Evaluation of models to predict the stoichiometry of volatile fatty acid profiles in rumen fluid of lactating Holstein cows
Bibliographic record
Abstract
Volatile fatty acids (VFA), produced in the rumen by microbial fermentation, are the main energy source for ruminants. The VFA profile, particularly the nonglucogenic (acetate, Ac; butyrate, Bu) to glucogenic (propionate, Pr) VFA ratio (NGR), is associated with effects on methane production, milk composition, and energy balance. The aim of this study was to evaluate extant rumen VFA stoichiometry models for their ability to predict in vivo VFA molar proportions. The models were evaluated using an independent data set consisting of 101 treatments from 24 peer-reviewed publications with lactating Holstein cows. All publications contained a full diet description, rumen pH, and rumen VFA molar proportions. Stoichiometric models were evaluated based on root mean squared prediction error (RMSPE) and concordance correlation coefficient (CCC) analysis. Of all models evaluated, the 1998 Friggens model had the lowest RMSPE for Ac and Bu (7.2 and 20.2% of observed mean, respectively). The 2006 Bannink model had the lowest RMSPE and highest CCC for Pr (14.4% and 0.70, respectively). The 2008 Bannink model had comparable predictive performance for Pr to that of the 2006 Bannink model but a larger error due to overall bias (26.2% of MSPE). The 1982 Murphy model provided the poorest prediction of Bu, with the highest RMSPE and lowest CCC (24.6% and 0.15, respectively). The 1988 Argyle and Baldwin model had the highest CCC for Ac with an intermediate RMSPE (0.47 and 8.0%, respectively). The 2006 Sveinbjörnsson model had the highest RMSPE (13.9 and 34.0%, respectively) and lowest CCC (0.31 and 0.40, respectively) for Ac and Pr. The NGR predictions had the lowest RMSPE and highest CCC in the 2 models of Bannink, whereas the lowest predictive performance was in the 2006 Sveinbjörnsson model. It appears that the type of VFA produced is not a simple linear relationship between substrate inputs and pH as currently represented. The analysis demonstrates that most rumen VFA stoichiometric approaches explain a large part of the variation in VFA molar proportions among diets, in particular for Ac, whereas predictive power for Pr and Bu differ largely among approaches. The move toward feed evaluation systems based on animal response might necessitate an improved representation of rumen fermentation, focused on improving our understanding of VFA proportions in diets that vary from the mean.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".