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首页> 外文期刊>Canadian Journal of Animal Science >Optimizing feed intake recording and feed efficiency estimation to increase the rate of genetic gain for feed efficiency in beef cattle
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Optimizing feed intake recording and feed efficiency estimation to increase the rate of genetic gain for feed efficiency in beef cattle

机译：优化进料进口记录和饲料效率估计，以提高牛肉牛饲料效率的遗传增益速率

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摘要

Data from a total of 4842 animals were used to test whether the regular dry matter intake (DMI) data collection and residual feed intake (RFI) estimation period could be decreased. Eighty-three shortened test periods were compared with the regular test period, and the results showed that the DMI data collection period could be decreased to 42 d without significantly compromising accuracy of feed efficiency testing. Competency of the selected shorter period (42 d with 30-42 d of valid feed intake days) to predict regular test period DMI (84 d with 60-84 d of valid feed intake days) was tested using a set of agreements criteria. The results showed that the selected shorter period can be used to accurately and precisely predict regular test DMI. The selected shorter test period combined with regular body weight measurements were used to estimate RFI adjusted for backfat (RFIfat). Assessment of agreement between estimated values for RFIfat showed that a shorter DMI test could be used to predict RFIfat with only 7% outside the range prediction. It is concluded that shortening the feed intake period to 42 d from 84 d could substantially increase power-of-the-test for experiments that target feed intake or efficiency and reduce per head cost with the current infrastructure.
机译：总共4842只动物的数据用于测试常规干物质摄入（DMI）数据收集和残留饲料摄入量（RFI）估计期间是否可以减少。将八十三次缩短的测试期与常规测试期进行比较，结果表明，DMI数据收集期可降低至42d，而不是显着损害饲料效率测试的准确性。使用一组协议标准测试所选较短时期的所选较短时期（具有30-42天的有效进料摄入日的有效进料摄入天）的能力进行了测试，以预测常规测试期DMI（带有60-84天的有效进料进口量）。结果表明，所选择的较短时期可用于准确且精确地预测常规测试DMI。所选择的较短测试期与常规体重测量相结合用于估计用于背部饮料（RFIFAT）的RFI。 RFIFAT的估计值之间的协议评估表明，较短的DMI测试可用于预测RFIFAT，仅在范围预测外的7％。得出结论，从84d缩短进料进口到42d至42d可以显着提高试验的功率，以便对当前基础设施进行目标进料或效率并降低每个头部成本的实验。

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