Literature DB >> 8778104

Prediction of ruminal volatile fatty acids and pH within the net carbohydrate and protein system.

R E Pitt1, J S Van Kessel, D G Fox, A N Pell, M C Barry, P J Van Soest.   

Abstract

A steady-state model of the production, absorption, passage, and concentration of ruminal VFA and pH is developed from published literature data and is structured to use the feed descriptions and inputs from the net carbohydrate and protein system. Included are the effects of pH on growth rate and yield of structural and non-structural carbohydrate-fermenting bacteria; production of acetate, propionate, butyrate, lactate, and methane; conversion of lactate to VFA; ruminal absorption of acids; and prediction of ruminal pH from dietary measures and from ruminal buffering and acidity. The root mean square error of predicted total VFA concentration was 12 mM. Individual VFA fractions were inadequately predicted. In a review of literature data, effective NDF (eNDF) provided a better correlation with ruminal pH than forage or NDF. Digestion rate of NDF remained at normal levels above pH 6.2, which corresponds to a minimum eNDF of 20% of dietary DM. Further research is needed to determine the individual VFA produced from carbohydrate fractions at various pH, the appropriateness of partitioning the starch and pectin carbohydrate pool into slowly and rapidly degraded fractions, and the effect on microbial yield, total tract digestibility, and predicted energy values of feeds.

Entities:  

Mesh:

Substances:

Year:  1996        PMID: 8778104     DOI: 10.2527/1996.741226x

Source DB:  PubMed          Journal:  J Anim Sci        ISSN: 0021-8812            Impact factor:   3.159


  13 in total

1.  Effect of ammonia fiber expansion-treated wheat straw and a recombinant fibrolytic enzyme on rumen microbiota and fermentation parameters, total tract digestibility, and performance of lambs.

Authors:  Gabriel O Ribeiro; Robert J Gruninger; Darryl R Jones; Karen A Beauchemin; Wen Zhu Yang; Yuxi Wang; D Wade Abbott; Adrian Tsang; Tim A McAllister
Journal:  J Anim Sci       Date:  2020-05-01       Impact factor: 3.159

2.  Effects of source and concentration of neutral detergent fiber from roughage in beef cattle diets: Comparison of methods to measure the effectiveness of fiber.

Authors:  Rodrigo S Goulart; Ricardo A M Vieira; Joao L P Daniel; Rafael C Amaral; Vanessa P Santos; Sergio G Toledo Filho; Edward H Cabezas-Garcia; Luis O Tedeschi; Luiz Gustavo Nussio
Journal:  J Anim Sci       Date:  2020-05-01       Impact factor: 3.159

3.  Whole or coarsely broken açai seed as a source of roughage in the diet of feedlot cattle: intake, digestibility, and ruminal parameters.

Authors:  Natália Gomes Lacerda; Luís Rennan Sampaio Oliveira; Carlos Magno Chaves Oliveira; Tatiane Teles Albernaz Ferreira; Kaliandra Souza Alves; Mikaelly Rodrigues de Almeida; Thamiris Silva de Souza; Mychelle Cristina Alves Santos; Daiany Iris Gomes; Rafael Mezzomo
Journal:  Trop Anim Health Prod       Date:  2022-06-09       Impact factor: 1.559

4.  Increasing the content of physically effective fiber in high-concentrate diets fed to beef heifers affects intake, sorting behavior, time spent ruminating, and rumen pH.

Authors:  Lourdes Llonch; Lorena Castillejos; Alfred Ferret
Journal:  J Anim Sci       Date:  2020-06-01       Impact factor: 3.159

5.  Absorption of short-chain fatty acids, sodium and water from the forestomach of camels.

Authors:  W von Engelhardt; Ch Dycker; M Lechner-Doll
Journal:  J Comp Physiol B       Date:  2007-04-12       Impact factor: 2.230

6.  Perturbation dynamics of the rumen microbiota in response to exogenous butyrate.

Authors:  Robert W Li; Sitao Wu; Ransom L Baldwin; Weizhong Li; Congjun Li
Journal:  PLoS One       Date:  2012-01-12       Impact factor: 3.240

7.  Quantitative analysis of ruminal methanogenic microbial populations in beef cattle divergent in phenotypic residual feed intake (RFI) offered contrasting diets.

Authors:  Ciara A Carberry; David A Kenny; Alan K Kelly; Sinéad M Waters
Journal:  J Anim Sci Biotechnol       Date:  2014-08-22

8.  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

9.  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

10.  Effect of traditional Chinese medicine compounds on rumen fermentation, methanogenesis and microbial flora in vitro.

Authors:  Shui Ping Wang; Wen Juan Wang; Zhi Liang Tan; Guo Wei Liu; Cheng Fu Zhou; Meng Jie Yin
Journal:  Anim Nutr       Date:  2018-10-25
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.