Physicochemical Characteristics and Microbiological Quality of Honey Produced in Benin
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Honey is a very complex biological product. It has great diversity, giving it a multitude of properties, both nutritionally and therapeutically. This study aimed to study the physicochemical and microbiological characteristics of honeys collected during the dry and rainy seasons in the different phytogeographical areas of Benin. The study revealed that all honeys had pH, water content, electrical conductivity, ash content, free acidity, total sugars, and reducing sugars, respectively, ranging within 3.65–4.09; 12.07–13.16%; 530.25–698.50 μ s/cm; 0.42–0.53%; 35.67–40.52 meq/kg; 60–70%; and 58–70%. Moisture content, total sugars, and reducing sugars varied very significantly (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mi>p</mml:mi><mml:mo><</mml:mo><mml:mn fontstyle="italic">0.05</mml:mn></mml:math>to<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mi>p</mml:mi><mml:mo><</mml:mo><mml:mn fontstyle="italic">0.001</mml:mn></mml:math>) from one area to another and from one season to another. However, only the production season has a significant influence (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M3"><mml:mi>p</mml:mi><mml:mo><</mml:mo><mml:mn fontstyle="italic">0.05</mml:mn></mml:math>) on the pH of the honey. With regard to the ash content, free acidity, and electrical conduction, no significant difference (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M4"><mml:mi>p</mml:mi><mml:mo>></mml:mo><mml:mn fontstyle="italic">0.05</mml:mn></mml:math>) between the zones or between the seasons was observed. The results of the microbiological characterization showed that there is heterogeneity in the microbial load. These results have shown that these honeys meet international standards and their characterization will make it possible to obtain Beninese quality labels.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it