Effects of Different Processing Methods on the Nutritional, Phytochemical and Functional Properties of Soya bean (Glycine max TGX 1835-10E) commonly produced in Cameroon
Bibliographic record
Abstract
Soya bean (variety TGX 1835-10E) is a legume commonly produced and consumed in Cameroon. Despite its affordability compared to animal sources of proteins, protein energy malnutrition (PEM) is still observed in the country and especially in rural areas. This can be attributed the way the available soya bean is processed which can easily affect its physicochemical properties and reduce its nutritional value and functional properties. This study was conducted in order to evaluate the effect of different processing methods on the nutritional composition, phytochemical and functional properties of soya bean. The beans were divided into nine groups that were processed differently and analyzed for their total phenolic content, antioxidant activity, oil quality and nutritional composition and the functional properties of their flours. Results showed that the total phenolic content was found to be ranged between 99.84 - 216.85 mg GAE/g and significantly increased with roasting and decreased with boiling treatments. All samples exhibited good antioxidant activity. All treatments altered soya bean oil quality with time. Soaking, boiling, de-hulling and drying considerably reduced the protein (43.49 to 29.93%) and carbohydrate (15.44 to 1.27%) contents of soya bean while soaking, de-hulling, boiling and drying increased its lipid content (11.60 to 15.90%). All treatments significantly reduced the mineral and anti-nutrient (phytate and oxalate) contents of soya bean. The flours exhibited good functional properties, except for emulsion and foaming capacities which significantly decrease with processing. Soya bean can be a good ingredient for food formulation and preparation, both for nutritional and technological purposes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".