Literature DB >> 22445378

A teleonomic model describing performance (body, milk and intake) during growth and over repeated reproductive cycles throughout the lifespan of dairy cattle. 1. Trajectories of life function priorities and genetic scaling.

O Martin1, D Sauvant.   

Abstract

The prediction of the control of nutrient partitioning, particularly energy, is a major issue in modelling dairy cattle performance. The proportions of energy channelled to physiological functions (growth, maintenance, gestation and lactation) change as the animal ages and reproduces, and according to its genotype and nutritional environment. This is the first of two papers describing a teleonomic model of individual performance during growth and over repeated reproductive cycles throughout the lifespan of dairy cattle. The conceptual framework is based on the coupling of a regulating sub-model providing teleonomic drives to govern the work of an operating sub-model scaled with genetic parameters. The regulating sub-model describes the dynamic partitioning of a mammal female's priority between life functions targeted to growth (G), ageing (A), balance of body reserves (R) and nutrient supply of the unborn (U), newborn (N) and suckling (S) calf. The so-called GARUNS dynamic pattern defines a trajectory of relative priorities, goal directed towards the survival of the individual for the continuation of the specie. The operating sub-model describes changes in body weight (BW) and composition, foetal growth, milk yield and composition and food intake in dairy cows throughout their lifespan, that is, during growth, over successive reproductive cycles and through ageing. This dynamic pattern of performance defines a reference trajectory of a cow under normal husbandry conditions and feed regimen. Genetic parameters are incorporated in the model to scale individual performance and simulate differences within and between breeds. The model was calibrated for dairy cows with literature data. The model was evaluated by comparison with simulations of previously published empirical equations of BW, body condition score, milk yield and composition and feed intake. This evaluation showed that the model adequately simulates these production variables throughout the lifespan, and across a range of dairy cattle genotypes.

Entities:  

Year:  2010        PMID: 22445378     DOI: 10.1017/S1751731110001357

Source DB:  PubMed          Journal:  Animal        ISSN: 1751-7311            Impact factor:   3.240


  3 in total

1.  A dynamic model as a tool to describe the variability of lifetime body weight trajectories in livestock females.

Authors:  L Puillet; O Martin
Journal:  J Anim Sci       Date:  2017-11       Impact factor: 3.159

Review 2.  ASAS-NANP Symposium: Mathematical Modeling in Animal Nutrition: Opportunities and challenges of confined and extensive precision livestock production.

Authors:  Hector M Menendez; Jameson R Brennan; Charlotte Gaillard; Krista Ehlert; Jaelyn Quintana; Suresh Neethirajan; Aline Remus; Marc Jacobs; Izabelle A M A Teixeira; Benjamin L Turner; Luis O Tedeschi
Journal:  J Anim Sci       Date:  2022-06-01       Impact factor: 3.338

3.  Disentangling the relative roles of resource acquisition and allocation on animal feed efficiency: insights from a dairy cow model.

Authors:  Laurence Puillet; Denis Réale; Nicolas C Friggens
Journal:  Genet Sel Evol       Date:  2016-09-26       Impact factor: 4.297

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.