Detecting volatile compounds in food by open-path Fourier-transform infrared spectroscopy.


Journal

Food research international (Ottawa, Ont.)
ISSN: 1873-7145
Titre abrégé: Food Res Int
Pays: Canada
ID NLM: 9210143

Informations de publication

Date de publication:
05 2019
Historique:
received: 10 07 2018
revised: 11 11 2018
accepted: 16 11 2018
entrez: 20 3 2019
pubmed: 20 3 2019
medline: 17 6 2020
Statut: ppublish

Résumé

We previously found that the brand of a food and spoilage of the food can be identified from the infrared spectra of the volatile compounds released. However, this required pumping the volatile compounds into a gas cell, meaning measurements over large areas could not be made. Gas components can be quantified from a distance of a few metres or kilometres by open-path Fourier-transform infrared spectroscopy (FTIR), and the spatial distributions of gas clouds can even be determined using open-path FTIR and an imaging detection method. In the study described here, we used open-path FTIR to remotely detect volatile compounds in food. Active and passive methods were used to obtain infrared spectra of volatile compounds released from spirits, vinegars, and grapes from a distance of 5 m. The absorption characteristics of ethanol, esters, and unknown volatile compounds were clearly found in the spectra. The brands of the spirits and degree to which the grapes had spoiled were identified by compensating for ethanol in the atmosphere and chemometrics. The results indicate that open-path FTIR can be used to remotely detect volatile compounds released by food and may be able to be used to identify spoiling food in large food warehouses.

Identifiants

pubmed: 30884737
pii: S0963-9969(18)30927-X
doi: 10.1016/j.foodres.2018.11.042
pii:
doi:

Substances chimiques

Gases 0
Volatile Organic Compounds 0
Ethanol 3K9958V90M
Acetic Acid Q40Q9N063P

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

968-973

Informations de copyright

Copyright © 2018. Published by Elsevier Ltd.

Auteurs

Leizi Jiao (L)

College of Engineering, Shanxi Agricultural University, Taigu 030801, China; National Engineering Laboratory for Agri-product Quality Traceability, Beijing Research Center for Intelligent Equipment for Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China.

Yuming Guo (Y)

College of Engineering, Shanxi Agricultural University, Taigu 030801, China. Electronic address: guoyuming99@sina.com.

Jia Chen (J)

National Engineering Laboratory for Agri-product Quality Traceability, Beijing Research Center for Intelligent Equipment for Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China.

Xiande Zhao (X)

National Engineering Laboratory for Agri-product Quality Traceability, Beijing Research Center for Intelligent Equipment for Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China.

Daming Dong (D)

National Engineering Laboratory for Agri-product Quality Traceability, Beijing Research Center for Intelligent Equipment for Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China. Electronic address: damingdong@hotmail.com.

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Classifications MeSH