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Standardized data in the broiler value chain

机译：肉鸡价值链中的标准化数据

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In the Dutch broiler chain, data are collected as a routine practice. However, there is wide variation in the content of data collected and in data collection systems. This variability hampers the use of field data in management information systems to support decisions. The objective of this study was to analyze the quality of data and to standardize the content of data sets in the broiler production chain. To evaluate the quality of data, data sets from 3 Dutch hatcheries, from 23,637 batches of eggs, were assessed. The quality of data was assessed intuitively based on 7 quality attributes. To standardize the content of the data set, a protocol was proposed and validated. The protocol was validated at 30 breeder farms, 3 hatcheries, and 104 broiler farms by using 3 quality attributes: consistency, uniformity, and completeness. Results of the data quality analysis of the 3 Dutch hatcheries showed that the data sets had some fields with inaccurate, incorrect, inconsistent, nonuniform, incomprehensible, missing relevant, or incomplete data. Results of the validation protocol were as follows: feedback was obtained from 23 (77%) breeder farms, 3 (100%) hatcheries, and 7 (7%) broiler farms. Of all the questions, on average 88% were answered on breeder farms; 57, 65, and 82% were answered at each of the 3 hatcheries, respectively; and 79% were answered on the broiler farms. Data collected at 2 hatcheries were more consistent than those collected at the third hatchery. Hatchery data were less consistent than breeder farm data, but the number of data entries at hatcheries far exceeded the number at the farm level. Data from the hatcheries, breeder farms, and broiler farms were not always uniform, possibly because of differences in management strategies. This protocol enables the listing of relevant and standard contents of a data set whereby information exchange along the chain can be simplified. However, it is recommended that the protocol be supplemented with some rules for data collection and management, for example, that variables must be recorded in the provided fields, and that a variable must have one and only one name or code, the same unit of measurement, and the same definition.
机译：在荷兰肉鸡链中，数据是按惯例收集的。但是，收集的数据内容和数据收集系统存在很大差异。这种可变性妨碍了在管理信息系统中使用现场数据来支持决策。这项研究的目的是分析数据的质量并使肉鸡生产链中的数据集标准化。为了评估数据的质量，评估了来自3个荷兰孵化场的23637批卵的数据集。根据7个质量属性直观地评估了数据质量。为了标准化数据集的内容，提出并验证了协议。通过使用3个质量属性：一致性，均匀性和完整性，该协议已在30个育种场，3个孵化场和104个肉鸡场得到验证。 3个荷兰孵化场的数据质量分析结果表明，这些数据集的某些字段具有不准确，不正确，不一致，不统一，无法理解，缺少相关或不完整的数据。验证协议的结果如下：从23个（77％）种鸡场，3个（100％）孵化场和7个（7％）肉鸡场获得了反馈。在所有问题中，平均88％在种猪场得到回答; 3个孵化场分别有57％，65％和82％被回答;在肉鸡场中回答了79％。在两个孵化场收集的数据比在第三个孵化场收集的数据更加一致。孵化场数据的一致性不如育种场数据，但是孵化场的数据条目数量远远超过了养殖场级别的数量。孵化场，种鸡场和肉鸡场的数据并不总是一致的，可能是由于管理策略的差异。该协议可以列出数据集的相关内容和标准内容，从而可以简化沿链的信息交换。但是，建议在协议中补充一些数据收集和管理规则，例如，必须将变量记录在提供的字段中，并且变量必须具有唯一的名称或代码，且必须使用相同的单位。测量，并且定义相同。

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