HUBEI AGRICULTURAL SCIENCES ›› 2021, Vol. 60 ›› Issue (9): 102-105.doi: 10.14088/j.cnki.issn0439-8114.2021.09.019

• Animal Husbandry & Veterinary Medicine • Previous Articles     Next Articles

Principal component analysis of carcass traits of yak under standardized production conditions

WU Jin-bo1, HE Shi-ming1, LI Zhu1, WANG Tai1, JIAN Shang-lin2, TA Ying3, TAN Ben-xu3   

  1. 1. Institute of Animal Science and Technology of Aba Tibetan and Qiang Autonomous Prefecture,Hongyuan 624402,Sichuan,China;
    2. Animal Husbandry Workstation of Aba Tibetan and Qiang Autonomous Prefecture,Barkam 624099,Sichuan,China;
    3. Animal Disease Prevention and Control Center of Ngawa Tibetan and Qiang Autonomous prefecture,Barkam 624099,Sichuan,China
  • Received:2020-04-13 Published:2021-05-14

Abstract: In order to explore the difference and correlation of yak laughter traits under standardized production conditions, we selected 15 Maiwa yaks and 15 Jinchuan yaks which with similar age and weight, then all the animals were slaughtered after breeding 100 days. 11 slaughter traits such as were determined and analyzed statistically. The results showed that the spleen weight of Maiwa yak was 0.75 kg, higher than that of Jinchuan yak (0.57 kg), and the difference was significant (P<0.01), while the other indicators showed no significant difference (P>0.05). The variation coefficients of liver weight and kidney weight in Maiwa yak were 11.28% and 14.81%, respectively, and those in Jinchuan yak were 12.39% and 11.76%, respectively, which suggesting that these two indexes have breeding potential. Three principal components were identified by principal component analysis, and the cumulative contribution rate was up to 70.844%. The first principal component could reflect the weight of yaks, the second principal component could reflect the development of spleen and liver of yaks, and the third principal component could reflect the kidney weight of yaks.

Key words: standardized production, yak, slaughter performance, principle component analysis

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