Potassium carbonate as a supplement to improve milk fat concentration and yield in early-lactating dairy goats fed a high-starch, low-fiber diet
Bibliographic record
Abstract
This study investigated the use of K 2 CO 3 as dietary buffer to prevent or to recover from low milk fat production when early-lactating dairy goats are fed a high-starch, low-fiber (HSLF) diet. At kidding, 30 Alpine goats housed in pens with Calan gate feeders received a total mixed ration with a forage-to-concentrate ratio of 55:45 on a dry matter (DM) basis for a baseline period of 27 ± 4 d. Goats (milk yield, 4.14 ± 0.88 kg/d; milk fat, 4.28 ± 0.52%; mean ± SD) were then assigned to 1 of 10 blocks according to parity (first vs. second or more) and milk fat concentration, and fed a HSLF diet containing 45% forages and 55% concentrates for 2 experimental periods of 28 d. Treatments were identified as (1) control, in which the HSLF diet was fed throughout both periods; (2) preventive, in which the HSLF diet supplemented with K 2 CO 3 (1.6% of DM) was fed during both periods; and (3) recovery, in which the HSLF diet was fed during the first period (P1) and the HSLF diet supplemented with K 2 CO 3 was fed during the second period (P2). Data from P1 and P2 were analyzed separately. In P1, preplanned contrasts were used to evaluate the preventive effect of K 2 CO 3 (control and recovery, both groups receiving the same diet during this period, vs. preventive), and in P2, to assess the potential of K 2 CO 3 to alleviate an already existing state of low milk fat (control vs. recovery and preventive vs. recovery). Feeding the HSLF diet in P1 moderately decreased milk fat concentration (−16%) and yield (−13%) as compared with baseline. Dietary addition of K 2 CO 3 decreased DM intake by 12 and 14% in P1 and P2, respectively. Ruminal pH was not different among treatments. There was also no significant difference in milk yield (4.13 and 3.71 kg/d on average in P1 and P2, respectively) for any tested contrasts. In P1, milk fat concentration and yield did not differ among goats fed control (3.58% and 151 g/d, respectively) and preventive (3.67% and 148 g/d, respectively) diets. In P2, milk fat concentration and yield did not differ among goats fed the control diet (3.38% and 137 g/d, respectively), and diets where K 2 CO 3 was used as preventive (3.44% and 126 g/d, respectively) or recovery treatment (3.25% and 113 g/d, respectively). Supplementing a high-concentrate diet with 1.6% K 2 CO 3 was therefore not effective in either preventing or suppressing already existing conditions of low milk fat production in dairy goats.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".