Non-Destructive Classification of Organic and Conventional Hens’ Eggs Using Near-Infrared Hyperspectral Imaging

Author:

Sahachairungrueng Woranitta1,Thompson Anthony Keith2,Terdwongworakul Anupun3,Teerachaichayut Sontisuk4

Affiliation:

1. Department of Food Science, School of Food-Industry, King Mongkut’s Institute of Technology Ladkrabang, Chalongkrung Road, Ladkrabang, Bangkok 10520, Thailand

2. Department of Postharvest Technology, Cranfield University, College Road, Cranfield, Bedford MK43 0AL, UK

3. Department of Agricultural Engineering, Faculty of Engineering at Kamphaeng Saen, Kasetsart University, Kamphaeng Saen, Nakhon Pathom 73140, Thailand

4. Department of Food Process Engineering, School of Food-Industry, King Mongkut’s Institute of Technology Ladkrabang, Chalongkrung Road, Ladkrabang, Bangkok 10520, Thailand

Abstract

Eggs that are produced using organic methods retail at higher prices than those produced using conventional methods, but they cannot be differentiated reliably using visual methods. Eggs can therefore be fraudulently mislabeled in order to increase their wholesale and retail prices. The objective of this research was therefore to test near-infrared hyperspectral imaging (NIR-HSI) to identify whether an egg has been produced using organic or conventional methods. A total of 210 organic and 210 conventional fresh eggs were individually scanned using NIR-HSI to obtain absorbance spectra for discrimination analysis. The physical properties of each egg were also measured non-destructively in order to analyze the performance of discrimination compared with those of the NIR-HSI spectral data. Principal component analysis (PCA) showed variation for PC1 and PC2 of 57% and 23% and 94% and 4% based on physical properties and the spectral data, respectively. The best results of the classification using NIR-HSI spectral data obtained an accuracy of 96.03% and an error rate of 3.97% via partial least squares–discriminant analysis (PLS-DA), indicating the possibility that NIR-HSI could be successfully used to rapidly, reliably, and non-destructively differentiate between eggs that had been produced using organic methods from eggs that had been produced using conventional methods.

Funder

King Mongkut’s Institute of Technology Ladkrabang

Publisher

MDPI AG

Subject

Plant Science,Health Professions (miscellaneous),Health (social science),Microbiology,Food Science

Reference62 articles.

1. Campmajo, G., Cayero, I., Saurina, J., and Nunez, O. (2019). Classification of hen eggs by HPLC-UV fingerprinting and chemometric methods. Foods, 8.

2. FAO (2022, November 14). Crops and Livestock Products. Available online: https://www.fao.org/faostat/en/#data/QCL/visualize.

3. McDougal, T. (2022, June 29). Global Egg Production Continues to Rise. Available online: https://www.poultryworld.net/Eggs/Articles/2020/6/Global-egg-production-continues-to-rise-604164E/.

4. Sun, D.W. (2009). Infrared Spectroscopy for Food Quality Analysis and Control, Elsevier Science.

5. Wang, X., Son, M., Meram, C., and Wu, J. (2019). Mechanism and potential of egg consumption and egg bioactive components on Type-2 diabetes. Nutrients, 11.

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