Literature DB >> 3819150

Metabolism of the lactating cow. II. Digestive elements of a mechanistic model.

R L Baldwin, J H Thornley, D E Beever.   

Abstract

The structure and characteristics of a model suitable for estimating digestion within the rumen and rates and patterns of nutrient entry in lactating cows are presented. The model consists of 12 state variables comprising a large particle pool, small particle pools representing insoluble dietary nutrients, soluble pools representing soluble dietary nutrients, and fermentation intermediates and end products. The model was constructed assuming continuous feeding, using Michaelis-Menten or mass action kinetics. The computer program was written in ACSL to run on a VAX computer. A fourth-order Runge-Kutta procedure was used for numerical integration. Sensitivity and behavioural analysis demonstrated that overall stability and sensitivity of the model to individual parameters was generally satisfactory, but the need to improve the description and parameterization of aspects such as particle size in relation to availability, rate and affinity constants for amino acid degradation and rate constants for particle outflow from the rumen was established. Adjustments of the model to examine discontinuous feeding regimes were undertaken and initial results with respect to changes in fermentation rates, rumen acetate levels and microbial metabolism were considered realistic. Comparisons with experimental data were considered satisfactory on forage-based and medium concentrate-containing diets, but with diets comprising 90% cereal, some inconsistencies, especially with respect to predictions of volatile fatty acid production rates, were observed. Reasons for this are put forward and suggestions for improvements in the model are discussed.

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Year:  1987        PMID: 3819150     DOI: 10.1017/s0022029900025231

Source DB:  PubMed          Journal:  J Dairy Res        ISSN: 0022-0299            Impact factor:   1.904


  7 in total

1.  Application of a hand-held laser methane detector for measuring enteric methane emissions from cattle in intensive farming.

Authors:  Kyewon Kang; Hyunjin Cho; Sinyong Jeong; Seoyoung Jeon; Mingyung Lee; Seul Lee; Yulchang Baek; Joonpyo Oh; Seongwon Seo
Journal:  J Anim Sci       Date:  2022-08-01       Impact factor: 3.338

2.  Effect of stearic or oleic acid on milk performance and energy partitioning when fed in diets with low and high rumen-active unsaturated fatty acids in early lactation.

Authors:  Chen Yanting; Guiling Ma; Joseph H Harrison; Elliot Block
Journal:  J Anim Sci       Date:  2019-11-04       Impact factor: 3.159

3.  Predicting in vitro rumen VFA production using CNCPS carbohydrate fractions with multiple linear models and artificial neural networks.

Authors:  Ruilan Dong; Guangyong Zhao
Journal:  PLoS One       Date:  2014-12-31       Impact factor: 3.240

4.  ASN-ASAS SYMPOSIUM: FUTURE OF DATA ANALYTICS IN NUTRITION: Mathematical modeling in ruminant nutrition: approaches and paradigms, extant models, and thoughts for upcoming predictive analytics1,2.

Authors:  Luis O Tedeschi
Journal:  J Anim Sci       Date:  2019-04-29       Impact factor: 3.159

Review 5.  Quantification of methane emitted by ruminants: a review of methods.

Authors:  Luis Orlindo Tedeschi; Adibe Luiz Abdalla; Clementina Álvarez; Samuel Weniga Anuga; Jacobo Arango; Karen A Beauchemin; Philippe Becquet; Alexandre Berndt; Robert Burns; Camillo De Camillis; Julián Chará; Javier Martin Echazarreta; Mélynda Hassouna; David Kenny; Michael Mathot; Rogerio M Mauricio; Shelby C McClelland; Mutian Niu; Alice Anyango Onyango; Ranjan Parajuli; Luiz Gustavo Ribeiro Pereira; Agustin Del Prado; Maria Paz Tieri; Aimable Uwizeye; Ermias Kebreab
Journal:  J Anim Sci       Date:  2022-07-01       Impact factor: 3.338

6.  Application of Top-Down and Bottom-up Systems Approaches in Ruminant Physiology and Metabolism.

Authors:  Khuram Shahzad; Juan J Loor
Journal:  Curr Genomics       Date:  2012-08       Impact factor: 2.236

7.  The Contribution of Mathematical Modeling to Understanding Dynamic Aspects of Rumen Metabolism.

Authors:  André Bannink; Henk J van Lingen; Jennifer L Ellis; James France; Jan Dijkstra
Journal:  Front Microbiol       Date:  2016-11-23       Impact factor: 5.640

  7 in total

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