JOURNAL ARTICLE

A simple way to calculate the volume and surface area of avian eggs.

  • Published In: Annals of the New York Academy of Sciences, 2023, v. 1524, n. 1. P. 118 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Shi, Peijian; Chen, Long; Quinn, Brady K.; Yu, Kexin; Miao, Qinyue; Guo, Xuchen; Lian, Meng; Gielis, Johan; Niklas, Karl J. 3 of 3

Abstract

Egg geometry can be described using Preston's equation, which has seldom been used to calculate egg volume (V) and surface area (S) to explore S versus V scaling relationships. Herein, we provide an explicit re‐expression of Preston's equation (designated as EPE) to calculate V and S, assuming that an egg is a solid of revolution. The side (longitudinal) profiles of 2221 eggs of six avian species were digitized, and the EPE was used to describe each egg profile. The volumes of 486 eggs from two avian species predicted by the EPE were compared with those obtained using water displacement in graduated cylinders. There was no significant difference in V using the two methods, which verified the utility of the EPE and the hypothesis that eggs are solids of revolution. The data also indicated that V is proportional to the product of egg length (L) and maximum width (W) squared. A 2/3‐power scaling relationship between S and V for each species was observed, that is, S is proportional to (LW2)2/3. These results can be extended to describe the shapes of the eggs of other species to study the evolution of avian (and perhaps reptilian) eggs. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Annals of the New York Academy of Sciences. 2023/06, Vol. 1524, Issue 1, p118
  • Document Type:Article
  • Subject Area:Mathematics
  • Publication Date:2023
  • ISSN:0077-8923
  • DOI:10.1111/nyas.15000
  • Accession Number:164438107
  • Copyright Statement:Copyright of Annals of the New York Academy of Sciences is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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