Comparison of Multiple NIR Spectrometers for Detecting Low-Concentration Nitrogen-Based Adulteration in Protein Powders.

chemometrics food fraud handheld NIRS melamine near-infrared spectroscopy quality control whey protein

Journal

Molecules (Basel, Switzerland)
ISSN: 1420-3049
Titre abrégé: Molecules
Pays: Switzerland
ID NLM: 100964009

Informations de publication

Date de publication:
08 Feb 2024
Historique:
received: 29 11 2023
revised: 01 02 2024
accepted: 04 02 2024
medline: 24 2 2024
pubmed: 24 2 2024
entrez: 24 2 2024
Statut: epublish

Résumé

Protein adulteration is a common fraud in the food industry due to the high price of protein sources and their limited availability. Total nitrogen determination is the standard analytical technique for quality control, which is incapable of distinguishing between protein nitrogen and nitrogen from non-protein sources. Three benchtops and one handheld near-infrared spectrometer (NIRS) with different signal processing techniques (grating, Fourier transform, and MEM-micro-electro-mechanical system) were compared with detect adulteration in protein powders at low concentration levels. Whey, beef, and pea protein powders were mixed with a different combination and concentration of high nitrogen content compounds-namely melamine, urea, taurine, and glycine-resulting in a total of 819 samples. NIRS, combined with chemometric tools and various spectral preprocessing techniques, was used to predict adulterant concentrations, while the limit of detection (LOD) and limit of quantification (LOQ) were also assessed to further evaluate instrument performance. Out of all devices and measurement methods compared, the most accurate predictive models were built based on the dataset acquired with a grating benchtop spectrophotometer, reaching R

Identifiants

pubmed: 38398532
pii: molecules29040781
doi: 10.3390/molecules29040781
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Matyas Lukacs (M)

Department of Food Measurement and Process Control, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences, 1118 Budapest, Hungary.

John-Lewis Zinia Zaukuu (JZ)

Department of Food Science & Technology, Kwame Nkrumah University of Science & Technology, Kumasi-Ghana 00233, Ghana.

George Bazar (G)

CORRELTECH Laboratory, ADEXGO Kft., 1222 Budapest, Hungary.

Bernhard Pollner (B)

Independent Researcher, 6020 Innsbruck, Austria.

Marietta Fodor (M)

Department of Food and Analytical Chemistry, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences, 1118 Budapest, Hungary.

Zoltan Kovacs (Z)

Department of Food Measurement and Process Control, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences, 1118 Budapest, Hungary.

Classifications MeSH