GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet-Tolosan, France.
SELMET, INRAE CIRAD, Montpellier SupAgro, Université Montpellier, Montpellier, France.
Animal. 2023 Jun;17(6):100845. doi: 10.1016/j.animal.2023.100845. Epub 2023 May 5.
In situations of negative energy balance (NEB) due to feed scarcity or high physiological demands, body energy reserves (BRs), mainly stored in adipose tissues, become the main sources of energy for ruminants. The capacity to mobilise and restore such BRs in response to different challenges is of major concern in the current context of breeding for resilience. Body condition score (BCS) is a common, practical indicator of BR variations throughout successive productive cycles, and quantitative tools for characterising such dynamics at the individual level are still lacking. The main objective of this work was to characterise body condition dynamics in terms of BR mobilisation and accretion capacities of meat sheep during their productive lifespan through a modelling approach, using BCS measurements. The animal model used in this work was the reproductive meat ewe (n = 1 478) reared in extensive rangeland. Regular measurements of BCS for each productive cycle were used as the indicator of BR variations. A hybrid mathematical model and a web interface, called PhenoBR, were developed to characterise ewes' BCS variations through four synthetic and biologically meaningful parameters for each productive cycle i: BR accretion rate (k), BR mobilisation rate (k), plus the time of onset and the duration of the BR mobilisation, t and ΔT, respectively. The model PhenoBR converged for all the ewes included in the analysis. Estimation of the parameters indicated the inter-individual variability for BR accretion and mobilisation rates, and the length of the mobilisation period. The present study is a proof of concept that the combination of data-driven and concept-driven models is required for the estimation of biologically meaningful parameters that describe body reserve dynamics through consecutive productive cycles. Individual characterisation of animals by these parameters makes it possible to rank them for their efficiency in the use of body reserves when facing NEB challenges. Such parameters could contribute to better management and decision-making by farmers and advisors, e.g. by adapting feeding systems to the individual characteristics of BR dynamics, or by geneticists as criteria to develop future animal breeding programmes including BR dynamics for more robust and resilient animals.
在因饲料短缺或高生理需求导致负能量平衡(NEB)的情况下,身体能量储备(BR),主要存储在脂肪组织中,成为反刍动物的主要能量来源。在当前培育弹性的背景下,动员和恢复这些 BR 的能力是一个主要关注点。体况评分(BCS)是反映连续生产周期中 BR 变化的常用实用指标,但个体水平上描述这种动态的定量工具仍然缺乏。本工作的主要目的是通过使用 BCS 测量值的建模方法,从 BR 动员和积累能力的角度来描述肉用绵羊在其生产寿命内的体况动态。本工作中使用的动物模型是在广泛的牧场上饲养的繁殖肉用母羊(n=1478)。每个生产周期的 BCS 定期测量用作 BR 变化的指标。开发了一种混合数学模型和一个名为 PhenoBR 的网络界面,用于通过每个生产周期的四个综合且具有生物学意义的参数来描述母羊的 BCS 变化:BR 积累率(k)、BR 动员率(k)、BR 动员的起始时间和持续时间,分别为 t 和ΔT。用于分析的所有母羊的模型 PhenoBR 都收敛了。参数估计表明 BR 积累和动员率以及动员期的个体间变异性。本研究证明了数据驱动和概念驱动模型的结合对于估计通过连续生产周期描述身体储备动态的具有生物学意义的参数是必要的。通过这些参数对动物进行个体特征描述,使得可以根据它们在面临 NEB 挑战时使用身体储备的效率对其进行排名。这些参数可以为农民和顾问提供更好的管理和决策依据,例如通过根据 BR 动态的个体特征来调整饲养系统,或者遗传学家可以将其作为开发包括 BR 动态的未来动物育种计划的标准,以培育更健壮和有弹性的动物。