Literature DB >> 27337677

Identification and quantification of turkey meat adulteration in fresh, frozen-thawed and cooked minced beef by FT-NIR spectroscopy and chemometrics.

Cristina Alamprese1, José Manuel Amigo2, Ernestina Casiraghi3, Søren Balling Engelsen2.   

Abstract

This work aims at the development of a method based on FT-NIR spectroscopy and multivariate analysis for the identification and quantification of minced beef meat adulteration with turkey meat. Samples were analyzed as raw, frozen-thawed and cooked. Different multivariate regression and class-modeling strategies were evaluated. PLS regression models with R(2) in prediction higher than 0.884 and RMSEP lower than 10.8% were developed. PLS-DA applied to discriminate each type of sample in two classes (adulteration threshold=20%) showed values of sensitivity and specificity in prediction higher than 0.84 and 0.76, respectively. Thus, the study demonstrates that FT-NIR spectroscopy coupled with suitable chemometric strategies is a reliable tool for the identification and quantification of minced beef adulteration with turkey meat not only in fresh products, but also in frozen-thawed and cooked samples. This achievement is of crucial importance in the meat industry due to the increasing number of processed meat products, in which technological treatments can mask a possible inter-species adulteration.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Beef; Chemometrics; FT-NIR spectroscopy; Meat adulteration; PLS; PLS-DA; Turkey

Mesh:

Year:  2016        PMID: 27337677     DOI: 10.1016/j.meatsci.2016.06.018

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


  11 in total

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Authors:  Giovanni Visco; Susanne H Plattner; Patrizia Fortini; Mariapia Sammartino
Journal:  Environ Sci Pollut Res Int       Date:  2017-04-04       Impact factor: 4.223

2.  Determination of Adulteration of Chicken Meat into Minced Beef Mixtures using Front Face Fluorescence Spectroscopy Coupled with Chemometric.

Authors:  Asima Saleem; Amna Sahar; Imran Pasha; Muhammad Shahid
Journal:  Food Sci Anim Resour       Date:  2022-07-01

3.  Rapid Identification of Rainbow Trout Adulteration in Atlantic Salmon by Raman Spectroscopy Combined with Machine Learning.

Authors:  Zeling Chen; Ting Wu; Cheng Xiang; Xiaoyan Xu; Xingguo Tian
Journal:  Molecules       Date:  2019-08-06       Impact factor: 4.411

4.  Differentiation of South African Game Meat Using Near-Infrared (NIR) Spectroscopy and Hierarchical Modelling.

Authors:  Kiah Edwards; Marena Manley; Louwrens C Hoffman; Anel Beganovic; Christian G Kirchler; Christian W Huck; Paul J Williams
Journal:  Molecules       Date:  2020-04-16       Impact factor: 4.411

5.  Detection of Meat Adulteration Using Spectroscopy-Based Sensors.

Authors:  Lemonia-Christina Fengou; Alexandra Lianou; Panagiοtis Tsakanikas; Fady Mohareb; George-John E Nychas
Journal:  Foods       Date:  2021-04-15

6.  Discrimination of Minced Mutton Adulteration Based on Sized-Adaptive Online NIRS Information and 2D Conventional Neural Network.

Authors:  Zongxiu Bai; Jianfeng Gu; Rongguang Zhu; Xuedong Yao; Lichao Kang; Jianbing Ge
Journal:  Foods       Date:  2022-09-23

Review 7.  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 8.  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

9.  Implementation of Multispectral Imaging (MSI) for Microbiological Quality Assessment of Poultry Products.

Authors:  Evgenia D Spyrelli; Agapi I Doulgeraki; Anthoula A Argyri; Chrysoula C Tassou; Efstathios Z Panagou; George-John E Nychas
Journal:  Microorganisms       Date:  2020-04-11

10.  Performance of Fluorescence and Diffuse Reflectance Hyperspectral Imaging for Characterization of Lutefisk: A Traditional Norwegian Fish Dish.

Authors:  Abdo Hassoun; Karsten Heia; Stein-Kato Lindberg; Heidi Nilsen
Journal:  Molecules       Date:  2020-03-06       Impact factor: 4.411

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