Non-destructive method for whole-egg freshness inspection in food manufacturing
Keywords:
Egg-freshness inspection, Food manufacturing, Image processingAbstract
Importance of the work: Expired eggs can ruin an entire batch in the food industry; however, under current practice, only a subset of the eggs is randomly tested for freshness.
Objectives: To develop a non-destructive testing method for full egg-freshness inspection based on the analysis of the yolk movement speed.
Materials and Methods: Experiments were conducted on eggs from three farms, with storage periods ranging from 1 to 14 days. The inspection apparatus incorporated image processing with the traditional candle testing method and consisted of egg holder hardware and a vision system. A camera was used to capture yolk images that were subsequently used to calculate the yolk movement speed. From the literature review, it was found that the viscosity of egg whites decreases as the storage duration of eggs increases. Consequently, the egg yolk moves more rapidly over time. This study utilizes this principle to assess the freshness of eggs.
Results: The storage period increased the average yolk movement speed. With storage for up to 6 d, the yolk movement speed of the tested eggs was similar (16.3 mm/s on average), to 7–8 d of storage (25.4 mm/s), with a slight increase after 9–13 d. After 14 d of storage, the average yolk movement speed was 31.4 mm/s or approximately twice that of the fresh eggs. The results were verified based on other benchmarked methods.
Main finding: The proposed method was verified as a non-destructive method for egg-freshness inspection. A full-inspection system could be developed and integrated into the manufacturing process.
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Copyright (c) 2025 online 2452-316X print 2468-1458/Copyright © 2025. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/), production and hosting by Kasetsart University Research and Development Institute on behalf of Kasetsart University.online 2452-316X print 2468-1458/Copyright © 2022. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/),
production and hosting by Kasetsart University of Research and Development Institute on behalf of Kasetsart University.