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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author Xiangfu Kong
Shanhuan Huang
Xuangang Wang
Haoying Liang
Chen Hu
Yujue Wang
Zhenmin Bao
Xiaoli Hu
author_facet Xiangfu Kong
Shanhuan Huang
Xuangang Wang
Haoying Liang
Chen Hu
Yujue Wang
Zhenmin Bao
Xiaoli Hu
author_sort Xiangfu Kong
collection DOAJ
description 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.
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spelling doaj-art-9ebf03c20c4e4a0b856d82eba6b530772025-08-20T03:57:58ZengElsevierAquaculture Reports2352-51342025-10-014410301910.1016/j.aqrep.2025.103019Development of automated phenotyping system for growth traits in bivalvesXiangfu Kong0Shanhuan Huang1Xuangang Wang2Haoying Liang3Chen Hu4Yujue Wang5Zhenmin Bao6Xiaoli Hu7Ministry of Education Key Laboratory of Marine Genetics and Breeding, College of Marine Life Science, Ocean University of China, Qingdao 266003, ChinaMinistry of Education Key Laboratory of Marine Genetics and Breeding, College of Marine Life Science, Ocean University of China, Qingdao 266003, ChinaMinistry of Education Key Laboratory of Marine Genetics and Breeding, College of Marine Life Science, Ocean University of China, Qingdao 266003, ChinaMinistry of Education Key Laboratory of Marine Genetics and Breeding, College of Marine Life Science, Ocean University of China, Qingdao 266003, ChinaMinistry of Education Key Laboratory of Marine Genetics and Breeding, College of Marine Life Science, Ocean University of China, Qingdao 266003, ChinaMinistry of Education Key Laboratory of Marine Genetics and Breeding, College of Marine Life Science, Ocean University of China, Qingdao 266003, ChinaMinistry of Education Key Laboratory of Marine Genetics and Breeding, College of Marine Life Science, Ocean University of China, Qingdao 266003, China; Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao Marine Science and Technology Center, Qingdao, Shandong 266237, ChinaMinistry of Education Key Laboratory of Marine Genetics and Breeding, College of Marine Life Science, Ocean University of China, Qingdao 266003, China; Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao Marine Science and Technology Center, Qingdao, Shandong 266237, China; Corresponding author at: Ministry of Education Key Laboratory of Marine Genetics and Breeding, College of Marine Life Science, Ocean University of China, Qingdao 266003, China.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.http://www.sciencedirect.com/science/article/pii/S2352513425004053BivalvesGrowth trait measurementSortingIndividual identificationAutomatic phenotyping system
spellingShingle Xiangfu Kong
Shanhuan Huang
Xuangang Wang
Haoying Liang
Chen Hu
Yujue Wang
Zhenmin Bao
Xiaoli Hu
Development of automated phenotyping system for growth traits in bivalves
Aquaculture Reports
Bivalves
Growth trait measurement
Sorting
Individual identification
Automatic phenotyping system
title Development of automated phenotyping system for growth traits in bivalves
title_full Development of automated phenotyping system for growth traits in bivalves
title_fullStr Development of automated phenotyping system for growth traits in bivalves
title_full_unstemmed Development of automated phenotyping system for growth traits in bivalves
title_short Development of automated phenotyping system for growth traits in bivalves
title_sort development of automated phenotyping system for growth traits in bivalves
topic Bivalves
Growth trait measurement
Sorting
Individual identification
Automatic phenotyping system
url http://www.sciencedirect.com/science/article/pii/S2352513425004053
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