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Reproduction 1

机译:再现1

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摘要

Automated data collection systems were used to identify periods ofincreased activity at estrus and to assess factors affecting the magnitudeand duration of estrous activity. In total, 4,172 estrous periods in1,454 cows across 5 herds in Europe and Canada were studied. Eachherd used automated management systems manufactured by DeLaval(Tumba, Sweden) including a milk progesterone (MP4) measurementand analysis system (Herd Navigator), a body condition scoring system(BCS Camera) and an activity system (DelPro). A “heat alarm” (HA)was defined as 2 consecutive MP4 samples below 5 ng/mL following aluteal phase. Estrus was defined as an increase in activity within 7 d afterHA. Peaks in activity (estrus) were detected with an algorithm and themagnitude (fold change above baseline), duration, and area were determined.Cows were classified according to parity, month, BCS (≤2.75,2.75–3.0, 3.0–3.25, >3.25), days in milk (DIM; ≤56, 57–84, 85–140,and >140), and daily milk production (<40, 40–50, and >50 kg/d) at thetime of HA. Data were analyzed using a mixed model (PROC MIXED;SAS) with animal nested within herd defined as random. There was aneffect of herd (range: 65.7 to 78.7%; P < 0.001), month (range: 69.0%for May–Jun to 78.7% for Nov-Dec; P < 0.002) and BCS (range: 70.0%for ≤2.75 to 77.1% for >3.25; P < 0.004) on the percentage of cows withan activity peak after HA. Neither DIM, parity, nor milk affected peakdetection. For cows with an activity peak, the peak area was affected byherd (P < 0.001), DIM (P < 0.001), month (P < 0.001) and BCS (P <0.001). Differences in peak area were primarily associated with greaterpeak duration and not peak magnitude. Peak duration (h) differed forherds (range: 16.9 ± 0.3 to 19.2 ± 0.2; P < 0.001), DIM (range: 17.4 ±0.2 for ≤56 to 19.3 ± 0.3 for >140; P < 0.001), month (range: 17.3 ± 0.3for May–June to 19.1 ± 0.2 for Nov-Dec) and BCS (range: 17.6 ± 0.3for ≤2.75 to 18.9 ± 0.2 for >3.25; P < 0.001). Neither parity nor milkaffected peak area or duration. Conclusions were that estrous activity isaffected by herd, season (lowest in summer), BCS (lowest in low BCScows) and DIM (lowest in early lactation cows).
机译:自动数据收集系统用于识别期间增加了雌雄的活动,并评估影响幅度的因素和持续时间的发言活动。总共有4,172个修饰时期研究了欧洲和加拿大的5个牛群的1,454股牛。每个牛群使用了脱挥瓦制造的自动化管理系统(Tumba,Sweden)包括牛奶孕酮(MP4)测量和分析系统(牛群导航仪),一个体重评分系统(BCS相机)和活动系统(Delpro)。 “热警报”(HA)被定义为2以下的连续MP4样品5. a以下低于5 ng / ml黄体期。 estrus被定义为后7 d内的活动增加哈。用算法和算法检测活动中的峰值(雌激)确定幅度(折叠变化高于基线),持续时间和区域。根据奇偶,月,BCS(≤2.75,2.75-3.0,3.0-3.25,> 3.25),牛奶天(昏暗;≤56,57-84,85-140,和> 140),每日牛奶生产(<40,40-50,和> 50千克/ d)哈的时间。使用混合模型进行分析数据(Proc混合;SAS)用动物嵌入牧群中定义随机。有一个牛群的影响(范围:65.7至78.7%; P <0.001),月份(范围:69.0%12月6日至12月至78.7%; P <0.002)和BCS(范围:70.0%> 3.25的≤2.75至77.1%; p <0.004)对奶牛的百分比HA后的活性峰值。既不昏暗,平价,也不是牛奶影响峰值检测。对于具有活动峰的奶牛,峰面积受到影响牛群(p <0.001),暗淡(p <0.001),月份(p <0.001)和bcs(p <0.001)。峰面积的差异主要与大关相关峰值持续时间而不是峰值幅度。峰值持续时间(h)不同牛群(范围:16.9±0.3至19.2±0.2; P <0.001),昏暗(范围:17.4±±0.2≤56至19.3±0.3,> 140; P <0.001),月(范围:17.3±0.32010年6月至6月至12月12.1±0.2,11月)和BCS(范围:17.6±0.3对于> 3.25,≤2.75至18.9±0.2; p <0.001)。既不是平等也不是牛奶受影响的峰面积或持续时间。结论是发言活动是受牧群,季节(夏季最低),BCS(低BCS中最低)奶牛)和昏暗(早期哺乳奶牛中最低)。

著录项

  • 来源
    《Journal of dairy science》 |2019年第suppla期|113-116|共4页
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  • 收录信息 美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
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  • 正文语种 eng
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