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Effect of Fermentation on Nutrient and Antinutrient Contents of Cocoyam Corm

2013· article· en· W2034172642 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Pharmacy and Nutrition Sciences · 2013
Typearticle
Languageen
FieldMedicine
TopicPapaya Research and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsAntinutrientFood scienceFermentationChemistryTanninPerillaPhytic acid

Abstract

fetched live from OpenAlex

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.132

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.048
GPT teacher head0.422
Teacher spread0.374 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it