Comparative Evaluation of the Antioxidant Properties of Whole Peanut Flour, Defatted Peanut Protein Meal, and Peanut Protein Concentrate
Bibliographic record
Abstract
Defatted peanut meal is a low value agro-industrial residue from peanut oil production with potential use as a value addition food ingredient. In this study, peanuts were roasted at 100°C for 5 min, de-skinned and milled into whole peanut flour (WPF) from which the defatted meal (DPM) was prepared by acetone extraction and the peanut protein concentrate (PPC) obtained from the DPM using isoelectric pH precipitation. The protein content, amino acid profile, total phenolic content (TPC), total flavonoid content (TFC) and in vitro antioxidant properties of the peanut samples were then determined. Results showed that DPM had a TPC of 0.12 ± 0.02 mg gallic acid equivalent (GAE)/g, which was significantly ( p < 0.05) higher than and twice the levels in WPF and PPC (0.06 ± 0.03 mg GAE/g). However, WPF had TFC of 0.21 ± 0.01 μg quercetin equivalent (QE)/g, which was significantly ( p < 0.05) higher than DPM (0.16 ± 0.03 μg QE/g) and PPC (0.11 ± 0.05 μg QE/g). However, PPC had superior amino acid profile in addition to stronger radical scavenging and metal chelation activities than WPF and DPM. The results suggest that PPC is a protein rich product that could be utilized as an ingredient in food product fortification to enhance nutritional quality and in the formulation of functional foods with antioxidant benefits.
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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) | 0.000 | 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 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".