Formulation of Senescent Plantain Dish with Various Local Cereal and Leguminous Flours for Feeding Rats: Growth Performance Evaluation
Bibliographic record
Abstract
The aim of this study was to valorize senescent plantain. Therefore, a traditional dish named Dockounou was prepared with a mixture of senescent plantain and various millet, soybean, sorghum, cassava, maize or rice flours. The growth performance of several Wistar rats feed by Dockounou was followed. Thus, batches of rats were fed for 15 days with three formulations (F1, F2, F3) in proportion of 90:10, 80:20 and 75:25 (senescent plantain dough/flours) obtained after two cooking modes (dry cooking: baked ; wet cooking: boiled). The effects of these formulations were compared to control diet (C. diet). Beyond the control diet, rats fed with the soybean baked Dockounou presented, the best following growth parameters: weight gain (2.82 to 4.19 g/d), food intake (8.92 to 9.72 g/d), feed efficiency (0.10 to 0.42), proteins intake (8.28 to 19.67), proteins efficiency (0.13 to 3.15). The physicochemical and nutritive characteristics of soybean baked Dockounou were as follow: ash (2.93 ±0.15 %), proteins (10.62±0.59 %), carbohydrates (15.46±1.53 %), calcium (232.04 – 558.20 mg/100g), potassium (313.97 – 385.11 mg/100g), magnesium (42.40 – 72.22 mg/100g), sodium (211.24 – 303.85 mg/100g) and phosphorus (330.70 – 433.71 mg/100g). Also, the study showed that, two formulations, 80:20 and 75:25, have really impact on rats growth. These results suggest that soybean baked Dockounou with important proportions, 80 % and 75 %, of senescent plantain dough can be effectively used in the diet of laboratory Wistar rats regarding the good zoological performances there are obtained.
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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 | 0.003 | 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) | 0.000 | 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".