REPRODUCTIVE TRAITS SELECTION IN NELORE BEEF CATTLE

Author:

Moreira Heverton Luis1,Buzanskas Marcos Eli2,Munari Danisio Prado2,Canova Érika Breda1,Lôbo Raysildo Barbosa3,Paz Claudia Cristina Paro de1

Affiliation:

1. Agência Paulista de Tecnologia dos Agronegócios/APTA, Brazil

2. Universidade Estadual Paulista Júlio de Mesquita Filho/UNESP, Brazil

3. Universidade de São Paulo/USP, Brazil

Abstract

Genetic breeding programs of beef cattle in Brazil are including new features, mainly related to reproductive efficiency.Thus, it is necessary to study the effectiveness of selection and quantify genetic gain for these traits in herds. This study estimated genetic and phenotypic parameters and genetic trends for reproductive traits used in breeding programs for Nelore beef cattle. The traits studied were the scrotal circumference (SC) at 365 and 450 days of age (SC365 and SC450), age at first calving (AFC) and gestation length, as a cow trait (GLcow) and a calf trait (GLcalf). The (co)variance components were obtained with the Restricted Maximum Likelihood Methodology in a single and double-trait analysis of the animal model. For scrotal circumference (SC365 and SC450), positive and favorable genetic gains were observed. For AFC, GLcow and GLcalf, the trends were favorable for selection, but without significant genetic gain. Selection for large SC may reduce AFC and improve female reproductive efficiency. The selection for reproductive traits (SC365, SC450, AFC and GL) may improve reproductive and productive efficiency of Nelore cattle, if used as a selection criterion.

Publisher

FapUNIFESP (SciELO)

Subject

Soil Science,General Veterinary,Agronomy and Crop Science,Animal Science and Zoology,Food Science

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3