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WhoseEgg: classification software for invasive carp eggs

Authors :
Katherine Goode
Michael J. Weber
Philip M. Dixon
Source :
PeerJ, Vol 11, p e14787 (2023)
Publication Year :
2023
Publisher :
PeerJ Inc., 2023.

Abstract

The collection of fish eggs is a commonly used technique for monitoring invasive carp. Genetic identification is the most trusted method for identifying fish eggs but is expensive and slow. Recent work suggests random forest models could provide an inexpensive method for identifying invasive carp eggs based on morphometric egg characteristics. While random forests provide accurate predictions, they do not produce a simple formula for obtaining new predictions. Instead, individuals must have knowledge of the R coding language, limiting the individuals who can use the random forests for resource management. We present WhoseEgg: a web-based point-and-click application that allows non-R users to access random forests via a point and click interface to rapidly identify fish eggs with an objective of detecting invasive carp (Bighead, Grass, and Silver Carp) in the Upper Mississippi River basin. This article provides an overview of WhoseEgg, an example application, and future research directions.

Details

Language :
English
ISSN :
21678359
Volume :
11
Database :
Directory of Open Access Journals
Journal :
PeerJ
Publication Type :
Academic Journal
Accession number :
edsdoj.285fa4bd4797409ea7f58c44324f2179
Document Type :
article
Full Text :
https://doi.org/10.7717/peerj.14787