Desmodium tortuosum, Euphorbia heterophylla and Moringa oleifera Effect on Local Rabbit Does Milk Production and Pups’ Performances
Bibliographic record
Abstract
Desmodium tortuosum and Euphorbia heterophylla are fields’ weeds. Moringa oleifera plant is adapted to several agroecological zones and has many food and medicinal virtues. This work assessed these three plants potential to induce milk production. Thus, 96 primiparous local breed rabbit does, 10 months old, with an average 2983.6±212.4 g weight were used. They were grouped into 4 blocks containing 24 animals each. Then, one diet among 4 diets was randomly assigned to each group. Panicum maximum as fodder was mixed with a commercial pellet rabbit feed, the control (Pan). Then, this control diet was supplemented with Desmodium tortuosum (Des), Euphorbia heterophylla (Eup) and Moringa oleifera (Mor) in pellet partial substitution. The parameters monitored were the litter size, the pups’ average daily weight gain, the does’ weights before and during gestation, and after farrowing. Likewise, the milk production at peak lactation was evaluated. As a result, compare to Pan, Des, and Eup diets improved the total rabbit pups’ number from 96 to 112, and it represented a 16.67% gain. But Mor diet reduced Pan diet performance to 76 newborn rabbits, it was a 20.83% loss. Moreover, Des, Eup, and Mor diets induced an improvement in the milk quantity at peak lactation. In this order, these improvements were +15.51, +27.74, and +19.98%, respectively, compared to Pan diet which produced 109.6 g. In conclusion, Desmodium tortuosum and Euphorbia heterophylla could be used as green forages to improve milk production in local rabbit does breeding.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".