluation of Three Kinds of Meats Based on the Electronic Nose.

electronic nose freshness evaluation meat

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
31 Jan 2019
Historique:
received: 04 12 2018
revised: 21 01 2019
accepted: 28 01 2019
entrez: 3 2 2019
pubmed: 3 2 2019
medline: 3 2 2019
Statut: epublish

Résumé

The aim of this study was to use an electronic nose set up in our lab to detect and predict the freshness of pork, beef and mutton. Three kinds of freshness, including fresh, sub-fresh and putrid, was established by human sensory evaluation and was used as a reference for the electronic nose's discriminant factor analysis. The principal component analysis results showed the electronic nose could distinguish well pork, beef and mutton samples with different storage times. In the PCA figures, three kinds of meats samples all presented an approximate parabola trend during 7 days' storage time. The discriminant factor analysis showed electronic nose could distinguish and judge well the freshness of samples (accuracy was 89.5%, 84.2% and 94.7% for pork, beef and mutton, respectively). Therefore, the electronic nose is promising for meat fresh detection application.

Identifiants

pubmed: 30709028
pii: s19030605
doi: 10.3390/s19030605
pmc: PMC6387179
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : National Key Research and Development Program of China
ID : 2017YFD0400102
Organisme : National Natural Science Foundation of China
ID : 31401570
Organisme : Science and Technology Program of Suzhou
ID : SS201605
Organisme : Zhejiang Provincial Collaborative Innovation Center of Food Safety and Nutrition
ID : 2017SICR104

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Auteurs

Jun Chen (J)

Inspection and Quarantine Integrated Technology Center, Suzhou Entry-Exit Inspection and Quarantine Bureau, Jiangsu 215104, China. chenjuneau@163.com.
School of Food Science and Biotechnology, Zhejiang GongShang University, Zhejiang 310018, China. chenjuneau@163.com.

Juanhong Gu (J)

Inspection and Quarantine Integrated Technology Center, Suzhou Entry-Exit Inspection and Quarantine Bureau, Jiangsu 215104, China. gujh2013@126.com.

Rong Zhang (R)

Inspection and Quarantine Integrated Technology Center, Suzhou Entry-Exit Inspection and Quarantine Bureau, Jiangsu 215104, China. doit2003@126.com.

Yuezhong Mao (Y)

School of Food Science and Biotechnology, Zhejiang GongShang University, Zhejiang 310018, China. myz-001@163.com.

Shiyi Tian (S)

School of Food Science and Biotechnology, Zhejiang GongShang University, Zhejiang 310018, China. tianshiyi@zjgsu.edu.cn.

Classifications MeSH