Modeling Ruminant Digestion and Metabolism

Baldwin, R.L.; Donovan, Kevin

doi:10.1007/978-1-4899-1959-5_21

Cited by 198 publications

(429 citation statements)

References 10 publications

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“…However, the diet effect on CH 4 production appears not always to be consistent with the observed shift in rumen fermentation pattern. The most detailed mechanistic models of CH 4 production (Baldwin, 1995;Benchaar et al, 1998;Mills et al, 2001) predicted rumen fermentation pattern based on VFA coefficients that were derived from surveys of literature data on rumen digestion, and under the assumption of consumption of all surplus H 2 for CH 4 production. However, there is a lack of a combination of these data.…”

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confidence: 99%

Methane production and diurnal variation measured in dairy cows and predicted from fermentation pattern and nutrient or carbon flow

Brask

Weisbjerg

Hellwing

et al. 2015

Animal

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Many feeding trials have been conducted to quantify enteric methane (CH 4 ) production in ruminants. Although a relationship between diet composition, rumen fermentation and CH 4 production is generally accepted, the efforts to quantify this relationship within the same experiment remain scarce. In the present study, a data set was compiled from the results of three intensive respiration chamber trials with lactating rumen and intestinal fistulated Holstein cows, including measurements of rumen and intestinal digestion, rumen fermentation parameters and CH 4 production. Two approaches were used to calculate CH 4 from observations: (1) a rumen organic matter (OM) balance was derived from OM intake and duodenal organic matter flow (DOM) distinguishing various nutrients and (2) a rumen carbon balance was derived from carbon intake and duodenal carbon flow (DCARB). Duodenal flow was corrected for endogenous matter, and contribution of fermentation in the large intestine was accounted for. Hydrogen (H 2 ) arising from fermentation was calculated using the fermentation pattern measured in rumen fluid. CH 4 was calculated from H 2 production corrected for H 2 use with biohydrogenation of fatty acids. The DOM model overestimated CH 4 /kg dry matter intake (DMI) by 6.1% ( R 2 = 0.36) and the DCARB model underestimated CH 4 /kg DMI by 0.4% ( R 2 = 0.43). A stepwise regression of the difference between measured and calculated daily CH 4 production was conducted to examine explanations for the deviance. Dietary carbohydrate composition and rumen carbohydrate digestion were the main sources of inaccuracies for both models. Furthermore, differences were related to rumen ammonia concentration with the DOM model and to rumen pH and dietary fat with the DCARB model. Adding these parameters to the models and performing a multiple regression against observed daily CH 4 production resulted in R 2 of 0.66 and 0.72 for DOM and DCARB models, respectively. The diurnal pattern of CH 4 production followed that of rumen volatile fatty acid (VFA) concentration and the CH 4 to CO 2 production ratio, but was inverse to rumen pH and the rumen hydrogen balance calculated from 4 × (acetate + butyrate)/2 × (propionate + valerate). In conclusion, the amount of feed fermented was the most important factor determining variations in CH 4 production between animals, diets and during the day. Interactions between feed components, VFA absorption rates and variation between animals seemed to be factors that were complicating the accurate prediction of CH 4 . Using a ruminal carbon balance appeared to predict CH 4 production just as well as calculations based on rumen digestion of individual nutrients.Keywords: modelling methane, VFA, enteric fermentation, carbon, dairy cow Implications Methane (CH 4 ) is a potent greenhouse gas that arises from feed fermentation in the rumen and large intestine of ruminant animals. The quantity of CH 4 depends on daily feed intake, feed chemical composition and feed rumen digestibility. Therefore, the present paper was ...

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mentioning

confidence: 99%

Methane production and diurnal variation measured in dairy cows and predicted from fermentation pattern and nutrient or carbon flow

Brask

Weisbjerg

Hellwing

et al. 2015

Animal

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“…Through this mechanistic representation, variations of wholeanimal performance emerged from the aggregation of several points of biochemical regulation. Similar attempts to incorporate regulation rules in animal models through control variables driving physiological processes were performed in several other studies, for example, 'lactation hormone' (Neal and Thornley, 1983;Baldwin et al, 1987c), 'anabolic and catabolic hormones' (Sauvant and Phocas, 1992;Baldwin, 1995;Martin and Sauvant, 2007) and 'growth hormone and insulin' (Danfaer, 1990).…”

Section: Introductionmentioning

confidence: 86%

“…The introduction of the idea of goal-directed process as a driving force referred to the teleonomy concept of Monod (1970): 'organisms are endowed with a purpose which is inherent in their structure and determines their behavior'. This deterministic point of view focuses on the biological significance of physiological processes giving rise to performance rather than focusing on their biochemical determinants, which is the basis of aggregated mechanistic models such as Baldwin's model (Baldwin et al, 1987a(Baldwin et al, , 1987b(Baldwin et al, and 1987cBaldwin, 1995). The proposed model falls into the category of 'teleonomic models' according to the typology of Thornley and France (2007), that is, explicitly incorporating an apparent goal-directed process.…”

Section: Teleonomic Argumentsmentioning

confidence: 99%

“…Further developments were carried out by Dijkstra et al (1997), Vetharaniam et al (2003a and2003b) and Pollott (2004). This principle of modelling was also used to direct adipose tissue anabolism and catabolism (Sauvant and Phocas, 1992;Baldwin, 1995;Martin and Sauvant, 2007) or to provide kinetics of plasma growth hormone and insulin driving exchanges between the tissues and udder (Danfaer, 1990). However, none of these approaches focused on a centralized regulating model.…”

Section: Teleonomic Argumentsmentioning

confidence: 99%

“…In attempting to describe all the mechanisms involved, they frequently come to be exhaustive encyclopaedic compilations (Baldwin, 1995) that themselves become complex objects, difficult to manipulate and use for prediction. In a reverse approach, we propose to explicitly model a centralized regulating sub-system structured on the basis of teleonomic arguments.…”

Section: Introductionmentioning

confidence: 99%

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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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Vitamin requirements: Relationship to basal metabolic need and functions

Rucker

Steinberg

2002

Biochem Molecular Bio Educ

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The dietary requirements for most water-soluble vitamins in homeothermic animals, particularly vitamins utilized in energy-related pathways, are related directly to metabolic rate. As a consequence, vitamin requirements are similar when expressed relative to empirical functions of metabolic body size, e.g. (Wt kg ) 3 ⁄4or body surface area. The vitamin requirements for a range of animals are expressed relative to their corresponding rates of basal metabolism. Data for the rates of ascorbic acid production and turnover in animals that produce ascorbic acid are also compared with the ascorbic acid requirements and turnover in humans and guinea pigs, species that require ascorbic acid as a dietary essential. Factors that are most important in dictating the relative need for a given vitamin from a chemical perspective include chemical stability, the relative number of catalytic events that are involved in the process, the nature of the interactions with associated enzymes, and the presence or absence of pathways for partial synthesis or regeneration of the given vitamin. Vitamins that are required daily in millimolar amounts are usually less stable chemically, are involved in numerous reactions, and often exist in tissues as dissociable cofactors. In contrast, vitamins that are required daily in micromolar amounts are involved in fewer reactions and are often covalently bound to the proteins or enzymes for which they serve as cofactors. Development of the preceding concepts allows linkages of relative vitamin requirements to energy utilization and related biochemical and oxidative processes, which can aid in developing a better understanding of the integrative nature of nutritional and biochemical relationships.Keywords: Vitamins, nutrient requirements, metabolic rate, cofactor function.In presentations dealing with vitamin-derived cofactor function and metabolism, interest is enhanced when the information is developed in ways that link vitamin function to nutritional need. Empirical relationships that have evolved from studies of animal energetics can be used to conceptualize similarities between vitamin requirements for common animal species, including humans. Moreover, explanations as to why requirements for individual watersoluble vitamins vary by several orders of magnitude can also be developed as a way of underscoring the importance of chemical stability, the specificity of cofactor protein interactions, relative metabolic needs, and other chemically related parameters.In homeothermic animals, a case may be made that water-soluble vitamin requirements are influenced by the same factors that dictate energy requirements. This perspective comes from the work of Kleiber [1] and Brody [2] and more recently work by Baldwin [3] and Heusner [4,5]. That is, in homeothermic animals, the estimation of relative metabolic rate correlates with metabolic size, when expressed as a function of (Wt kg ) 3 ⁄4 , even for animals whose body weights vary by orders of magnitude (Fig. 1). At ambient temperatures and at rest, most ...

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Modeling Ruminant Digestion and Metabolism

Cited by 198 publications

References 10 publications

Methane production and diurnal variation measured in dairy cows and predicted from fermentation pattern and nutrient or carbon flow

Methane production and diurnal variation measured in dairy cows and predicted from fermentation pattern and nutrient or carbon flow

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

Vitamin requirements: Relationship to basal metabolic need and functions

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