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Unscrambling the Provenance of Eggs by Combining Chemometrics and Near-Infrared Reflectance Spectroscopy

Authors :
Louwrens Christiaan Hoffman
Dongdong Ni
Buddhi Dayananda
N Abdul Ghafar
Daniel Cozzolino
Source :
Sensors, Vol 22, Iss 13, p 4988 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

Issues related to food authenticity, traceability, and fraud have increased in recent decades as a consequence of the deliberate and intentional substitution, addition, tampering, or misrepresentation of food ingredients, where false or misleading statements are made about a product for economic gains. This study aimed to evaluate the ability of a portable NIR instrument to classify egg samples sourced from different provenances or production systems (e.g., cage and free-range) in Australia. Whole egg samples (n: 100) were purchased from local supermarkets where the label in each of the packages was used as identification of the layers’ feeding system as per the Australian legislation and standards. The spectra of the albumin and yolk were collected using a portable NIR spectrophotometer (950–1600 nm). Principal component analysis (PCA) and linear discriminant analysis (LDA) were used to analyze the NIR data. The results obtained in this study showed how the combination of chemometrics and NIR spectroscopy allowed for the classification of egg albumin and yolk samples according to the system of production (cage and free range). The proposed method is simple, fast, environmentally friendly and avoids laborious sample pre-treatment, and is expected to become an alternative to commonly used techniques for egg quality assessment.

Details

Language :
English
ISSN :
14248220
Volume :
22
Issue :
13
Database :
Directory of Open Access Journals
Journal :
Sensors
Publication Type :
Academic Journal
Accession number :
edsdoj.75a1396b92cb4a418164c8ef3346d02d
Document Type :
article
Full Text :
https://doi.org/10.3390/s22134988