Nutritional quality evaluation of velvet bean seeds (<i>Mucuna pruriens</i>) exposed to gamma irradiation
Bibliographic record
Abstract
Effects of gamma irradiation on Mucuna pruriens seeds at various doses (0, 2.5, 5, 7.5, 10, 15 and 30 kGy) on the proximate composition, mineral constituents, amino acids, fatty acids and functional properties were investigated. Gamma irradiation resulted in a significant increase of crude protein at all doses, while the crude lipid, crude fibre and ash showed a dose-dependent decrease. Raw Mucuna seeds were rich in minerals (potassium, phosphorus, calcium, magnesium, iron and selenium). Sodium, copper and manganese were significantly decreased on irradiation at all the doses, while magnesium and iron showed a significant decrease only above 10 kGy. The essential amino acids of raw and gamma-irradiated Mucuna seeds were comparable with the FAO/WHO recommended pattern. A significant increase of in vitro protein digestibility was seen in seeds irradiated at 30 kGy. High amounts of unsaturated fatty acids in Mucuna seeds decreased significantly after irradiation. However, linoleic acid was not present in raw seeds but detected after irradiation and it was elevated to high level at 30 kGy. Behenic acid, a major anti-nutritional factor, was reduced significantly on irradiation, indicating the positive effect of gamma irradiation on Mucuna seeds. Significant enhancement in the water absorption and oil absorption capacities, protein solubility, emulsion activity and improvement in the gelation capacity was recorded after irradiation. Results of the present investigation reveal that application of gamma irradiation does not affect the overall nutritional composition and can be used as an effective method of preservation of Mucuna seed and their products.
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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) | 0.001 | 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".