Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 561571
Title Integration of handheld NIR and machine learning to “Measure & Monitor” chicken meat authenticity
Author(s) Parastar, Hadi; Kollenburg, Geert van; Weesepoel, Yannick; Doel, André van den; Buydens, Lutgarde; Jansen, Jeroen
Source Food Control 112 (2020). - ISSN 0956-7135
DOI https://doi.org/10.1016/j.foodcont.2020.107149
Department(s) BU Authenticity & Bioassays
Publication type Refereed Article in a scientific journal
Publication year 2020
Keyword(s) Chemometrics - Ensemble learning - Handheld NIR - Meat authenticity
Abstract

By combining portable, handheld near-infrared (NIR) spectroscopy with state-of-the-art classification algorithms, we developed a powerful method to test chicken meat authenticity. The research presented shows that it is both possible to discriminate fresh from thawed meat, based on NIR spectra, as well as to correctly classify chicken fillets according to the growth conditions of the chickens with good accuracy. In all cases, the random subspace discriminant ensemble (RSDE) method significantly outperformed other common classification methods such as partial least squares-discriminant analysis (PLS-DA), artificial neural network (ANN) and support vector machine (SVM) with classification accuracy of >95%. This study shows that handheld NIR coupled with machine learning algorithms is a useful, fast, non-destructive tool to identify the authenticity of chicken meat. By comparing and combining different protocols to measure the NIR spectra (i.e., through packaging and directly on meat), we show the possibilities for both consumers and food inspection authorities to check the authenticity and origin of packaged chicken fillet.

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