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Digital imaging assisted geometry of chicken eggs using Hügelschäffer’s model

Narushin, Valeriy G., Romanov, Michael N, Lu, Gang, Cugley, James, Griffin, Darren K. (2020) Digital imaging assisted geometry of chicken eggs using Hügelschäffer’s model. Biosystems Engineering, 197 . pp. 45-55. ISSN 1537-5110. (doi:10.1016/j.biosystemseng.2020.06.008) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:81946)

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Abstract

Geometrical description of the egg shape is of a great importance in a variety of studies and can be instrumental in predicting quality traits of table and hatching poultry eggs. Importantly, developments of non-destructive oomorphological models can drive novel insights in engineering and physical science and lead to new egg-related technologies and egg sorting systems for poultry industry. We attempted to test the Hügelschäffer’s egg model according to which an egg profile curve can be transformed from an ellipse using a specific parameter w. For this purpose, two-dimensional digital imaging and follow-up image processing techniques of chicken eggs were employed. The formulae for recalculation of the egg volume and surface area were consequently deduced from the Hügelschäffer’s equation. Eventually, we refined the Hügelschäffer’s egg model and proved its applicability for defining the contours of hen’s eggs. For practical use in poultry industry and food engineering, the proposed non-destructive methodology can be contributory in defining accurately the contour of any avian egg and determining such characteristics of the egg shape as volume, surface area, etc., with an expected potential in designing automated systems in poultry industry and in egg-related applications in biology, physical science, engineering and other areas.

Item Type: Article
DOI/Identification number: 10.1016/j.biosystemseng.2020.06.008
Uncontrolled keywords: Egg quality; Non-destructive measurements; Egg volume and surface area; Hügelschäffer’s model; Digital imaging; Image processing
Subjects: Q Science > QH Natural history > QH324.2 Computational biology
S Agriculture > SF Animal culture
T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image processing
Divisions: Divisions > Division of Natural Sciences > School of Biosciences
Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Signature Themes: Food Systems, Natural Resources and Environment
Depositing User: Mike Romanov
Date Deposited: 10 Jul 2020 09:39 UTC
Last Modified: 19 Jul 2021 18:12 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/81946 (The current URI for this page, for reference purposes)
Narushin, Valeriy G.: https://orcid.org/0000-0001-6799-6605
Romanov, Michael N: https://orcid.org/0000-0003-3584-4644
Lu, Gang: https://orcid.org/0000-0002-9093-6448
Griffin, Darren K.: https://orcid.org/0000-0001-7595-3226
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