Evaluation of a mathematical model of lactating sow metabolism2

Je, Pettigrew; Gill, M.; Close, WH

doi:10.2527/1992.70123762x

Cited by 17 publications

(6 citation statements)

References 2 publications

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“…the model are needed. This statement is systematically quoted in published models to improve a priori confidence in the validation (Pettigrew et al, 1992;Freetly et al, 1993). New observations are available because they are too aggregated to support the internal model parameterization.…”

Section: New Data That Have Not Been Used In Buildingmentioning

confidence: 97%

“…After these qualitative tests, quantitative objective tests are needed. In models where the outputs are obtained at the end of the simulation period, for examples the live weight change during lactation in the sow (Pettigrew et al, 1992), a comparison between the simulated and the measured outputs gives a quantitative validation of the model. The determination and decomposition of the mean square prediction error (Bibby and Toutenburg, 1977) is a reliable tool to evaluate a model.…”

Section: New Data That Have Not Been Used In Buildingmentioning

confidence: 99%

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Discussion of methods in building and validating a model: example of amino acid metabolism in ruminants

Lescoat¹,

Danfær²,

Sauvant³

1996

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A methodological approach of mechanistic modelling is proposed. Firstly, the goals and features of the model are defined. The qualitative flux diagram is described. Its translation into mathematical equations is presented. Some options to determine the model parameters are proposed. The mathematical integration and some limits are studied. Theoretical validations are made with an emphasis on sensitivity analyses. Several possibilities for external validation are shown. These different steps are illustrated through the development of a mechanistic model of the amino acid metabolism in the lactating cow. The decisions taken at each step of the modelling process are discussed and their limits are settled. The conclusions underlined the difficulty to endup with a final model and proposed an interdisciplinary approach as a possible solution. However, the models are very important through their construction since they underline the areas where there is a gap of knowledge and therefore they are an interesting tool to orientate future experiments. Moreover, these models can also be used pratically if they have been validated.

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Section: New Data That Have Not Been Used In Buildingmentioning

confidence: 97%

Section: New Data That Have Not Been Used In Buildingmentioning

confidence: 99%

Discussion of methods in building and validating a model: example of amino acid metabolism in ruminants

Lescoat¹,

Danfær²,

Sauvant³

1996

CrossRef Listing Of Deleted DOIs

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“…direct effects on the ovary) or indirectly, through effects on reproductive hormone release and degradation. The model described previously (Pettigrew et al 1992b) deals only with nutrient intake, metabolic state, milk production, and body reserves. It is not structured to address the connection between metabolic state and reproduction.…”

Section: Reproductive Performancementioning

confidence: 99%

Mathematical modelling of nitrogen flow in growing pigs and lactating sows

Pettigrew

1997

Proc. Nutr. Soc.

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Mathematical modelling as applied to growing pigs and lactating sows is a structured method for deriving quantitative estimates of the productive performance of the animal under varying diets and other conditions. A simple overview is that a model starts with a clear quantitative description of the animal (usually including body protein and fat content), estimates daily protein and fat accretion, updates the description, and repeats those estimates and updates until the desired end-point is reached. This is conceptually simple, but in practice it is quite challenging.A recent book edited by Moughan et al. (1995) provides a thorough description of modelling as applied to the pig. Progress in modelling the pig continues, as shown by recent publication of a model of digestion in the pig (Bastianelli et al. 1996).Models that predict whole-animal performance can vary in the level of aggregation at which they operate. Some models work at the metabolic level, predicting the flows of C and N through metabolic pathways. They do not work at the level of individual reactions, but aggregate those individual reactions into pathways. Others work at the level of lean and adipose tissues, predicting the rates of accretion of protein and fat in these tissues. They thus aggregate all the metabolic transactions into simple expressions of protein and fat accretion, so they are more highly aggregated than are the metabolic models. Still others operate at the whole-animal level, and are the most highly aggregated of all. They often are built of regression equations relating body-weight gain to variables such as dietary lysine concentration or stocking density, and thus aggregate accretion of protein, fat, water, ash, and gut contents into whole-body growth. They are considered empirical models because they are based entirely on observations, with no considerations of the underlying mechanisms. Nutrient-partitioning and metabolic models are considered mechanistic, because they are structured to reflect our perceptions of the mechanisms of animal growth. They admittedly contain empirical elements, because in some areas (e.g. relationship between backfat thickness and body fat content) we have no useful concepts of the underlying mechanisms. The terms empirical and mechanistic as applied to models are relative, not absolute, so there are degrees of mechanism. Metabolic models are more mechanistic than are nutrient-partitioning models, because there is a greater separation between the level of the outputs (whole-animal) and the level at which they are built than in the case of nutrient-partitioning models.Empirical models can be very accurate within the range of conditions in which they were developed, but are unreliable when used in other conditions. Mechanistic models are more reliable over a wider range of conditions because they are built on biological mechanisms. Therefore, they are usually more useful. However, as models become more mechanistic, reliable quantitative estimates of model variables are often more difficult to obtain,...

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“…This approach was extended by Kielanowski (1965) to develop an statistical method that derived constants for the partial energetic efficiencies of protein (K p ) and fat (K F ) deposition. The second approach (e.g., Gill et al, 1989;Pettigrew et al, 1992), attempts to quantify the pathways that lead to protein and lipid deposition and, by using biochemical knowledge, quantify the animal's energy balance from chemical stoichiometry. Each approach has its advantages and disadvantages.…”

Section: Introductionmentioning

confidence: 99%

Amino acid metabolism and the energetics of growth

Reeds

Burrin

Davis

et al. 1998

Archiv für Tierernaehrung

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The nonessential amino acids are involved in a large number of functions that are not directly associated with protein synthesis. Recent studies using a combination of transorgan balance and stable isotopic tracers have demonstrated that a substantial portion of the extra-splanchnic flux of glutamate, glutamine, glycine and cysteine derives from tissue synthesis. A key amino acid in this respect is glutamic acid. Little glutamic acid of dietary origin escapes metabolism in the small intestinal mucosa. Furthermore, because glutamic acid is the only amino acid that can be synthesized by mammals by reductive amination of a ketoacid, it is the ultimate nitrogen donor for the synthesis of other nonessential amino acids. Because the synthesis of glutamic acid and its product glutamine involve the expenditure of adenosine triphosphate (ATP), it seems possible that nonessential amino acid synthesis might have a significant bearing on the energetics of protein synthesis and, hence, of protein deposition. This paper discusses the topic of the energy cost of protein deposition, considers the metabolic physiology of amino acid oxidation and nonessential amino acid synthesis, and attempts to combine the information to speculate on the overall impact of amino acid metabolism on the energy exchanges of animals.

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Evaluation of a mathematical model of lactating sow metabolism2

Cited by 17 publications

References 2 publications

Discussion of methods in building and validating a model: example of amino acid metabolism in ruminants

Discussion of methods in building and validating a model: example of amino acid metabolism in ruminants

Mathematical modelling of nitrogen flow in growing pigs and lactating sows

Amino acid metabolism and the energetics of growth

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