Graduate Student Literature Review: Social and feeding behavior of group-housed dairy calves in automated milk feeding systems*

IF 3.7 1区 农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE Journal of Dairy Science Pub Date : 2024-07-01 DOI:10.3168/jds.2023-23745
Maria E. Montes, Jacquelyn P. Boerman
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Abstract

Automated milk feeders (AMF) allow farmers to raise calves in groups while generating individual records on milk consumption, drinking speed, and frequency of visits. Calves raised in groups benefit from social interaction, which facilitates learning and adapting to novelty. However, calves in large groups (>12 calves/feeder) experience a higher risk of disease transmission and competition than those housed individually or in smaller groups. Therefore, if group size, grouping strategy, and disease detection are not optimal, the health and performance of calves can be compromised. The objectives of this narrative literature review, from publications available as of February 2023, are to (1) describe the use of AMF in group housing systems for calves and the associated feeding behavior variables they automatically collect, (2) linking feeding behavior collected from AMF to disease risk in calves, (3) describe research on social behavior in AMF systems, and (4) introduce social networks as a promising tool for the study of social behavior and disease transmission in group-housed AMF-fed calves. Existing research suggests that feeding behavior measures from AMF can assist in detecting bovine respiratory disease and enteric disease, which are common causes of morbidity and mortality for preweaning dairy heifers. Automated milk feeder records show reduced milk intake, drinking speed, or frequency of visits when calves are sick. However, discrepancies exist among published research about the sensitivity of feeding behavior measures as indicators of sickness, likely due to differences in feeding plans and disease-detection protocols. Therefore, considering the influence of milk allowance, group density, and individual variation on the analysis of AMF data is essential to derive meaningful information used to inform management decisions. Research using dynamic social networks derived from precision data show potential for the use of social network analysis to understand disease transmission and the effect of disease on social behavior of group-housed calves.

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研究生文献综述:自动牛奶饲喂系统中群居乳牛的社交和饲喂行为。
自动喂奶器(AMF)使牧场主能够分组饲养犊牛,同时生成有关牛奶消耗量、饮水速度和访问频率的个人记录。分组饲养的犊牛受益于社会交往,这有利于学习和适应新事物。然而,与单独饲养或较小群体饲养的犊牛相比,大群体饲养的犊牛(大于 12 头犊牛/饲喂器)面临的疾病传播和竞争风险更高。因此,如果群体规模、分组策略和疾病检测不理想,犊牛的健康和表现就会受到影响。本叙述性文献综述来自截至 2023 年 2 月的出版物,目的在于1)描述在犊牛群居系统中使用AMF的情况及其自动收集的相关饲养行为变量;2)将从AMF中收集的饲养行为与犊牛的疾病风险联系起来;3)描述AMF系统中社会行为的研究;4)介绍社会网络作为研究群居AMF饲养犊牛的社会行为和疾病传播的一种有前途的工具。现有研究表明,AMF 的饲养行为测量有助于检测牛呼吸道疾病(BRD)和肠道疾病(ED),这两种疾病是导致断奶前乳牛发病和死亡的常见原因。AMF记录显示,犊牛生病时,采奶量、饮水速度或就诊频率都会下降。然而,可能由于饲喂计划和疾病检测规程的不同,已发表的研究对作为疾病指标的饲喂行为测量的敏感性存在差异。因此,考虑到奶量、群体密度和个体差异对AMF数据分析的影响,对于获得用于管理决策的有意义的信息至关重要。利用从精确数据中得出的动态社会网络进行的研究表明,利用社会网络分析(SNA)了解疾病传播以及疾病对群居犊牛社会行为的影响具有潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Dairy Science
Journal of Dairy Science 农林科学-奶制品与动物科学
CiteScore
7.90
自引率
17.10%
发文量
784
审稿时长
4.2 months
期刊介绍: The official journal of the American Dairy Science Association®, Journal of Dairy Science® (JDS) is the leading peer-reviewed general dairy research journal in the world. JDS readers represent education, industry, and government agencies in more than 70 countries with interests in biochemistry, breeding, economics, engineering, environment, food science, genetics, microbiology, nutrition, pathology, physiology, processing, public health, quality assurance, and sanitation.
期刊最新文献
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