饲料研究2024，Vol.47Issue(19)：86-90,5.DOI:10.13557/j.cnki.issn1002-2813.2024.19.017
腾冲雪鸡体重与体尺性状的主成分和聚类分析
Principal component analysis and cluster analysis of body weight and body size traits of Tengchong white chickens
摘要
Abstract
The experiment aimed to investigate the correlation between body weight and measurement traits of Tengchong white chickens,as well as their body shape characteristics.The study utilized correlation analysis,principal component analysis,and cluster analysis to examine the body weight and eight morphological indicators of 30 healthy roosters and hens at 300 days of age.The results showed that the average body weights of the Tengchong white chicken roosters and hens were(2 689.33±308.49)g and(2 016.67±351.44)g,respectively,with the roosters'weight being significantly higher than that of the hens(P＜0.05).Except for the chest angle,all other morphological indicators in roosters were significantly greater than those in hens(P＜0.05).Principal component analysis showed that the nine indicators of Tengchong white chickens could be condensed into three principal components,with cumulative contribution rates of 73.962％for roosters and 74.900％for hens.Among the simplified principal components for both sexes,body weight,body diagonal length,shank circumference,keel length,shank length,hip bone width,and chest width contributed the most to the principal components.Cluster analysis categorized the measured indicators of roosters and hens into four clusters.The study indicates that the body size index of Tengchong white chickens is at a medium level among the major local chicken breeds in Yunnan,with larger skeletal structures and superior meat production capabilities,classifying it as a larger breed.The outcomes of this study can serve as a reference for the further selection and breeding of Tengchong white chickens.关键词
腾冲雪鸡/体重/体尺性状/主成分分析/聚类分析Key words
Tengchong white chicken/body weight/body measurement trait/principal component analysis/cluster analysis分类
农业科技引用本文复制引用
蒋发俊,许文坤,梅国栋,范新阳,苗永旺..腾冲雪鸡体重与体尺性状的主成分和聚类分析[J].饲料研究,2024,47(19):86-90,5.基金项目
云南省重大科技专项计划项目(项目编号:202202AE090005) （项目编号:202202AE090005）
国家重点研发计划项目(项目编号:2022YFD1601905) （项目编号:2022YFD1601905）
