华中农业大学学报2026，Vol.45Issue(2)：45-57,13.DOI:10.13300/j.cnki.hnlkxb.2026.02.006
基于关键点检测的前臀鮡表型测量与体质量预测
Measuring phenotype and predicting body weight of Pareuchiloglanis anteanalis based on keypoint detection
摘要
Abstract
A method of automatically measuring the phenotype and predicting the body weight of Pa-reuchiloglanis anteanalis based on the keypoint detection was developed to improve the efficiency of obtain-ing the phenotypic data of P.anteanalis and reduce errors caused by manual measurements.951 images were collected from the ventral,lateral,and dorsal views of P.anteanalis.Keypoints were annotated in the COCO format.Traditional body size including body length,body height,and interorbital distance and index-es of frame distance were calculated based on the coordinates of keypoints.RTMPOSE,LiteHRNet,YO-LOv12n-pose,and YOLOv8n-pose were comparatively evaluated under the same configuration of training,and YOLOv8n-pose was determined to be used for the automatic measurement of phenotypic parameters.Results showed that YOLOv8n-pose had a precision of 94.70%on the test set,with mean relative error(MRE)of 5.45%for phenotypic measurements,and the relative error of most phenotypes was controlled within 10%.Key indexes of phenotype including the distance between pectoral-fin origins(X5),the distance from the pectoral-fin base to the right pelvic-fin base(X7),body height(X10),head length(X12),and inter-orbital distance(X14),were further selected by combining correlation and collinearity analysis to establish a multiple regression model for predicting body-weight,yielding an R² of 0.97 on the test set.It is indicated that the proposed method can achieve automated measurement of phenotype and quantitative estimation of body weight of P.anteanalis.It will provide data support for monitoring growth and evaluating selective breeding of small sisorid freshwater fishes.关键词
前臀鮡/表型测量/计算机视觉/YOLOv8n-pose/关键点检测/体质量预测Key words
Pareuchiloglanis anteanalis/measuring the phenotype/computer vision/YOLOv8n-pose/keypoint detection/prediction of body weight分类
信息技术与安全科学引用本文复制引用
周逸驰,陈彦祥,刘季松,熊皓,苏晓静,杨庆勇,杨瑞斌,郑芳..基于关键点检测的前臀鮡表型测量与体质量预测[J].华中农业大学学报,2026,45(2):45-57,13.基金项目
湖北省支持种业高质量发展资金项目(HBZY2023B009) （HBZY2023B009）
国家自然科学基金项目(31971421) （31971421）
华电集团金沙江上游远期放流鱼种人工繁育技术研究项目(T-2022-04) （T-2022-04）
