Ability of three dairy feed evaluation systems to predict postruminal outflows of nitrogenous compounds in dairy cows: A meta-analysis
Bibliographic record
Abstract
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 15 N labeling was used as a microbial marker compared with purines. Such a difference was not observed for duodenal studies. The reasons underlying these systematic differences are not clear as the type of measurements used in the current meta-analysis does not allow to delineate if one site or one microbial marker is yielding the "true" post-rumen N outflows. Rumen degradabilities of protein ( RDP ) was under-predicted with CNCPS, and RDP responses to a dietary change was under-predicted by the 3 feed programs with increased RDP predictions. Rumen degradability of NDF was under-predicted and had poor fit statistics for NASEM compared with CNCPS. Fit statistics were similar between CNCPS and NASEM for rumen degradability of starch, but with an under-prediction of the response with NASEM and absolute values being over-predicted with CNCPS. Multivariate regression analyses showed that diet characteristics were correlated with prediction errors of N outflows in each feed program. Globally, compared with NAN and NANMN, residuals of MiN were correlated with several moderators in the 3 feed programs reflecting the complexity to measure and model this outflow. In addition, residuals of NANMN were correlated positively with RDP suggesting an overestimation of this parameter. In conclusion, although progress is still to be made to improve equations predicting post-rumen N outflows, the current feed programs provide sufficient precision and accuracy to predict metabolizable protein supply.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.029 | 0.023 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.037 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".