Literature DB >> 16527876

Integration of ruminal metabolism in dairy cattle.

J L Firkins1, A N Hristov, M B Hall, G A Varga, N R St-Pierre.   

Abstract

An important objective is to identify nutrients or dietary factors that are most critical for advancing our knowledge of, and improving our ability to predict, milk protein production. The Dairy NRC (2001) model is sensitive to prediction of microbial protein synthesis, which is among the most important component of models integrating requirement and corresponding supply of metabolizable protein or amino acids. There are a variety of important considerations when assessing appropriate use of microbial marker methodology. Statistical formulas and examples are included to document and explain limitations in using a calibration equation from a source publication to predict duodenal flow of purine bases from measured urinary purine derivatives in a future study, and an improved approach was derived. Sources of specific carbohydrate rumen-degraded protein components probably explain microbial interactions and differences among studies. Changes in microbial populations might explain the variation in ruminal outflow of biohydrogenation intermediates that modify milk fat secretion. Finally, microbial protein synthesis can be better integrated with the production of volatile fatty acids, which do not necessarily reflect volatile fatty acid molar proportions in the rumen. The gut and splanchnic tissues metabolize varying amounts of volatile fatty acids, and propionate has important hormonal responses influencing milk protein percentage. Integration of ruminal metabolism with that in the mammary and peripheral tissues can be improved to increase the efficiency of conversion of dietary nutrients into milk components for more efficient milk production with decreased environmental impact.

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Year:  2006        PMID: 16527876     DOI: 10.3168/jds.S0022-0302(06)72362-1

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  6 in total

1.  Effect of carbohydrate sources and cotton seed meal in the concentrate: II. Feed intake, nutrient digestibility, rumen fermentation and microbial protein synthesis in beef cattle.

Authors:  Metha Wanapat; Suban Foiklang; Peter Rowlinson; Ruangyote Pilajun
Journal:  Trop Anim Health Prod       Date:  2011-11-10       Impact factor: 1.559

2.  Performance, nutritional behavior, and carcass characteristics of feedlot lambs fed diets with non-forage fiber source or sodium bicarbonate.

Authors:  Ana Carolina Silva Vicente; Matheus Sousa de Paula Carlis; Isabela Jorge Dos Santos; Adrielly Lais Alves da Silva; Paulo César Gonzales Dias Júnior; Rhaissa Garcia de Assis; Thamires Ubices Sturion; Janaina Socolovski Biava; Alexandre Vaz Pires; Evandro Maia Ferreira
Journal:  Trop Anim Health Prod       Date:  2022-09-09       Impact factor: 1.893

Review 3.  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

4.  Effect of carbohydrate sources and levels of cotton seed meal in concentrate on feed intake, nutrient digestibility, rumen fermentation and microbial protein synthesis in young dairy bulls.

Authors:  M Wanapat; N Anantasook; P Rowlinson; R Pilajun; P Gunun
Journal:  Asian-Australas J Anim Sci       Date:  2013-04       Impact factor: 2.509

5.  Effect of carbohydrate source and cottonseed meal level in the concentrate on feed intake, nutrient digestibility, rumen fermentation and microbial protein synthesis in swamp buffaloes.

Authors:  M Wanapat; R Pilajun; S Polyorach; A Cherdthong; P Khejornsart; P Rowlinson
Journal:  Asian-Australas J Anim Sci       Date:  2013-07       Impact factor: 2.509

6.  Effects of Lonicera japonica extract on performance, blood biomarkers of inflammation and oxidative stress during perinatal period in dairy cows.

Authors:  Yiguang Zhao; Zhiwen Tang; Xuemei Nan; Fuyu Sun; Linshu Jiang; Benhai Xiong
Journal:  Asian-Australas J Anim Sci       Date:  2019-10-21       Impact factor: 2.509

  6 in total

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