Increasing physically effective fiber content of dairy cow diets through forage proportion versus forage chop length: Chewing and ruminal pH
Bibliographic record
Abstract
A study was conducted to evaluate whether the risk of acidosis in dairy cows can be lowered by increasing the physically effective fiber (peNDF) concentration of the diet, either through increased theoretical chop length of alfalfa silage or higher proportion of forage in the diet. The experiment was designed as a replicated 4 x 4 Latin square using 8 ruminally cannulated lactating dairy cows. Treatments were arranged in a 2 x 2 factorial design; 2 forage particle lengths (FPL) of alfalfa silage (short and long) were combined with low (35:65) and high (60:40) forage:concentrate (F:C) ratios [dry matter (DM) basis]. Dietary peNDF concentration (DM basis) was determined from the sum of the proportion of dietary DM retained either on the 2 sieves (8 and 19 mm) or on the 3 sieves (1.18, 8, and 19 mm) of the Penn State Particle Separator multiplied by the neutral detergent fiber concentration of the diet. The dietary peNDF concentrations were altered by changing the F:C or the FPL, and ranged from 10.7 to 17.5% using 2 sieves, or from 23.1 to 28.2% using 3 sieves. Intake of peNDF was increased by increasing FPL but not by increasing F:C ratio because of the reduction of DM intake at the higher F:C ratio. Chewing activity, including number of chews and chewing time, increased with increasing F:C ratio or FPL. Mean ruminal pH was elevated by 0.4 and 0.2 units with increasing F:C ratio and FPL, respectively. Lowering the F:C ratio decreased the duration that ruminal pH was below 5.8 (1.2 vs. 8 h/d). Increased F:C ratio or FPL reduced ruminal volatile fatty acids concentration from 137 to 122 or from 133 to 126 mM, respectively, whereas acetate:propionate ratio was increased from 2.55 to 3.46 with increasing F:C ratio. Dietary peNDF concentration measured using 2 sieves was correlated to chewing time (r = 0.57) and mean ruminal pH (r = 0.75), whereas dietary peNDF concentration measured using 3 sieves was correlated to mean ruminal pH (r = 0.83) and negatively correlated to the time that pH was below 5.8 (r = -0.78). This study shows that the risk of ruminal acidosis is high for cows fed a low F:C diet. Increasing the proportion of forage in the diet helps prevent ruminal acidosis through increased chewing time, a change in meal patterns, and decreased ruminal acid production. Increasing FPL elevates ruminal pH, but in low forage diets, increased FPL does not alleviate subacute acidosis because the fermentability of the diet is high and changes in chewing activity are marginal.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".