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首页> 外文期刊>Livestock Science >Genotype by environment interaction for birth and weaning weights of composite beef cattle in different regions of Brazil.
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Genotype by environment interaction for birth and weaning weights of composite beef cattle in different regions of Brazil.

机译:通过环境相互作用对巴西不同地区复合肉牛的出生和断奶体重进行基因分型。

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摘要

The objectives of the present study were to characterize and define homogenous production environments of composite beef cattle in Brazil in terms of climatic and geographic variables using multivariate exploratory techniques and to use them to assess the presence of G x E for birth weight (BW) and weaning weight (WW). Data from animals born between 1995 and 2008 on 36 farms located in 27 municipalities of the Brazilian states were used. Fifteen years of climate observations (mean minimum and maximum annual temperature and mean annual rainfall) and geographic (latitude, longitude and altitude) data were obtained for each municipality where the farms were located for characterization of the production environments. Hierarchical and nonhierarchical cluster analysis was used to group farms located in regions with similar environmental variables into clusters. Six clusters of farms were formed. The effect of sire-cluster interaction was tested by single-trait analysis using deviance information criterion (DIC). Genetic parameters were estimated by multi-trait analysis considering the same trait to be different in each cluster. According to the values of DIC, the inclusion of sire-cluster effect did not improve the fit of the genetic evaluation model for BW and WW. Estimates of genetic correlations among clusters ranged from -0.02 to 0.92. The low genetic correlation among the most studied regions permits us to suggest that a separate genetic evaluation for some regions should be undertaken.Digital Object Identifier http://dx.doi.org/10.1016/j.livsci.2012.07.017
机译:本研究的目的是使用多元探索性技术,根据气候和地理变量来表征和定义巴西复合肉牛的同质生产环境,并利用它们评估出生体重(BW)和体重的G x E的存在。断奶体重(WW)。使用了1995年至2008年之间出生于巴西各州27个城市的36个农场的动物的数据。从农场所在的每个城市获得了十五年的气候观测数据(平均最低和最高年温度以及平均年降雨量)和地理(纬度,经度和海拔)数据,以表征生产环境。层次聚类分析和非层次聚类分析用于将环境变量相似的区域中的农场分组为聚类。形成了六个农场集群。通过使用偏差信息标准(DIC)进行的单性状分析测试了父亲与集群之间的相互作用。通过多性状分析估计遗传参数,考虑到每个集群中相同的性状不同。根据DIC的值,包含父集群效应并不能提高BW和WW遗传评估模型的拟合度。簇之间的遗传相关性估计在-0.02到0.92之间。研究最多的地区之间的遗传相关性低,这使我们建议应该对某些地区进行单独的遗传评估。数字对象标识符http://dx.doi.org/10.1016/j.livsci.2012.07.017

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