Inside the Egg—Demonstrating Provenance Without the Cracking Using Near Infrared Spectroscopy
Several cases of mislabeling of the hen farming system of production on the eggs’ package have been reported by different research groups worldwide. The objective of this study was to evaluate the ability of a portable NIR instrument to classify egg samples non-destructively, from different provenan...
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Veröffentlicht in: | Food analytical methods 2022-11, Vol.15 (11), p.3013-3019 |
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creator | Hoffman, Louw Ni, Dongdong Dayananda, Buddhi AbdulGhafar, Nuratifah Cozzolino, Daniel |
description | Several cases of mislabeling of the hen farming system of production on the eggs’ package have been reported by different research groups worldwide. The objective of this study was to evaluate the ability of a portable NIR instrument to classify egg samples non-destructively, from different provenances or production systems (e.g. cage, cage-free, free-range and organic) in Australia. Intact whole egg samples 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 intact whole egg samples were obtained using a portable NIR spectrophotometer within the 950–1600-nm wavelength range. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to analyse the NIR data. The results obtained in this study indicated that 100% of the egg samples were correctly classified using NIR spectroscopy non-destructively. It was concluded that NIR spectroscopy is a promising tool for the non-invasive, rapid and inexpensive analytical verification of the provenance or the production system of whole egg samples. |
doi_str_mv | 10.1007/s12161-022-02348-6 |
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The objective of this study was to evaluate the ability of a portable NIR instrument to classify egg samples non-destructively, from different provenances or production systems (e.g. cage, cage-free, free-range and organic) in Australia. Intact whole egg samples 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 intact whole egg samples were obtained using a portable NIR spectrophotometer within the 950–1600-nm wavelength range. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to analyse the NIR data. The results obtained in this study indicated that 100% of the egg samples were correctly classified using NIR spectroscopy non-destructively. 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Methods</addtitle><description>Several cases of mislabeling of the hen farming system of production on the eggs’ package have been reported by different research groups worldwide. The objective of this study was to evaluate the ability of a portable NIR instrument to classify egg samples non-destructively, from different provenances or production systems (e.g. cage, cage-free, free-range and organic) in Australia. Intact whole egg samples 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 intact whole egg samples were obtained using a portable NIR spectrophotometer within the 950–1600-nm wavelength range. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to analyse the NIR data. The results obtained in this study indicated that 100% of the egg samples were correctly classified using NIR spectroscopy non-destructively. 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subjects | Analytical Chemistry Cages Chemistry Chemistry and Materials Science Chemistry/Food Science Discriminant analysis Eggs Food Science Infrared spectroscopy Legislation Microbiology Near infrared radiation Portability Principal components analysis Spectrum analysis |
title | Inside the Egg—Demonstrating Provenance Without the Cracking Using Near Infrared Spectroscopy |
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