期刊文献+

不同类群大白猪窝产仔数的遗传分析 被引量:3

Genetic Analysis of Litter Size in Different Large White Lines
下载PDF
导出
摘要 对双肌臀大白猪和普通大白猪组成的 561窝产仔数的资料进行了遗传分析。结果表明 :公猪和胎次均对母猪产仔数 (总产仔数和活产仔数 )具有极显著影响 (P <0 .0 0 1 ) ,季节和类群均对母猪产仔数 (总产仔数和活产仔数 )具有显著影响 (P <0 .0 5)。大白猪产仔数的平均值随胎次增长而增加。夏季分娩的大白猪具有最高的产仔数 ,依次为春季和冬季 ,秋季最低。大白猪总产仔数和活产仔数的遗传力分别为0 .0 9和 0 .1 0 ,属低遗传力 ,直接选择窝产仔数几乎没有效果 ;它们之间的遗传相关为 0 .80 ,表型相关为0 .85,环境相关为 0 .90 ,它们之间的协遗传力为 0 .0 8。这些参数表明总产仔数和活产仔数是两个不同的性状 ,在生产实践中单独记录它们是有理由的、必要的。 Genetic analyses were conducted on the data of 2 populations with 561 litters in Large White pigs.The results indicated that both boar and parity had highly significant(P<0.001)effects on the litter size in sows, both season and line had significant (P<0.05) effects on the litter size in sows. The means of the total number born and the number born alive increased with the increasing parity. The sows farrowing in summer had the highest litter size, while the lowest litter size reached in autumn. The litter size was higher in spring than in winter. The heritability estimates for the total number born and the number born alive were 0.09and 0.10,respectively. Phenotypic,genetic and environmental correlations between the total number born and the number born alive were 0.80,0.85 and 0.90,respectively. The coheritability for the total number born and the number born alive was 0.08. These parameters showed that the total number born and the number born alive were two different traits,that it was reasonable and necessary to independently record them in the production practice.
作者 郭万库
出处 《中国畜牧杂志》 CAS 北大核心 2000年第2期6-8,共3页 Chinese Journal of Animal Science
基金 农业部"948"引进项目!(批准号 962066)
关键词 大白猪 窝产仔猪 遗传分析 胎次 季节 类群 Large White pigs Litter size Genetic analysis
  • 相关文献

参考文献2

二级参考文献76

  • 1Labrinidis A, Jagadish H V. Challenges and opportuni- ties with big data[ J]. Proceedings of the VLDB Endow- ment, 2012, 5(12): 2032-2033.
  • 2Ye Tao, Bickson D, Yan Qiang. Second workshop on large-scale recommender systems: research and best prac- tice [ C ] //J 8'h ACM Conference on Recommender Sys- tems, 2014 ACM. Silicon Valley: ACM Press, 2014: 385 -386.
  • 3Hong Jongyi, Suh E H, Kim J, et al. Contextaware sys- tem for proactive personalized service based on context history [J]. Expert Systems with Applications, 2009, 36 (4) : 7448-7457.
  • 4Pessemier T D, Deryckere T, Martens L. Extending the Bayesian classifier to a context-aware recommender system for mobile devices [ C ]//Internet and Web Applications and Services (ICIW), 2010 Fifth International Confer- ence on IEEE. Barcelona, Spain: IEEE Press, 2010: 242-247.
  • 5Shahabi C, Chen Yishin. An adaptive recommendation system without explicit acquisition of user relevanee feed- back [J]. Distributed and Parallel Databases, 2003, 14 (2) : 173-192.
  • 6Yang Diyi, Chen Tianqi, Zhang Weinan, et al. Local implicit feedback mining for music recommendation [ C 1// the 6th ACM Conference on Recommender Systems, 2012 ACM. Dublin: ACM Press, 2012: 91-98.
  • 7Rafailidis D, Nanopoulos A. Modeling the dynamics of user preferences in coupled tensor factorization [ C ] // the 8'h ACM Conference on Recommender Systems, 2014 ACM. Silicon Valley: ACM Press, 2014: 321- 324.
  • 8Oh K J, Lee W J, Lim C G, et al. Personalized news recommendation using classified keywords to capture user preference [ C ] //16th Advanced Communication Technology (ICACT) , 2014 International Conference on IEEE. South Korea: IEEE Press, 2014: 1283-1287.
  • 9Taktics G, Piltiszy I, N6meth B, et al. Scalable collabo- rative filtering approaches for large recommender systems [ J]. The Journal of Machine Learning Research, 2009, 10(12) : 623-656.
  • 10Bhagat S, Weinsberg U, Loannidis S, et al. Recom- mending with an agenda: active learning of private attributes using matrix factorization [ J]. ArXiv Preprint ArXiv, 2013: 1311-1321.

共引文献469

同被引文献15

引证文献3

二级引证文献11

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部