Optimisation Of On-farm Technologies To Predict Health And Resilience In Dairy Calves

优化农场技术以预测奶牛的健康和弹性

• 批准号: BB/W020459/1
• 负责人: Jasmeet Kaler
• 金额: $ 25.06万
• 依托单位: University of Nottingham
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FW020459%2F1
• 关键词: Optimisation; farm; Technologies; Predict; Health

Currently there are no accurate digital tools with decision support to predict calf health and production. Our approach is highly novel as it uses cutting-edge data techniques to develop and use novel features from various calf behaviours (various activities, social networks, feeding, play) and physiology (temperature both core and eye) captured by technologies (automatic feeders, activity location sensors, bolus, thermal cameras) and on-farm data to predict health and production and welfare indicator as play. We will optimise the use of technologies by identifying which information is of value and by conducting a comparative evaluation of the technologies w.r.t their predictive accuracy. Our approach is different and extends the use of technologies for the first-time to accurately measure and quantify dynamic indicators of resilience in 3 states (behavioural, physiological and production) in calves. Through implementation of a "Living Lab" (LL; first for dairy), a user-centric research methodology for prototyping, refining and validating IoT solutions, the results will inform decision support for farmers. It's timely as results allow optimal and novel use of current technologies and through our consortium involving multiple stakeholders, including commercial partners, we are best placed to exploit these outcomes.Translation and applicability: The algorithms we will develop in the project will help farmers by providing early disease detection for calves, measures of positive welfare (play) for the herd and predicting production outcomes - these will be of value to both farmers and vets for calf management decisions. The outcome and knowledge of feature importance from different technologies in prediction and their comparative evaluation is of huge value to farmers, vets (for choice and adoption) and wider industry (for innovation). Routes to translation and impact will be via our consortium and hosting of LL workshops during the project lifetime with various stakeholders and through our extensive existing networks. Using technologies to measure resilience has the added value in that it could promote their embedment in decision support and drive the uptake of technology on farms. This can help farmers and vets to identify animals that are vulnerable and predict how they are likely to respond to a future stressor and have a measure of herd resilience. Our results have applicability to other livestock sectors with digital tools.Next steps: Our longer-term aim (5 yr) plan will be to further validate the findings from this study, link to lifetime resilience and improve our understanding of early-life conditions that support the development and expression of these markers of resilience in calves. To understand which management interventions enhance resilience and how these markers could be incorporated in breeding programmes. A comprehensive validated resilience index will support a paradigm shift and move the focus from mere disease management to a more holistic and dynamic view of animal health.

目前还没有具有决策支持的准确数字工具来预测犊牛健康和生产。我们的方法非常新颖，因为它使用尖端的数据技术来开发和使用技术（自动喂食器、活动位置传感器、推注、热像仪）和农场数据来预测健康、生产和福利指标。我们将通过识别哪些信息有价值并对技术及其预测准确性进行比较评估来优化技术的使用。我们的方法有所不同，首次扩展了技术的使用，以准确测量和量化犊牛 3 种状态（行为、生理和生产）的弹性动态指标。通过实施“生活实验室”（LL；第一个乳制品实验室），这是一种以用户为中心的研究方法，用于原型设计、完善和验证物联网解决方案，其结果将为农民提供决策支持。这是及时的，因为结果允许对当前技术进行最佳和新颖的利用，并且通过我们涉及多个利益相关者（包括商业合作伙伴）的联盟，我们最有能力利用这些成果。翻译和适用性：我们将在该项目中开发的算法将通过提供犊牛的早期疾病检测、牛群积极福利（玩耍）的衡量以及预测生产结果 - 这些对于农民和兽医的犊牛管理决策都很有价值。不同技术的预测结果和特征重要性知识及其比较评估对于农民、兽医（用于选择和采用）和更广泛的行业（用于创新）具有巨大价值。转化和影响的途径将通过我们的联盟以及在项目生命周期内与各个利益相关者一起主办的 LL 研讨会以及通过我们广泛的现有网络来实现。使用技术来衡量复原力具有附加值，因为它可以促进其在决策支持中的嵌入并推动农场对技术的采用。这可以帮助农民和兽医识别脆弱的动物，并预测它们可能如何应对未来的压力源，并衡量牛群的恢复能力。我们的结果适用于其他畜牧业的数字工具。下一步：我们的长期目标（5 年）计划将是进一步验证这项研究的结果，与终生复原力联系起来，并提高我们对早期生命状况的理解，支持犊牛这些复原力标志物的发展和表达。了解哪些管理干预措施可以增强复原力以及如何将这些标记纳入育种计划。经验证的综合复原力指数将支持范式转变，并将重点从单纯的疾病管理转移到更全面、更动态的动物健康观点。

项目成果

Familiarity, age, weaning and health status impact social proximity networks in dairy calves.

• DOI: 10.1038/s41598-023-29309-1
• 发表时间: 2023-02-08
• 期刊: SCIENTIFIC REPORTS
• 影响因子: 4.6
• 作者: Vazquez-Diosdado, Jorge A.;Occhiuto, Francesca;Carslake, Charles;Kaler, Jasmeet
• 通讯作者: Kaler, Jasmeet

Evidence of personality-dependent plasticity in dairy calf movement behaviours derived from automated data collection.

• DOI: 10.1038/s41598-023-44957-z
• 发表时间: 2023-10-25
• 期刊: SCIENTIFIC REPORTS
• 影响因子: 4.6
• 作者: Occhiuto, Francesca;Vazquez-Diosdado, Jorge A.;King, Andrew J.;Kaler, Jasmeet
• 通讯作者: Kaler, Jasmeet

Indication of a personality trait in dairy calves and its link to weight gain through automatically collected feeding behaviours.

• DOI: 10.1038/s41598-022-24076-x
• 发表时间: 2022-11-12
• 期刊: SCIENTIFIC REPORTS
• 影响因子: 4.6
• 作者: Carslake, Charles;Occhiuto, Francesca;Vazquez-Diosdado, Jorge A.;Kaler, Jasmeet
• 通讯作者: Kaler, Jasmeet

Personality and predictability in farmed calves using movement and space-use behaviours quantified by ultra-wideband sensors.

• DOI: 10.1098/rsos.212019
• 发表时间: 2022-06
• 期刊: Royal Society open science
• 影响因子: 3.5