Predicting Egg Storage Time with a Portable Near-Infrared Instrument: Effects of Temperature and Production System

Author:

Cozzolino Daniel1ORCID,Sanal Pooja2,Schreuder Jana3ORCID,Williams Paul James3ORCID,Assadi Soumeh Elham2ORCID,Dekkers Milou Helene4,Anderson Molly4,Boisen Sheree4,Hoffman Louwrens Christiaan13ORCID

Affiliation:

1. Centre for Nutrition and Food Sciences, Queensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia

2. School of Agriculture and Food Sustainability, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia

3. Food Science Department, Stellenbosch University, Private Bag X1, Matieland, Stellenbosch 7602, South Africa

4. Queensland Animal Science Precinct (QASP), The University of Queensland, Gatton Campus, St. Lucia, Brisbane, QLD 4072, Australia

Abstract

Determining egg freshness is critical for ensuring food safety and security and as such, different methods have been evaluated and implemented to accurately measure and predict it. In this study, a portable near-infrared (NIR) instrument combined with chemometrics was used to monitor and predict the storage time of eggs under two storage conditions—room temperature (RT) and cold (CT) storage—from two production systems: cage and free-range. A total of 700 egg samples were analyzed, using principal component analysis (PCA) and partial least squares (PLS) regression to analyze the NIR spectra. The PCA score plot did not show any clear separation between egg samples from the two production systems; however, some egg samples were grouped according to storage conditions. The cross-validation statistics for predicting storage time were as follows: for cage and RT eggs, the coefficient of determination in cross validation (R2CV) was 0.67, with a standard error in cross-validation (SECV) of 7.64 days and residual predictive deviation (RPD) of 1.8; for CT cage eggs, R2CV of 0.84, SECV of 5.38 days and RPD of 3.2; for CT free-range eggs, R2CV of 0.83, SECV of 5.52 days and RPD of 3.2; and for RT free-range eggs, R2CV of 0.82, SECV of 5.61 days, and RPD of 3.0. This study demonstrated that NIR spectroscopy can predict storage time non-destructively in intact egg samples. Even though the results of the present study are promising, further research is still needed to further extend these results to other production systems, as well as to explore the potential of this technique to predict other egg quality parameters associated with freshness.

Funder

Internal University of Queensland

Publisher

MDPI AG

Subject

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

Reference46 articles.

1. Burley, R.W., and Vadehra, D.V. (1989). The Avian Egg: Chemistry and Biology, John Wiley & Sons.

2. (2023, December 10). Australian Eggs. Available online: https://www.australianeggs.org.au/nutrition/health-benefits.

3. Stadelman, W.J., Newkirk, D., and Newby, L. (2017). Egg Science and Technology, CRC Press.

4. Methods to evaluate egg freshness in research and industry: A review;Karoui;Eur. Food Res. Technol.,2006

5. Non-destructive optical sensing technologies for advancing the egg industry toward Industry 4.0: A review;Ahmed;Compr. Rev. Food Sci. Food Saf.,2023

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