Effect of Fermentation on Nutrient and Antinutrient Contents of Cocoyam Corm
Bibliographic record
Abstract
Objective: Cocoyam corms were fermented with the aim of enhancing and reducing its nutrient and antinutrient contents respectively. Methods: Cocoyam corm was fermentated naturally by submerged fermentation method in a sterile medium (distilled water) for four days. Microbial examination of the fermenting corms was carried out at 24hours interval for four days. Results: Twenty bacterial strains were isolated within the fermentation periods. They include the general: Micrococcus species, Lactobacillus plantarum, L. fermentum, Enterobacter, Escherichia coli and Staphylococcus aureus. The total bacteria count increased from 5.70 log cfu/ml to 8.97 log cfu/g while fungal count increased from 3.33 log cfu/g to 4.84 log cfu/g. Temperature and the total titratable acidities increased from 27oC to 35oC and 1.13% to 3.72% respectively while the pH values decreased from 5.68 to 3.75. The result of the proximate analysis showed that the fermented sample had higher protein (12.00%), ash (2.84%) and fat (4.84%) contents than the unfermented sample which contained 7.30%, 2.4% and 4.55% respectively. However, moisture, fibre and carbohydrate contents decreased from 9.70%, 3.00% and 73.04% in unfermented sample to 8.94%, 2.78% and 67.60% in fermented sample respectively. All the antinutrient contents decreased at the end of the fermentation [phytate (1.32-0.38) g/100DM, oxalate (0.72-0.21) g/100DM, tannin (0.18-0.07) g/100DM, saponin (0.45-0.22) g/100DM, hydrocyanide (22.27-10.22)g/kg of the fermented sample than the unfermented one.
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.
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) | 0.001 | 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".