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构建一个机械模型以描述瘤胃中颗粒流出的动态过程,并预测奶牛中饲草颗粒的通过速率。

Development of a mechanistic model to represent the dynamics of particle flow out of the rumen and to predict rate of passage of forage particles in dairy cattle.

作者信息

Seo S, Lanzas C, Tedeschi L O, Pell A N, Fox D G

机构信息

Department of Animal Science, Cornell University, Ithaca, NY 14853, USA.

出版信息

J Dairy Sci. 2009 Aug;92(8):3981-4000. doi: 10.3168/jds.2006-799.

DOI:10.3168/jds.2006-799
PMID:19620682
Abstract

A mechanistic and dynamic model was developed to represent physiological aspects of particle dynamics in the reticulo-rumen (RR) and to predict rate of passage out of the RR (Kp) of forage particles quantitatively. The model consists of 2 conceptual pools with 3 spatial compartments of particles; the compartment the particle enters is based on functional specific gravity (FSG). The model assumes 2 major pressure gradient-driven flows of particles out of the RR through the reticulo-omasal orifice between 2 consecutive primary reticular contractions. One is associated with the second phase of primary reticular contraction and involves propulsion of particles in the vicinity of the honeycomb structure of the reticulum from the RR. The second flow involves movement of particles in the reticulum without selection by size. Particle outflow rate was assumed to be proportional to liquid outflow rate. The passage coefficient, defined as the ratio of particle to liquid outflow rate, was estimated for each particle group by an equation derived from the probability of passage based on FSG and particle size. Particles retained on a 1.18-mm screen were defined as large particles. When the model was evaluated with 41 observations in an independent database, it explained 66% of the variation in observed Kp of forage particles with a root mean square prediction error of 0.009. With 16 observations that also included measurements of liquid passage rate, the model explained 81 and 86% of the variation in observed Kp liquid and Kp forage, respectively. An analysis of model predictions using a database with 455 observations indicated that the assumptions underlying the model seemed to be appropriate to describe the dynamics of forage particle flow out of the RR. Sensitivity analysis showed that probability of a particle being in the pool likely to escape is most critical in the passage of large forage particles, whereas the probability of being in the reticulum as well as in the likely to escape pool is important in the passage of small forage and concentrate particles. The FSG of a particle is more important in determining the fate of a particle than its size although they are correlated, especially for forage particles. We conclude that this model can be used to understand the factors that affect the dynamics of particle flow out of the RR and predict Kp of particles out of the RR in dairy cattle.

摘要

建立了一个机械动力学模型,以描述瘤网胃(RR)中颗粒动力学的生理方面,并定量预测饲草颗粒从RR排出的速率(Kp)。该模型由2个概念池和3个颗粒空间隔室组成;颗粒进入的隔室基于功能比重(FSG)。该模型假设在两次连续的初级网状收缩之间,有两种主要的压力梯度驱动颗粒通过瘤网口从RR流出。一种与初级网状收缩的第二阶段相关,涉及从RR推进网状蜂巢结构附近的颗粒。第二种流动涉及网状结构中颗粒的移动,而不按大小进行选择。颗粒流出速率假定与液体流出速率成正比。通过基于FSG和颗粒大小的通过概率推导的方程,为每个颗粒组估计定义为颗粒与液体流出速率之比的通过系数。保留在1.18毫米筛网上的颗粒定义为大颗粒。当使用独立数据库中的41个观测值对模型进行评估时,它解释了饲草颗粒观测Kp中66%的变异,均方根预测误差为0.009。对于16个还包括液体通过率测量的观测值,该模型分别解释了观测到的Kp液体和Kp饲草中81%和86%的变异。使用包含455个观测值的数据库对模型预测进行的分析表明,模型所依据的假设似乎适合描述饲草颗粒从RR流出的动力学。敏感性分析表明,颗粒处于可能逃逸池中的概率在大型饲草颗粒的通过中最为关键,而处于网状结构以及可能逃逸池中的概率在小型饲草和浓缩颗粒的通过中很重要。颗粒的FSG在决定颗粒命运方面比其大小更重要,尽管它们相关,尤其是对于饲草颗粒。我们得出结论,该模型可用于理解影响颗粒从RR流出动力学的因素,并预测奶牛中颗粒从RR的Kp。

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