A simulation model “CTR Dairy” to predict the supply of nutrients in dairy cows managed under discontinuous feeding patterns

Chilibroste, P.; Dijkstra, J.; Robinson, P.H.; Tamminga, S.

doi:10.1016/j.anifeedsci.2007.05.009

Cited by 18 publications

(9 citation statements)

References 49 publications

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“…Although the simulation of a steady state within the rumen during continuous feeding has proved effective for the simulation of many aspects of rumen fermentation, the objectives of this investigation require pulsed model inputs, thus simulating rumen function in the cow fed a limited number of meals during the day. France et al (1982), Baldwin, (1995), and Chilibroste et al (2001Chilibroste et al ( , 2008 describe models of whole-rumen function for which inputs were either continuous or pulsed to represent discontinuous feeding schedules. Due to the objectives of the present model, the approach taken by France et al (1982) is used to simulate discontinuous feeding where instantaneous values for nutrient inputs (D x ) are represented as follows:…”

Section: Model Parameterizationmentioning

confidence: 99%

A dynamic mechanistic model of lactic acid metabolism in the rumen

Mills

Crompton

Ellis

et al. 2014

Journal of Dairy Science

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Current feed evaluation systems for ruminants are too imprecise to describe diets in terms of their acidosis risk. The dynamic mechanistic model described herein arises from the integration of a lactic acid (La) metabolism module into an extant model of whole-rumen function. The model was evaluated using published data from cows and sheep fed a range of diets or infused with various doses of La. The model performed well in simulating peak rumen La concentrations (coefficient of determination = 0.96; root mean square prediction error = 16.96% of observed mean), although frequency of sampling for the published data prevented a comprehensive comparison of prediction of time to peak La accumulation. The model showed a tendency for increased La accumulation following feeding of diets rich in nonstructural carbohydrates, although less-soluble starch sources such as corn tended to limit rumen La concentration. Simulated La absorption from the rumen remained low throughout the feeding cycle. The competition between bacteria and protozoa for rumen La suggests a variable contribution of protozoa to total La utilization. However, the model was unable to simulate the effects of defaunation on rumen La metabolism, indicating a need for a more detailed description of protozoal metabolism. The model could form the basis of a feed evaluation system with regard to rumen La metabolism.

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Section: Model Parameterizationmentioning

confidence: 99%

A dynamic mechanistic model of lactic acid metabolism in the rumen

Mills

Crompton

Ellis

et al. 2014

Journal of Dairy Science

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“…Moreover, rumen volume was assumed to be related to size of the meals and DM content. Chilibroste et al (2008) included a representation of effect of chewing efficiency on the release rate of intracellular constituents in their rumen model. This release rate appears to be an important determinant of instantaneous substrate availability to rumen microorganisms, and therefore also determines the rumen pH and VFA diurnal patterns.…”

Section: P Utilization and Excretionmentioning

confidence: 99%

Recent advances in modeling nutrient utilization in ruminants1

Kebreab

Dijkstra

Bannink

2009

Journal of Animal Science

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Mathematical modeling techniques have been applied to study various aspects of the ruminant, such as rumen function, postabsorptive metabolism, and product composition. This review focuses on advances made in modeling rumen fermentation and its associated rumen disorders, and energy and nutrient utilization and excretion with respect to environmental issues. Accurate prediction of fermentation stoichiometry has an impact on estimating the type of energy-yielding substrate available to the animal, and the ratio of lipogenic to glucogenic VFA is an important determinant of methanogenesis. Recent advances in modeling VFA stoichiometry offer ways for dietary manipulation to shift the fermentation in favor of glucogenic VFA. Increasing energy to the animal by supplementing with starch can lead to health problems such as subacute rumen acidosis caused by rumen pH depression. Mathematical models have been developed to describe changes in rumen pH and rumen fermentation. Models that relate rumen temperature to rumen pH have also been developed and have the potential to aid in the diagnosis of subacute rumen acidosis. The effect of pH has been studied mechanistically, and in such models, fractional passage rate has a large impact on substrate degradation and microbial efficiency in the rumen and should be an important theme in future studies. The efficiency with which energy is utilized by ruminants has been updated in recent studies. Mechanistic models of N utilization indicate that reducing dietary protein concentration, matching protein degradability to the microbial requirement, and increasing the energy status of the animal will reduce the output of N as waste. Recent mechanistic P models calculate the P requirement by taking into account P recycled through saliva and endogenous losses. Mechanistic P models suggest reducing current P amounts for lactating dairy cattle to at least 0.35% P in the diet, with a potential reduction of up to 1.3 kt/yr. A model that integrates nutrient utilization and health has great potential benefit for ruminant nutrition research. Finally, whole-animal or farm level models are discussed. An example that used a multiple-criteria decision-making framework is reviewed, and the approach is considered to be appropriate in dealing with the multidimensional nature of agricultural systems and can be applied to assist the decision process in cattle operations.

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“…However, simulation models such as Johnson et al (2008) and Chilibroste et al (2008) are beginning to impact modelling efforts, and this type of metabolic modelling requires new kinds of information. The practical value of simulation models are currently constrained due to many factors, but one of the most important is the unpredictability of the genetic expression of milk yield by cows prior to initiating a lactation, especially those cows entering their first lactation.…”

Section: Introductionmentioning

confidence: 99%