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Spatial dynamics of the Girolando breed in Brazil: analysis of genetic integration and environmental factors

机译:巴西吉尔索多品种的空间动力学:遗传整合与环境因素分析

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Brazil is one of the world's largest milk producers. Several scientific studies have been developed related to landscape analyses that combine genetic with landscape structure data. In the present study, we aimed to analyze the relationship between genetic, environmental, and socioeconomic aspects of production in Girolando cattle in Brazil, as well as verify the spatial patterns of its genetic diversity. Genetic values and accuracy of 46,289 animals were used as well as information from DNA of 310 Girolando animals. Canonic, discriminant, and cluster analyses were conducted in SAS (R) and K-means method in ArcGIS 10.3 software. The relationship between genetic and geographic distance was analyzed using different methods in software Alleles in Space (R). Clusters with animals with higher genetic values for milk production are located in municipalities with lower gross domestic product, fewer family-based establishments, and lower human development index. These clusters are associated with regions with higher area planted with crops, lower percentage of pastures that were less degraded, higher humidity, lower temperature range, and lower normalized difference vegetation index (NDVI) values. The greater the geographical distance between groups of animals, the greater the genetic distance between them with a significant distinction over 504 km. There is high genetic heterogeneity among animals. From these results, it will be possible to develop methodologies for better evaluation of the animals within the production systems.
机译:巴西是世界上最大的牛奶生产商之一。已经制定了几个科学研究与景观分析相关,将遗传分析与景观结构数据相结合。在本研究中,我们旨在分析巴西吉隆索牛生产遗传,环境和社会经济方面的关系,以及验证其遗传多样性的空间模式。使用46,289只动物的遗传值和准确性以及来自310个吉隆索动物的DNA的信息。在ArcGIS 10.3软件中以SAS(R)和K-MERIC方法在SAS(R)和K-MERIC方法中进行统计,判别和群集分析。在空间(R)中的软件等位基因中,分析了遗传和地理距离之间的关系。具有较高粮食生产遗传价值的动物的簇位于国内生产总值较低的市内,基于家庭的家庭的机构较少,人类发展指数降低。这些簇与具有作物种植更高的区域的区域有关,较低的牧场百分比较低,湿度较高,较低的温度范围,较低的归一化差异植被指数(NDVI)值。动物组之间的地理距离越大,它们之间的遗传距离越大,超过504公里。动物之间存在高遗传异质性。通过这些结果,可以制定用于更好地评估生产系统内的动物的方法。

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