畜牧与饲料科学 ›› 2022, Vol. 43 ›› Issue (6): 64-67.doi: 10.12160/j.issn.1672-5190.2022.06.011

• 动物遗传与繁育 • 上一篇    下一篇

苏尼特羊体重与体尺的相关性分析

辛满喜1,特日格勒2,王国庆3,纳钦4,何小龙2   

  1. 1.内蒙古自治区锡林郭勒盟畜牧工作站,内蒙古 锡林浩特 026000
    2.内蒙古自治区农牧业科学院,内蒙古 呼和浩特 010031
    3.内蒙古农业大学动物科学学院,内蒙古 呼和浩特 010018
    4.内蒙古自治区农牧业技术推广中心,内蒙古 呼和浩特 010011
  • 收稿日期:2022-09-26 出版日期:2022-11-30 发布日期:2022-12-19
  • 通讯作者: 何小龙(1983—),男,研究员,博士,硕士生导师,主要研究方向为绵羊遗传育种与繁殖。
  • 作者简介:辛满喜(1980—),男,高级畜牧师,主要从事畜牧业技术推广与研究工作。
  • 基金资助:
    内蒙古自治区科技重大专项(2020ZD0003);内蒙古自治区农牧业科学院创新基金项目(2018CXJJM01)

Correlation Analysis between Body Weight and Body Size of Sunit Sheep

XIN Man-xi1,Terigele 2,WANG Guo-qing3,Naqin 4,HE Xiao-long2   

  1. 1. Animal Husbandry Working Station of Xilin Gol League of Inner Mongolia,Xilinhot 026000,China
    2. Inner Mongolia Academy of Agricultural and Animal Husbandry Sciences,Hohhot 010031,China
    3. College of Animal Science,Inner Mongolia Agricultural University,Hohhot 010018,China
    4. Inner Mongolia Agricultural and Animal Husbandry Technology Promotion Center,Hohhot 010011,China
  • Received:2022-09-26 Online:2022-11-30 Published:2022-12-19

摘要:

[目的]分析内蒙古自治区锡林郭勒盟地方特色肉羊品种苏尼特羊体重与体尺指标的关联程度。[方法]随机选取5~6月龄发育及健康状况良好的苏尼特羊公羊247只、母羊260只,对羊只的体重(Y)、尾长(X1)、尾宽(X2)、体高(X3)、体长(X4)、胸围(X5)进行生产性能测定,数据整理后使用SPSS 26.0统计学软件对体重与体尺指标进行相关性分析和多元线性回归分析,最终建立最优回归模型。[结果]影响苏尼特羊公羊和母羊体重的主要体尺指标为尾宽、体高、体长和胸围,且与体重均呈极显著(P<0.01)相关;逐步回归分析建立了多元线性回归模型,公羊的最优线性方程为:Y=0.57X5+0.325X4+0.241X2-35.795,R2=0.834;母羊的最优线性方程为:Y=0.577X5+0.246X4+0.205X2-31.94,R2=0.799。[结论]回归方程中胸围、体长、尾宽与体重相关性均较高,皆可作为苏尼特羊的体重预测模型。

关键词: 苏尼特羊, 体重, 体尺, 相关性分析, 模型

Abstract:

[Objective] This study was conducted to analyze the correlation between body weight and body size indexes of Sunit sheep, a local distinctive mutton sheep breed in Xilin Gol League of Inner Mongolia, China. [Method] A total of 247 Sunit rams and a total of 260 Sunit ewes aged 5 to 6 months with good development and health condition were randomly selected, and the indexes potentially associated with production performance including body weight (Y), tail length (X1), tail width (X2), body height (X3), body length (X4) and chest circumference (X5) were measured. Following data processing, SPSS 26.0 software was used to perform correlation analysis and multiple linear regression analysis on the body weight and body size indexes. The best regression model was then established. [Result] The main body size indexes affecting the body weights of Sunit rams and ewes were tail width, body height, body length and chest circumference, which were all extremely significantly (P<0.01) correlated with the body weight. A multiple linear regression model was established by stepwise regression analysis. The optimal linear equation of Sunit ram was: Y=0.57X5+0.325X4+0.241X2-35.795, R2=0.834; the optimal linear equation of Sunit ewe was: Y=0.577X5+0.246X4+0.205X2-31.94, R2=0.799. [Conclusion] The body size indexes of chest circumference, body length and tail width had high correlation with body weight in the regression equation, and all of them could be used as the prediction indicators for body weight.

Key words: Sunit sheep, body weight, body size, correlation analysis, model

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