Meta-analysis of postruminal microbial nitrogen flows in dairy cattle. I. Derivation of equations

Publication date: October 2016
Source:Journal of Dairy Science, Volume 99, Issue 10
Author(s): Yairanex Roman-Garcia, Robin R. White, Jeffrey L. Firkins
The objective was to summarize the literature and derive equations that relate the chemical composition of diet and rumen characteristics to the intestinal supply of microbial nitrogen (MicN), efficiency of microbial protein synthesis (EMPS), and flow of nonammonia nonmicrobial N (NANMN). In this study, 619 treatment means from 183 trials were assembled for dairy cattle sampled from the duodenum or omasum. Backward elimination multiple regression was used to derive equations to estimate flow of nitrogenous components over a large range of dietary conditions. An intercept shift for sample location revealed that omasal sampling estimated greater MicN flow relative to duodenal sampling, but sample location did not interact with any other variables tested. The ruminal outflow of MicN was positively associated with dry matter intake (DMI) and with dietary starch percentage at a decreasing rate (quadratic response). Also, MicN was associated with DMI and rumen-degraded starch and neutral detergent fiber (NDF). When rumen measurements were included, ruminal pH and ammonia-N were negatively related to MicN flow along with a strong positive association with ruminal isovalerate molar proportion. When evaluating these variables with EMPS, isovalerate interacted with ammonia such that the slope for EMPS with increasing isovalerate increased as ammonia-N concentration decreased. A similar equation with isobutyrate confirms the importance of branched-chain volatile fatty acids to increase growth rate and therefore assimilation of ammonia-N into microbial protein. The ruminal outflow of NANMN could be predicted by dietary NDF and crude protein percentages, which also interacted. This result is probably associated with neutral detergent insoluble N contamination of NDF in certain rumen-undegradable protein sources. Because NANMN is calculated by subtracting MicN, sample location was inversely related compared with the MicN equation, and omasal sampling underestimated NANMN relative to duodenal sampling. As in the MicN equation, sampling location did not interact with any other variables tested for NANMN. Equations derived from dietary nutrient composition are robust across dietary conditions and could be used for prediction in protein supply-requirement models. These empirical equations were supported by more mechanistic equations based on the ruminal carbohydrate degradation and ruminal variables related to dietary rumen degradable protein.



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