Literature DB >> 22823348

Principles and applications of hyperspectral imaging in quality evaluation of agro-food products: a review.

Gamal Elmasry1, Mohammed Kamruzzaman, Da-Wen Sun, Paul Allen.   

Abstract

The requirements of reliability, expeditiousness, accuracy, consistency, and simplicity for quality assessment of food products encouraged the development of non-destructive technologies to meet the demands of consumers to obtain superior food qualities. Hyperspectral imaging is one of the most promising techniques currently investigated for quality evaluation purposes in numerous sorts of applications. The main advantage of the hyperspectral imaging system is its aptitude to incorporate both spectroscopy and imaging techniques not only to make a direct assessment of different components simultaneously but also to locate the spatial distribution of such components in the tested products. Associated with multivariate analysis protocols, hyperspectral imaging shows a convinced attitude to be dominated in food authentication and analysis in future. The marvellous potential of the hyperspectral imaging technique as a non-destructive tool has driven the development of more sophisticated hyperspectral imaging systems in food applications. The aim of this review is to give detailed outlines about the theory and principles of hyperspectral imaging and to focus primarily on its applications in the field of quality evaluation of agro-food products as well as its future applicability in modern food industries and research.

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Year:  2012        PMID: 22823348     DOI: 10.1080/10408398.2010.543495

Source DB:  PubMed          Journal:  Crit Rev Food Sci Nutr        ISSN: 1040-8398            Impact factor:   11.176


  25 in total

1.  Identification of fungi-contaminated peanuts using hyperspectral imaging technology and joint sparse representation model.

Authors:  Xiaotong Qi; Jinbao Jiang; Ximin Cui; Deshuai Yuan
Journal:  J Food Sci Technol       Date:  2019-06-10       Impact factor: 2.701

2.  Visualized detection of quality change of cooked beef with condiments by hyperspectral imaging technique.

Authors:  Anguo Xie; Jing Sun; Tingmin Wang; Yunhong Liu
Journal:  Food Sci Biotechnol       Date:  2022-06-28       Impact factor: 3.231

Review 3.  Near-Infrared Spectroscopy as a Potential COVID-19 Early Detection Method: A Review and Future Perspective.

Authors:  Muna E Raypah; Asma Nadia Faris; Mawaddah Mohd Azlan; Nik Yusnoraini Yusof; Fariza Hanim Suhailin; Rafidah Hanim Shueb; Irneza Ismail; Fatin Hamimi Mustafa
Journal:  Sensors (Basel)       Date:  2022-06-10       Impact factor: 3.847

4.  Technical workflows for hyperspectral plant image assessment and processing on the greenhouse and laboratory scale.

Authors:  Stefan Paulus; Anne-Katrin Mahlein
Journal:  Gigascience       Date:  2020-08-01       Impact factor: 6.524

Review 5.  Recent developments in hyperspectral imaging for assessment of food quality and safety.

Authors:  Hui Huang; Li Liu; Michael O Ngadi
Journal:  Sensors (Basel)       Date:  2014-04-22       Impact factor: 3.576

6.  Hyperspectral imaging for mapping of total nitrogen spatial distribution in pepper plant.

Authors:  Ke-Qiang Yu; Yan-Ru Zhao; Xiao-Li Li; Yong-Ni Shao; Fei Liu; Yong He
Journal:  PLoS One       Date:  2014-12-30       Impact factor: 3.240

7.  Non-destructive analysis of sucrose, caffeine and trigonelline on single green coffee beans by hyperspectral imaging.

Authors:  Nicola Caporaso; Martin B Whitworth; Stephen Grebby; Ian D Fisk
Journal:  Food Res Int       Date:  2017-12-14       Impact factor: 6.475

8.  Hyperspectral imaging for non-destructive prediction of fermentation index, polyphenol content and antioxidant activity in single cocoa beans.

Authors:  Nicola Caporaso; Martin B Whitworth; Mark S Fowler; Ian D Fisk
Journal:  Food Chem       Date:  2018-03-11       Impact factor: 7.514

9.  Hyperspectral Imaging Coupled with Random Frog and Calibration Models for Assessment of Total Soluble Solids in Mulberries.

Authors:  Yan-Ru Zhao; Ke-Qiang Yu; Yong He
Journal:  J Anal Methods Chem       Date:  2015-09-14       Impact factor: 2.193

10.  Hyperspectral Imaging for Evaluating Impact Damage to Mango According to Changes in Quality Attributes.

Authors:  Duohua Xu; Huaiwen Wang; Hongwei Ji; Xiaochuan Zhang; Yanan Wang; Zhe Zhang; Hongfei Zheng
Journal:  Sensors (Basel)       Date:  2018-11-14       Impact factor: 3.576

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