Ability of three dairy feed programs to predict post-rumen outflows of nitrogenous compounds in dairy cows: A meta-analysis.

duodenal meta-analysis microbial omasal protein

Journal

Journal of dairy science
ISSN: 1525-3198
Titre abrégé: J Dairy Sci
Pays: United States
ID NLM: 2985126R

Informations de publication

Date de publication:
06 Sep 2023
Historique:
received: 29 12 2022
accepted: 15 05 2023
medline: 9 9 2023
pubmed: 9 9 2023
entrez: 8 9 2023
Statut: aheadofprint

Résumé

Adequate prediction of post-rumen outflow of protein fractions is the starting point for the determination of metabolizable protein supply in dairy cows. The objective of this meta-analysis was to compare the performance of 3 dairy feed programs [National Research Council (NRC, 2001), Cornell Net Protein and Carbohydrate System (CNCPS, v6.5.5), and National Academies of Sciences, Engineering and Medicine (NASEM, 2021)] to predict outflows (g/d) of NAN, microbial N (MiN), nonammonia nonmicrobial N (NANMN). Predictions of rumen degradabilities (% of nutrient) of protein (RDP), NDF and starch were also evaluated. The data set included 1,294 treatment means from 312 digesta flow studies. The 3 feed programs were compared using the concordance correlation coefficient (CCC), the ratio of root mean square prediction error (RMSPE) on standard deviation of observed values (RSR), and the slope between observed and predicted values. Mean and linear biases were deemed biologically relevant and are discussed if higher than a threshold of 5% of the mean of observed values. The comparisons were done on observed values adjusted or not for the study effect; the adjustment had a small effect on the mean bias but the linear bias reflected a response to a dietary change rather than absolute predictions. For the absolute predictions of NAN and MiN, CNCPS had the best fit statistics (8% greater CCC; 6% lower RMSPE) without any bias; NRC and NASEM under-predicted NAN and MiN, and NASEM had an additional linear bias indicating that the under-prediction of MiN increased at increased predictions. For NANMN, fit statistics were similar among the 3 feed programs with no mean bias; however, the linear bias with NRC and CNCPS indicated under-prediction at low predictions and over-prediction at elevated predictions. On average, the CCC were smaller and RSR ratios were greater for MiN vs, NAN indicating increased prediction errors for MiN. For NAN responses to a dietary change, CNCPS also had the best predictions, although the mean bias with NASEM was not biologically relevant and the 3 feed programs did not present a linear bias. However, CNCPS, but not the 2 other feed programs, presented a linear bias for MiN, with responses being over-predicted at increased predictions. For NANMN, responses were over-predicted at increased predictions for the 3 feed programs, but to a lesser extent with NASEM. The site of sampling had an effect on the mean bias of MiN and NANMN in the 3 feed programs. The mean bias of MiN was higher in omasal than duodenal studies in the 3 feed programs (from 55 to 61 g/d) and this mean bias was twice as large when

Identifiants

pubmed: 37683889
pii: S0022-0302(23)00616-1
doi: 10.3168/jds.2022-23215
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2023, The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Auteurs

R Martineau (R)

Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, QC, Canada, J1M 0C8. Electronic address: roger.martineau@agr.gc.ca.

D R Ouellet (DR)

Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, QC, Canada, J1M 0C8.

D Pellerin (D)

Department of Animal Science, Laval University, Québec, QC, Canada, G1V 0A6.

J L Firkins (JL)

The Ohio State University, Columbus 43210.

M D Hanigan (MD)

Department of Dairy Science, Virginia Tech, Blacksburg 24060.

R R White (RR)

Department of Dairy Science, Virginia Tech, Blacksburg 24060.

A LaPierre (A)

Department of Animal Science, Cornell University, Ithaca, NY 14850.

M E Van Amburgh (ME)

Department of Animal Science, Cornell University, Ithaca, NY 14850.

H Lapierre (H)

Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, QC, Canada, J1M 0C8.

Classifications MeSH