Some Nutritional and Physical Properties of Different Zambian Market Classes of Bambara Groundnut (Vigna subterranea)
Bibliographic record
Abstract
Selected nutritional and physical properties of the two commonly cultivated Zambian market classes of Bambara groundnut (red and brown) were investigated to establish their end-user traits. Nutritional (essential amino acids, proximate and mineral compositions) and physical (hydration capacity, hydration index, swelling capacity, swelling index and 100 seed mass) properties were investigated using established standard methods. All the essential amino acids were present in both the red and brown Bambara groundnuts. The highest amount was recorded for leucine (9.7 g/100g protein) in the brown Bambara groundnut and least for methionine (1.2 g/100g protein) in the red market class. All the essential amino acids except methionine in the brown Bambara groundnut market class were above the recommended WHO/FAO provisional requirements for children (2 – 5 years) and adults. The crude protein values ranged from 14.62-18.55 g/100g, total ash (4.21 – 4.29 g/100g), crude fibre (2.79 – 5.33 g/100g), fat (6.28 – 6.54 g/100g), moisture (8.95 – 9.13 g/100g) and carbohydrate (59.23 – 60.34 g/100g). Potassium was found to be the most concentrated mineral in both market classes, followed by phosphorous, magnesium and calcium, while lead, mercury and arsenic were not detected. The swelling capacity, swelling index, hydration capacity, and hydration index of the two market classes of Bambara groundnuts were not significantly different, whereas their 100 seed mass was significantly different, with the brown recording the highest.
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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 | 0.001 | 0.001 |
| 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".