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Mob-based walk-over weights: similar to the average of individual static weights?

机译:基于生物的步行权重:类似于单个静态权重的平均值?

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Merino ewe liveweight represents an objective measure shown to have a profound effect on production outcomes and therefore research into technology that provides accurate and timely feedback of ewe liveweight change is warranted. Most sheep in Australia are not individually identified and therefore management of sheep is on a flock or 'mob' basis. Mob-based walk-over weighing (MBWOW) is a remote weighing concept for sheep flocks whereby animal weights are collected as they pass freely over a strategically placed weighing platform. The weights are then collected by the livestock manager, analysed and interpreted to aid nutritional decision making on a whole-flock basis. The hypothesis tested in this study was that data from MBWOW systems is comparable to data from static weighing sessions. At three sites, MBWOW data was collected simultaneously with monthly static weighing sessions. Raw data from MBWOW from each site was manipulated through a series of methodologies that were compared according to their relationship with the static weight data. All forms of MBWOW data showed a significant relationship with static weighing data (P<0.05). Using a 25% filter (data within 25% of a predetermined central weight kept) and grouping data into 5-day groups strengthens the relationship between MBWOW data and static weighing data. In 1-day groupings, MBWOW data with a 25% filter and subjectively chosen central weight showed the strongest relationship (R2=0.89) with static weighing data. In 5-day groupings, MBWOW data with a 25% filter and reference weight from a previous weighing event as a central weight showed the strongest relationship (R2=0.88) to static weighing data. The former MBWOW data manipulation methodology had the least mean numerical difference (+or-s.d.) between MBWOW data and static weighing data (1.86+or-0.85 kg), yet the latter had the least mean numerical difference in change-in MBWOW data and change-in static weighing data (1.51+or-0.39 kg), and as change-in liveweight has the most application to industry, it is recommend as the preferred data manipulation technique. These findings suggest that although MBWOW is not fully congruent with static weighing, a strong relationship (R2
机译:美利奴羊母羊活体重代表了一种对生产结果有深远影响的客观指标,因此,有必要对能提供准确及时的母羊活体重变化反馈的技术进行研究。在澳大利亚,大多数绵羊没有单独识别,因此,绵羊的管理是基于羊群或“暴民”。基于生物的步行式称重(MBWOW)是一种用于羊群的远程称重概念,通过该称重,动物体重可以自由地经过战略性放置的称重平台,从而进行收集。然后由家畜管理员收集重量,进行分析和解释,以帮助整个鸡群进行营养决策。在这项研究中检验的假设是,MBWOW系统的数据与静态称重会话的数据可比。在三个站点上,MBWOW数据与每月静态称重会话同时收集。来自每个站点的MBWOW的原始数据通过一系列方法进行操作,根据它们与静态权重数据之间的关系进行比较。所有形式的MBWOW数据均与静态称重数据具有显着相关性( P <0.05)。使用25%的过滤器(保留的数据不超过预先确定的中心重量的25%)并将数据分组为5天的分组可增强MBWOW数据与静态称量数据之间的关系。在1天分组中,具有25%过滤器和主观选择的中心权重的MBWOW数据与静态称重数据之间显示出最强的关系( R 2 = 0.89)。在5天分组中,具有25%过滤器的MBWOW数据和前一次称重事件的参考权重作为中心权重,与( R 2 = 0.88)之间的关系最强静态称重数据。前者MBWOW数据处理方法在MBWOW数据和静态称重数据之间(1.86+或-0.85 kg)具有最小的平均数值差(+或-sd),而后者在输入的MBWOW数据和换入式静态称重数据(1.51+或-0.39 kg),并且由于换入式活重在工业上应用最多,因此建议将其作为首选的数据处理技术。这些发现表明,尽管MBWOW与静态称量并不完全一致,但两者之间的关系很强( R 2

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