Effects of using Water Hyacinth (Eichhornia crassipes L.) in the Diet of Swamp Buffaloes on Nutrient Digestibility, Rumen Environment, Purine Derivatives, and Nitrogen Retention
Bibliographic record
Abstract
The present experiment aims to evaluate the effects of incremental levels of water hyacinth (WH) in Para grass (Brachiaria mutica) based on the diet on nutrient intake, digestibility, and nitrogen retention of growing swamp buffaloes. Four male buffaloes of 305 ± 8.40 kg were allocated in a 4x4 Latin square design. The treatments were 25, 50, 75, and 100% WH (DM basis), replacing the Para grass (PG) corresponding to WH25, WH50, WH75, and WH100 treatment. Urea-molasses cake was used to supply the dietary crude protein intake so that this was 210 g/100 kg live weight per day for all the treatments (DM basis). The results showed that although the dry matter (DM), neutral detergent fiber (NDF), and metabolizable energy (ME) intake were not significantly different (P>0.05) among the treatments, these were numerically higher for the WH50 treatment. Especially in the daily ME intake (MJ/k g LW) was 39.1, 43.4, 41.7, and 39.9 for the WH25, WH50, WH75, and WH100 treatments, respectively. With 50% WH replacing PG in the diet, it gave potential for better nutrient digestibility, nitrogen retention, and daily weight gain in the present study. In conclusion, WH could be used to replace PG in buffalo diet up to 100%. At a level of 50% replacement of WH to PG in the buffalo, the diet was optimum based on the utilization of nutrients and energy of WH, lower feed cost, and environmental improvement.
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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".