Literature DB >> 24915395

Recent developments and applications of hyperspectral imaging for quality evaluation of agricultural products: a review.

Dan Liu1, Xin-An Zeng, Da-Wen Sun.   

Abstract

Food quality and safety is the foremost issue for consumers, retailers as well as regulatory authorities. Most quality parameters are assessed by traditional methods, which are time consuming, laborious, and associated with inconsistency and variability. Non-destructive methods have been developed to objectively measure quality attributes for various kinds of food. In recent years, hyperspectral imaging (HSI) has matured into one of the most powerful tools for quality evaluation of agricultural and food products. HSI allows characterization of a sample's chemical composition (spectroscopic component) and external features (imaging component) in each point of the image with full spectral information. In order to track the latest research developments of this technology, this paper gives a detailed overview of the theory and fundamentals behind this technology and discusses its applications in the field of quality evaluation of agricultural products. Additionally, future potentials of HSI are also reported.

Keywords:  NIR; Non-destructive methods; chemometrics; computer vision; data mining; food quality; hyperspectral imaging

Mesh:

Year:  2015        PMID: 24915395     DOI: 10.1080/10408398.2013.777020

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


  6 in total

Review 1.  Quality Assessment of Fruits and Vegetables Based on Spatially Resolved Spectroscopy: A Review.

Authors:  Wan Si; Jie Xiong; Yuping Huang; Xuesong Jiang; Dong Hu
Journal:  Foods       Date:  2022-04-20

2.  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

3.  Integration of Partial Least Squares Regression and Hyperspectral Data Processing for the Nondestructive Detection of the Scaling Rate of Carp (Cyprinus carpio).

Authors:  Huihui Wang; Kunlun Wang; Xinyu Zhu; Peng Zhang; Jixin Yang; Mingqian Tan
Journal:  Foods       Date:  2020-04-16

4.  Spectral-Based Screening Approach Evaluating Two Specific Maize Lines With Divergent Resistance to Invasion by Aflatoxigenic Fungi.

Authors:  Zuzana Hruska; Haibo Yao; Russell Kincaid; Feifei Tao; Robert L Brown; Thomas E Cleveland; Kanniah Rajasekaran; Deepak Bhatnagar
Journal:  Front Microbiol       Date:  2020-01-22       Impact factor: 5.640

Review 5.  Spectroscopic techniques for authentication of animal origin foods.

Authors:  Vandana Chaudhary; Priyanka Kajla; Aastha Dewan; R Pandiselvam; Claudia Terezia Socol; Cristina Maria Maerescu
Journal:  Front Nutr       Date:  2022-09-20

Review 6.  Application of Visible/Infrared Spectroscopy and Hyperspectral Imaging With Machine Learning Techniques for Identifying Food Varieties and Geographical Origins.

Authors:  Lei Feng; Baohua Wu; Susu Zhu; Yong He; Chu Zhang
Journal:  Front Nutr       Date:  2021-06-17
  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.