Evaluation of a data-driven youngstock rearing quality system in Dutch dairy herds (2019–2022)

IF 2.2 2区 农林科学 Q1 VETERINARY SCIENCES
Cathérine E. Paarlberg, Anouk Veldhuis, Gustavo E. Monti, Lourens Heres, Thomas Dijkstra, Inge M.G.A. Santman-Berends
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引用次数: 0

Abstract

In recent years, the Netherlands exhibited an increased focus on improving youngstock rearing. Several data-driven tools were developed to assess and benchmark calf rearing practices based on key indicators, stimulate farmers to improve their youngstock rearing and reduce calf mortality. KalfOK is such a data-driven tool in which a farm-level overview with 15 indicators of youngstock rearing quality is communicated to participating farmers. In this study we assessed which farm characteristics are associated with A) a continuously high or low KalfOK score and B) frequent usage of KalfOK. Data from KalfOK and the identification and registration system were available for all participating herds over a period between 2019 and 2022 (Dataset A). Additionally, a sample of 324 dairy farmers, randomly selected from the entire Dutch dairy population (Dataset B), participated in a voluntary survey. Multivariable (logistic) regression models were used to A) identify differences in characteristics between farms with a continuously high- and farms with a continuously low KalfOK score and B) assess which farm characteristics were associated with frequent use of the KalfOK report. The results of analysis A showed multiple factors associated with having a low or high KalfOK score, including replacement rate, closed farming system, limited growth in herd size and the region where a farm was located. Sociological factors might also partly explain the difference between high and low scoring farms. Analysis B showed that approximately half of the surveyed farmers indicated that they do not frequently use their KalfOK overview in their calf rearing management. The KalfOK score of farmers who regularly use their KalfOK report was higher – and consequently better - compared to the KalfOK score of farmers who sometimes or never use KalfOK. Additionally, farmers using a milk robot and those discussing KalfOK regularly with their veterinarian, used KalfOK more often. Thirty four percent of the surveyed farmers made adjustments to their youngstock rearing management since the start of participation. The study’s insights into patterns in KalfOK utilization and associations with farm characteristics provide valuable information for ongoing efforts to enhance calf rearing practices via the use of KalfOK. It is important to consider what is needed to convince farmers that do not use the KalfOK tool to frequently start using their KalfOK report. Future research incorporating sociological aspects can provide a more comprehensive understanding of other dynamics influencing calf rearing and contribute valuable insights for enhancing the effectiveness of programs like KalfOK in promoting calf health and welfare.

荷兰奶牛场数据驱动的幼畜饲养质量系统评估(2019-2022 年)
近年来,荷兰越来越重视改善幼畜饲养。荷兰开发了几种数据驱动工具,根据关键指标对犊牛饲养方法进行评估和设定基准,激励农场主改进幼畜饲养,降低犊牛死亡率。KalfOK 就是这样一种数据驱动工具,其中包含 15 项幼畜饲养质量指标的农场概览将传达给参与的农场主。在本研究中,我们评估了哪些农场特征与 A) KalfOK 分数持续偏高或偏低以及 B) 经常使用 KalfOK 相关。KalfOK 和识别与登记系统提供了 2019 年至 2022 年期间所有参与牧场的数据(数据集 A)。此外,从整个荷兰奶牛场中随机抽取的 324 个奶牛场主样本(数据集 B)参加了自愿调查。多变量(逻辑)回归模型用于:A)确定 KalfOK 分数持续较高的牧场与持续较低的牧场之间的特征差异;B)评估哪些牧场特征与频繁使用 KalfOK 报告有关。分析 A 的结果显示,有多种因素与 KalfOK 分数的高低相关,包括替代率、封闭式养殖系统、牛群规模增长有限以及牧场所在地区。社会因素也可部分解释高分和低分牧场之间的差异。分析 B 显示,约有一半的受访牧场主表示,他们在犊牛饲养管理中并不经常使用 KalfOK 综述。与偶尔或从不使用 KalfOK 的牧场主相比,经常使用 KalfOK 报告的牧场主的 KalfOK 得分更高,因此得分也更高。此外,使用挤奶机器人和定期与兽医讨论 KalfOK 的牧场主使用 KalfOK 的频率更高。34%的受访牧场主自参与研究以来,对其幼畜饲养管理进行了调整。本研究对 KalfOK 的使用模式以及与牧场特征的关联进行了深入分析,为通过使用 KalfOK 不断改进犊牛饲养方法提供了宝贵信息。重要的是要考虑如何说服不使用 KalfOK 工具的农场主经常使用其 KalfOK 报告。结合社会学方面的未来研究可以更全面地了解影响犊牛饲养的其他动态因素,并为提高 KalfOK 等项目在促进犊牛健康和福利方面的有效性提供有价值的见解。
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来源期刊
Preventive veterinary medicine
Preventive veterinary medicine 农林科学-兽医学
CiteScore
5.60
自引率
7.70%
发文量
184
审稿时长
3 months
期刊介绍: Preventive Veterinary Medicine is one of the leading international resources for scientific reports on animal health programs and preventive veterinary medicine. The journal follows the guidelines for standardizing and strengthening the reporting of biomedical research which are available from the CONSORT, MOOSE, PRISMA, REFLECT, STARD, and STROBE statements. The journal focuses on: Epidemiology of health events relevant to domestic and wild animals; Economic impacts of epidemic and endemic animal and zoonotic diseases; Latest methods and approaches in veterinary epidemiology; Disease and infection control or eradication measures; The "One Health" concept and the relationships between veterinary medicine, human health, animal-production systems, and the environment; Development of new techniques in surveillance systems and diagnosis; Evaluation and control of diseases in animal populations.
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