(In Press) Smart storage technologies applied to fresh foods: A review

Wang, J, Zhang, M, Gao, Z and Adhikari, B 2019, '(In Press) Smart storage technologies applied to fresh foods: A review', Critical Reviews in Food Science and Nutrition, vol. 58, no. 16, pp. 2689-2699.

Document type: Journal Article
Collection: Journal Articles

Title (In Press) Smart storage technologies applied to fresh foods: A review
Author(s) Wang, J
Zhang, M
Gao, Z
Adhikari, B
Year 2019
Journal name Critical Reviews in Food Science and Nutrition
Volume number 58
Issue number 16
Start page 2689
End page 2699
Total pages 11
Publisher Taylor and Francis
Abstract Fresh foods are perishable, seasonal and regional in nature and their storage, transportation and preservation of freshness are quite challenging. Smart storage technologies can online detection and monitor the changes of quality parameters and storage environment of fresh foods during storage, so that operators can make timely adjustments to reduce the loss. This article reviews the smart storage technologies from two aspects: online detection technologies and smartly monitoring technologies for fresh foods. Online detection technologies include electronic nose, nuclear magnetic resonance (NMR), near infrared spectroscopy (NIRS), hyperspectral imaging and computer vision. Smartly monitoring technologies mainly include some intelligent indicators for monitoring the change of storage environment. Smart storage technologies applied to fresh foods need to be highly efficient and nondestructive and need to be competitively priced. In this work, we have critically reviewed the principles, applications, and development trends of smart storage technologies.
Subject Food Processing
Keyword(s) cold chain
fresh foods
storage technology
DOI - identifier 10.1080/10408398.2017.1323722
Copyright notice © 2017 Taylor and Francis Group, LLC
ISSN 1040-8398
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in Thomson Reuters Web of Science Article
Altmetric details:
Access Statistics: 17 Abstract Views  -  Detailed Statistics
Created: Mon, 29 Apr 2019, 13:04:00 EST by Catalyst Administrator
© 2014 RMIT Research Repository • Powered by Fez SoftwareContact us