Literature DB >> 27750085

Hyperspectral imaging with multivariate analysis for technological parameters prediction and classification of muscle foods: A review.

Jun-Hu Cheng1, Bart Nicolai2, Da-Wen Sun3.   

Abstract

Muscle foods are very important for a well-balanced daily diet. Due to their perishability and vulnerability, there is a need for quality and safety evaluation of such foods. Hyperspectral imaging (HSI) coupled with multivariate analysis is becoming increasingly popular for the non-destructive, non-invasive, and rapid determination of important quality attributes and the classification of muscle foods. This paper reviews recent advances of application of HSI for predicting some significant muscle foods parameters, including color, tenderness, firmness, springiness, water-holding capacity, drip loss and pH. In addition, algorithms for the rapid classification of muscle foods are also reported and discussed. It will be shown that this technology has great potential to replace traditional analytical methods for predicting various quality parameters and classifying muscle foods. Copyright Â
© 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Chemometrics; Classification; HSI; Muscle food; Technological parameter

Mesh:

Substances:

Year:  2016        PMID: 27750085     DOI: 10.1016/j.meatsci.2016.09.017

Source DB:  PubMed          Journal:  Meat Sci        ISSN: 0309-1740            Impact factor:   5.209


  3 in total

1.  HyTexiLa: High Resolution Visible and Near Infrared Hyperspectral Texture Images.

Authors:  Haris Ahmad Khan; Sofiane Mihoubi; Benjamin Mathon; Jean-Baptiste Thomas And Jon Yngve Hardeberg; Jon Yngve
Journal:  Sensors (Basel)       Date:  2018-06-26       Impact factor: 3.576

Review 2.  A Review on Meat Quality Evaluation Methods Based on Non-Destructive Computer Vision and Artificial Intelligence Technologies.

Authors:  Yinyan Shi; Xiaochan Wang; Md Saidul Borhan; Jennifer Young; David Newman; Eric Berg; Xin Sun
Journal:  Food Sci Anim Resour       Date:  2021-07-01

Review 3.  Non-Destructive Spectroscopic Techniques and Multivariate Analysis for Assessment of Fat Quality in Pork and Pork Products: A Review.

Authors:  Christopher T Kucha; Li Liu; Michael O Ngadi
Journal:  Sensors (Basel)       Date:  2018-01-28       Impact factor: 3.576

  3 in total

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