Altering Dietary Cation-Anion Difference in Lactating Dairy Cows to Reduce Phosphorus Excretion to the Environment
Bibliographic record
Abstract
Four early-lactating dairy cows were randomly allocated to 4 diets with dietary cation-anion difference [DCAD; (Na + K) - (Cl- + S2-) mEq/100 g dry matter)] values of +14, +18, +24, and +45. Diets were formulated to be isoenergetic and isonitrogenous, and supplied similar levels of P (0.46%) and Ca (0.77%). The salts, MgCl2, MgSO4, K2CO3, and NaHCO3 were used to alter DCAD. The main objective of the study was to ascertain whether a decrease in DCAD would reduce fecal P excretion in lactating dairy cattle. The experiment was conducted as a 4 x 4 Latin square design with 21-d periods. During the last 5 d, diets were offered at a restricted level and samples of blood, milk, feces, and urine were collected. Measures of acid-base status of the cows were linearly related to DCAD, but the animals did not experience metabolic acid stress. Neither fecal P nor urinary P was affected by DCAD, and there was no change in overall P balance. Plasma P tended to increase and blood concentrations of ionized Ca were enhanced as DCAD decreased; P excretion in milk showed a quadratic response to DCAD. Milk yield and milk composition were unaffected by changes in DCAD. Although DCAD may have influenced P homeostasis in lactating cows, there was no evidence that, within the range of + 14 to + 45 mEq/ 100 g dry matter, DCAD could be used as a nutritional strategy to reduce manure P from dairy cattle.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".