A dynamic model of feed intake regulation
in dairy cows. Model description

Petruzzi, H. J.; Danfær, A.

doi:10.22358/jafs/67384/2004

Cited by 5 publications

(6 citation statements)

References 38 publications

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“…The models of Petruzzi and Danfaer (2004), Bryant et al (2008), Baudracco et al (2012) and Brun-Lafleur (2011) all explicitly recognize genetically driven changes in body energy reserves. It can also be argued that the notion has become implicit in recent versions of the Cornell Net Carbohydrate and Protein System (Tylutki et al, 2008) and the INRA Fill Unit System (Faverdin et al, 2007), as both recognize the value of adjusting intake predictions for a lactational trajectory of body reserve usage, as well as a lactation curve of milk production.…”

Section: Introductionmentioning

confidence: 99%

Advances in predicting nutrient partitioning in the dairy cow: recognizing the central role of genotype and its expression through time

Friggens

Brun-Lafleur

Faverdin

et al. 2013

Animal

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In recent years, it has become increasingly clear that understanding nutrient partitioning is central to a much broader range of issues than just being able to predict productive outputs. The extent to which nutrients are partitioned to other functions such as health and reproduction is clearly important, as are the efficiency consequences of nutrient partitioning. Further, with increasing environmental variability, there is a greater need to be able to predict the ability of an animal to respond to the nutritional limitations that arise from the environment in which it is placed. How the animal partitions its nutrients when resources are limited, or imbalanced, is a major component of its ability to cope, that is, its robustness. There is mounting evidence that reliance on body reserves is increased and that robustness of dairy cows is reduced by selection for increased milk production. A key element for predicting the partition of nutrients in this wider context is to incorporate the priorities of the animal, that is, an explicit recognition of the role of both the cow's genotype (genetic make-up), and the expression of this genotype through time on nutrient partitioning. Accordingly, there has been a growing recognition of the need to incorporate in nutritional models these innate driving forces that alter nutrient partitioning according to physiological state, the genetically driven trajectories. This paper summarizes some of the work carried out to extend nutritional models to incorporate these trajectories, the genetic effects on them, as well as how these factors affect the homeostatic capacity of the animal. At present, there are models capable of predicting the partition of nutrients throughout lactation for cows of differing milk production potentials. Information concerning genotype and stage of lactation effects on homeostatic capacity has not yet been explicitly included in metabolic models that predict nutrient partition, although recent results suggest that this is achievable. These developments have greatly extended the generality of nutrient partitioning models with respect to the type of animal and its physiological state. However, these models remain very largely focussed on predicting partition between productive outputs and body reserves and, for the most part, remain research models, although substantial progress has been made towards developing models that can be applied in the field. The challenge of linking prediction of nutrient partitioning to its consequences on health, reproduction and longevity, although widely recognized, is only now beginning to be addressed. This is an important perspective for future work on nutrient partitioning.

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Section: Introductionmentioning

confidence: 99%

Advances in predicting nutrient partitioning in the dairy cow: recognizing the central role of genotype and its expression through time

Friggens

Brun-Lafleur

Faverdin

et al. 2013

Animal

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“…An average value of energy corrected milk was reported for each treatment for the period of analysis. This average milk yield was used in combination with the equation taken from Friggens et al (1999) and included in the model (see Petruzzi and Danfaer, 2004) to produce a pattern of daily milk production that could be used as daily inputs to the model. Body condition score was not measured in the experiment, but on average the animals were in a good condition at calving (Børsting, personal communication).…”

Section: Methodsmentioning

confidence: 99%

“…Due to the equation used to calculate Upper (See Apendix and Figure 2 in Petruzzi and Danfaer, 2004), differences in intake are expected if the variable E_diff takes values in the range were the slope of the NDF load curve is high, i.e. Figure 1 (a, b, c, d, e and f).…”

Section: From Sensitivity Analysismentioning

confidence: 99%

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A dynamic model of feed intake regulation in dairy cows. Model evaluation

Petruzzi¹,

Danfær²,

Friggens³

2004

J. Anim. Feed Sci.

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The objective of this work was the evaluation of a feed intake regulation model for dairy cows described in a previous paper. Sensibility analysis revealed that the model is sensible mainly to those parameters defining the upper limit of NDF rumen digesta. The level of sensibility varies with the energy content of the diet evaluated and with the time in the lactation cycle where the sensibility analysis is done. A total of 17 treatments from a series of experiments were used to compare experimentally observed feed intake and body condition score (BCS) of dairy cows with model predictions of these variables. Feed intake, either throughout the whole lactation period or as an average for a certain period of it, is predicted by the model with an acceptable degree of accuracy for most of the treatments. Typical curves of feed intake are predicted by the model for most of the treatments. Accuracy of prediction of BCS depends on the treatment being evaluated. However, losses of BCS are predicted at the beginning of the lactation period followed by a gradual increase in BCS. The interplay between energy transactions and rumen digesta load constitutes an acceptable framework on which mechanistic models of feed intake regulation can be developed.

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“…The trajectory involves an optimal body condition balanced during the transition between successive reproductive cycles and safeguarded to ensure individual survival. This idea was already captured by Friggens et al (2004) in developing a genetically driven pattern of body lipid change through pregnancy and lactation in dairy cattle, seen as a trajectorysafeguarding reproductive success (Friggens, 2003), and used in a model of feed intake regulation in dairy cows (Petruzzi and Danfaer, 2004). Published models considering lifetime performance were mainly built with a herd level perspective with a simple and operational representation of nutrient partitioning at the animal level (Blackburn and Cartwright, 1987;Sorensen et al, 1992;Tess and Kolstad, 2000).…”

Section: Teleonomic Argumentsmentioning

confidence: 99%

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

Martin

Sauvant

2010

Animal

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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.

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A dynamic model of feed intake regulation in dairy cows. Model description

Cited by 5 publications

References 38 publications

Advances in predicting nutrient partitioning in the dairy cow: recognizing the central role of genotype and its expression through time

Advances in predicting nutrient partitioning in the dairy cow: recognizing the central role of genotype and its expression through time

A dynamic model of feed intake regulation in dairy cows. Model evaluation

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

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