Literature DB >> 1331382

Simulation of nutrient digestion, absorption and outflow in the rumen: model description.

J Dijkstra1, H D Neal, D E Beever, J France.   

Abstract

A mathematical model is described that stimulates the digestion, absorption and outflow of nutrients in the rumen. The model consists of 17 state variables, representing nitrogen, carbohydrate, lipid, microbial and volatile fatty acid pools. The flux equations are described by Michaelis-Menten or mass action forms with parameters calculated from the literature. Several specific areas of improvement in representation of rumen processes were reconsidered during model development. These included microbial substrate preference, differential outflow and chemical composition of rumen microbes, recycling of microbial matter within the rumen, uncoupling of fermentation with respect to nitrogen availability, reduced microbial activity at reduced rumen pH and pH-dependent absorption of volatile fatty acids and ammonia. The model was used to examine the effects of the diet on the profile of nutrients available for absorption and was shown to respond appropriately to different intake and nitrogen levels. The validity of the improvements and the predictions of nutrient supply on a variety of dietary inputs are tested in a companion paper.

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Year:  1992        PMID: 1331382     DOI: 10.1093/jn/122.11.2239

Source DB:  PubMed          Journal:  J Nutr        ISSN: 0022-3166            Impact factor:   4.798


  11 in total

1.  A simulation of microbial competition in the human colonic ecosystem.

Authors:  M E Coleman; D W Dreesen; R G Wiegert
Journal:  Appl Environ Microbiol       Date:  1996-10       Impact factor: 4.792

2.  In vitro fermentation of Pennisetum clandestinum Hochst. Ex Chiov increased methane production with ruminal fluid adapted to crude glycerol.

Authors:  Diana Marcela Valencia Echavarria; Luis Alfonso Giraldo Valderrama; Alejandra Marín Gómez
Journal:  Trop Anim Health Prod       Date:  2019-08-29       Impact factor: 1.559

3.  Measurement and prediction of enteric methane emission.

Authors:  Veerasamy Sejian; Rattan Lal; Jeffrey Lakritz; Thaddeus Ezeji
Journal:  Int J Biometeorol       Date:  2010-09-01       Impact factor: 3.787

Review 4.  Maximizing efficiency of rumen microbial protein production.

Authors:  Timothy J Hackmann; Jeffrey L Firkins
Journal:  Front Microbiol       Date:  2015-05-15       Impact factor: 5.640

5.  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

Review 6.  Recent Advances in Measurement and Dietary Mitigation of Enteric Methane Emissions in Ruminants.

Authors:  Amlan K Patra
Journal:  Front Vet Sci       Date:  2016-05-20

7.  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

8.  Effect of different forage-to-concentrate ratios on ruminal bacterial structure and real-time methane production in sheep.

Authors:  Runhang Li; Zhanwei Teng; Chaoli Lang; Haizhu Zhou; Weiguang Zhong; Zhibin Ban; Xiaogang Yan; Huaming Yang; Mohammed Hamdy Farouk; Yujie Lou
Journal:  PLoS One       Date:  2019-05-22       Impact factor: 3.240

9.  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

10.  A mathematical model to describe the diurnal pattern of enteric methane emissions from non-lactating dairy cows post-feeding.

Authors:  Min Wang; Rong Wang; Xuezhao Sun; Liang Chen; Shaoxun Tang; Chuangshe Zhou; Xuefeng Han; Jinghe Kang; Zhiliang Tan; Zhixiong He
Journal:  Anim Nutr       Date:  2015-11-28
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