Effects of supplementation Senegalia macrostachya seed flour on the zootechnical performance of traditional chickens from Burkina Faso
Bibliographic record
Abstract
The decline in productivity of traditional chicken in Burkina Faso is mainly linked to the management of its feeding. This work aimed to evaluate the acceptability of Senegalia macrostchya seed flour in the feed ration of traditional chickens. This study involved 50 traditional chicks aged eight weeks. The chickens were divided into five batches of ten chicks corresponding to the five experimental diets containing 0%, 1%, 2%, 3% and 4% Senegalia macrostachya seed meal. The nutritional composition of Senegalia macrostachya seed meal, growth parameters and carcass characteristics were determined. Senegalia macrostachya seeds were mainly rich in protein (40.3 ± 0.74% DM) and fat (27 ± 6.45% DM). These seeds also contain mineral salts with particularity for calcium (0.41 ± 0.00% DM). In addition, Senegalia macrostachya seeds were rich in palmitic acid, α-linolenic acid, linoleic acid, and oleic acid. Thus, the group of chickens fed with 3% supplementation of Senegalia macrostachya seed meal had a feed conversion ratio (4.61), individual feed consumption (42.56 g/d) and average daily gain (11.29 g/d) higher than the other supplementation levels (0.1, 2 and 4%). However, this supplementation resulted in a decrease in abdominal fat of the batches of 1%, 2%, 3% and 4% compared to the 0% control batch. Senegalia macrostachya seed flour could be a solution to the protein source problem in traditional chicks.
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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".