Erfassung der Futteraufnahme im Rahmen der Stationsprüfung potentieller Besamungsbullen

Author:

Wassmuth R.,Alps H.

Abstract

Abstract. Title ofthe paper: Recording of feed intake in stationary testing of potential AI bulls This study was performed in order to estimate correlations between feed intake, eating time and daily gain in young bulls and in order to estimate genetic parameters for feed intake in successive testing periods aiming at reduction of costs for testing. Data were collected from 269 Station tested potential AI bulls of German Holstein. In the testing period beginning with the 112th and ending with the 312 day of life, bulls consumed 5.1 kg roughage in 125 minutes per day and increased their weight by 1,300 g daily. The heritability of feed intake was 0.42, of eating behaviour 0.40 and of daily gain 0.62. Between feed intake and eating behaviour no relationship could be observed. Hence, an indirect measurement of feed intake is not possible. The high genetic correlation between feed intake and daily gain of 0.96 is no reason to replace feed intake recording because of a promising relationship between feed intake and health of dairy cows. Because of a delayed Start of 32 % of all tested bulls a shortening of the test period should be orientated to the last testing periods. In the last testing period, the heritability of feed intake was 0.65 and the genetic correlation between feed intake in the last and in the whole test period was high with 0.88. Hence, the test period could be shortened favouring intake measurements between 263rd and 312th day of life.

Publisher

Copernicus GmbH

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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