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Development and evaluation of a dynamic simulation model of reproductive performance in pasture based suckler beef systems
Agricultural Systems ( IF 6.6 ) Pub Date : 2020-06-01 , DOI: 10.1016/j.agsy.2020.102797
R. Lynch , A.K. Kelly , D.A. Kenny , P. Crosson

The reproductive performance of a beef cow herd is largely a factor of efficient animal management strategies and genetics. The complex and cumulative nature of individual management decisions on a farm system's performance over multiple years mean that robust evaluation is time consuming and costly. A dynamic deterministic simulation model (Grange Reproductive Management Model; GReMM) with the capacity to replicate herd inventory dynamics over multiple reproductive cycles was developed using the Stella Architect dynamic modelling platform. The model is representative of a pasture-based spring calving suckled beef cow herd and is initialised by specifying individual farm parameters with respect to reproductive management, such as the breeding season duration, nutrition and management of the cow and calf postpartum. The focus was on the key factors which affect the duration of the postpartum anoestrus interval (PPAI); body condition score of the cow at calving (BCSc), postpartum nutrition (PPN), access of the suckling calf to the dam and, exposure of the dam to a fertile male. Model output was displayed in the form of a shift in calving distribution, the number of calves produced per cow bred per year and, percentage of cows culled due to barrenness. Three management scenarios were investigated to represent a herd implementing current industry best practice (BASE), a herd implementing intensive levels of reproductive management (Intensive reproductive management; IRM) and a herd implementing poor levels of reproductive management (Poor reproductive management; PRM). When evaluated in terms of calving distribution over six production cycles, both PRM and IRM showed a shift in the calving spread with a higher proportion of animals calving earlier and later, respectively, in the calving season compared to the BASE. This resulted in a 5% increase and a 14% decrease in six-week calving rates relative to BASE by year six, for IRM and PRM, respectively. Correspondingly, culling rates due to barrenness reduced by 0.9% and increased by 3.3% relative to BASE for IRM and PRM, respectively. The model developed offers a realistic and intuitive dynamic simulation model capable of investigating practical on-farm management decisions on herd reproductive performance.

中文翻译:

牧场乳肉牛系统繁殖性能动态模拟模型的开发与评价

肉牛群的繁殖性能在很大程度上是有效的动物管理策略和遗传学的一个因素。对农场系统多年绩效的个人管理决策的复杂性和累积性意味着稳健的评估既费时又费钱。使用 Stella Architect 动态建模平台开发了一个动态确定性仿真模型(Grange Reproductive Management Model;GReMM),能够在多个繁殖周期内复制畜群库存动态。该模型代表以牧场为基础的春季产犊乳牛群,并通过指定与繁殖管理相关的个别农场参数进行初始化,例如繁殖季节持续时间、母牛和小牛产后的营养和管理。重点关注影响产后无动情期(PPAI)持续时间的关键因素;母牛在产犊时的身体状况评分 (BCSc)、产后营养 (PPN)、乳牛与母牛的接触以及母牛与可育雄性的接触。模型输出以产犊分布变化的形式显示,每头奶牛每年生产的小牛数量以及因不育而被淘汰的奶牛百分比。对三种管理方案进行了调查,分别代表实施当前行业最佳实践 (BASE) 的牛群、实施集约化繁殖管理水平的牛群(集约化繁殖管理;IRM)和实施低水平繁殖管理的牛群(不良繁殖管理;PRM)。根据六个生产周期的产犊分布进行评估时,与 BASE 相比,PRM 和 IRM 都显示了产犊分布的变化,产犊季节中较早和较晚产犊的动物比例分别更高。这导致到第六年,IRM 和 PRM 的六周产犊率相对于 BASE 分别增加 5% 和减少 14%。相应地,与 BASE 相比,IRM 和 PRM 导致的不育淘汰率分别降低了 0.9% 和增加了 3.3%。开发的模型提供了一个现实和直观的动态模拟模型,能够研究关于畜群繁殖性能的实际农场管理决策。这导致到第六年,IRM 和 PRM 的六周产犊率相对于 BASE 分别增加 5% 和减少 14%。相应地,与 BASE 相比,IRM 和 PRM 导致的不育淘汰率分别降低了 0.9% 和增加了 3.3%。开发的模型提供了一个现实和直观的动态模拟模型,能够研究关于畜群繁殖性能的实际农场管理决策。这导致到第六年,IRM 和 PRM 的六周产犊率相对于 BASE 分别增加 5% 和减少 14%。相应地,与 BASE 相比,IRM 和 PRM 导致的不育淘汰率分别降低了 0.9% 和增加了 3.3%。开发的模型提供了一个现实和直观的动态模拟模型,能够研究关于畜群繁殖性能的实际农场管理决策。
更新日期:2020-06-01
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