Formulation of Functional Food Supplements: Case Study of Manufacturing Process Optimization at ‘Sarepta Production’, Burkina Faso
Bibliographic record
Abstract
Introduction: In the context of promoting local resources and achieving food sovereignty, plant-based food supplements play a key role. However, their production often remains artisanal, making them prone to contamination and quality inconsistency. Objective: This study aimed to harmonize and standardize the manufacturing practices of four dietary supplements produced at the “Sarepta Production” unit in Ouagadougou, Burkina Faso, by integrating Good Manufacturing Practices (GMP) and Good Hygiene Practices (GHP). Methodology: Standard Operating Procedures (SOPs) were developed for each stage of the production process. Microbiological analyses were carried out on three successive batches at Agence Nationale pour la Sécurité Sanitaire de l’Environnement, de l’Alimentation, du Travail et des produits de santé (ANSSEAT) using standards established by the International Organization for Standardization (ISO standards) to assess sanitary quality. Results and Discussion: The results showed a progressive reduction in total aerobic mesophilic flora, yeasts, molds, and thermotolerant coliforms across the three production cycles. No pathogenic microorganisms like Salmonella, E. coli, or S. aureus were detected. The implementation of GMP, GHP, and Hazard Analysis and Critical Control Points (HACCP) principles enabled effective control of critical points, such as raw material reception, mixing, packaging, and storage. Conclusion: This study demonstrates that strict integration of hygiene and quality standards within small-scale food supplement manufacturing units significantly improves microbiological safety and consumer acceptability. It offers a reproducible model for other local food initiatives in sub-Saharan Africa in general and in Burkina Faso in particular. Keywords: Food Supplements, Good Manufacturing Practices, Microbiological Quality, Harmonization, Local Production, Critical Control Points.
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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 | 0.000 | 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) | 0.000 | 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".