中国水产科学2026，Vol.33Issue(5)：23-33,11.DOI:10.12264/JFSC2026-0134
基于三维模型的棕点石斑鱼多维表型解析方法研究
A multi-dimensional phenotypic analysis method for Epinephelus fuscoguttatus based on 3D models
摘要
Abstract
Fish phenotypic data serve as the foundational basis for intelligent breeding in aquaculture.Modern breeding technologies—such as genomic selection and genome-wide association study—require phenotypic data of greater dimensionality and precision.Conventional manual measurements and two-dimensional image analysis are limited to obtaining a small set of one-dimensional size parameters,which cannot adequately represent the rich morphological information of fish as three-dimensional entities.To address this,a method for three-dimensional phenotypic analysis of fish was developed based on multi-view 3D reconstruction.Multi-view images of the fish body were captured using a rotating three-camera system.Dense point clouds were reconstructed via a structure-from-motion algorithm,followed by the conversion of these point clouds into structured 3D data through the following steps:PCA-based orientation standardization,surface meshing,midline extraction,and cross-sectional slicing.Multi-dimensional phenotypic parameters were then extracted at three levels:(1)3D geometric traits,(2)basic dimensional traits and(3)high-dimensional morphological traits.Validation experiments conducted on 30 individuals of Epinephelus fuscoguttatus demonstrated a 100%success rate in 3D reconstruction.Measurements of total length and body height exhibited high agreement with manual measurements(TL:R2=0.9939;BH:R2=0.9648).The prediction accuracy of body mass using point cloud-derived volume(R2=0.94)was significantly higher than that achieved with conventional total length alone(R2=0.81).Additionally,cross-sectional morphological profiles along the body midline revealed shape pattern variations among individuals with different condition factors,which could not be detected using traditional size-based measurements.In conclusion,the proposed method extends the phenotypic characterization of fish from a handful of conventional one-dimensional size parameters to high-dimensional morphological information—encompassing 3D geometry and along-axis shape variation.This offers a norval phenotypic data foundation for advancing intelligent breeding practices in aquaculture.关键词
鱼类三维表型/多视角三维重建/点云分析/形态解析/智能育种Key words
fish 3D phenotyping/multi-view 3D reconstruction/point cloud analysis/morphological analysis/intelligent breeding分类
农业科技引用本文复制引用
陈雨泽,麻志宏,刘鹰,戚云辉..基于三维模型的棕点石斑鱼多维表型解析方法研究[J].中国水产科学,2026,33(5):23-33,11.基金项目
海南省种业实验室科技计划项目(B24H10035). （B24H10035）
