Development of automated phenotyping system for growth traits in bivalves

Bivalves are economically important aquaculture species, contributing to over half of the maricultural production in China. Improving growth rate has been a central focus in bivalve breeding to enhance the farming yield. Accurate and efficient phenotyping is critical for the breeding and revealing t...

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Main Authors: Xiangfu Kong, Shanhuan Huang, Xuangang Wang, Haoying Liang, Chen Hu, Yujue Wang, Zhenmin Bao, Xiaoli Hu
Format: Article
Language:English
Published: Elsevier 2025-10-01
Series:Aquaculture Reports
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Online Access:http://www.sciencedirect.com/science/article/pii/S2352513425004053
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Summary:Bivalves are economically important aquaculture species, contributing to over half of the maricultural production in China. Improving growth rate has been a central focus in bivalve breeding to enhance the farming yield. Accurate and efficient phenotyping is critical for the breeding and revealing the genetic basis of traits. Traditionally, growth traits in bivalves were measured manually using vernier caliper and scales, a method to inaccuracies and is time-consuming, adversely affecting the accuracy of breeding parent selection and slowing genetic improvement. In this study, we developed an automated phenotyping system for growth trait measurements, which integrates 3D laser imaging, dynamic weighing, sorting, and barcode reading platform. The 3D laser imaging platform enables accurate measurement of body size parameters (shell height, length, width, area and circumference) within 1.2 s per individual, with measurement error ranging from 0.01 to 0.30 mm. The weighing platform demonstrates an accuracy exceeding 99 % for bivalves moving at 1.0 m/s. Additionally, the sorting platform enables automatic sorting of individuals based on size and weight, achieving 100 % accuracy. Individual marking and identification method were also incorporated to efficiently record sample information and monitor growth traits of individuals. The whole system handles each sample in just 1.6 s, operating at a speed approximately 11 times faster than conventional manual methods, and it is capable of handling over two thousand bivalve samples per hour. In conclusion, this system provides a rapid and accurate approach for measuring growth traits, sorting, and automatically identifying bivalves, making it a valuable platform for bivalve phenotyping and breeding.
ISSN:2352-5134