Effect of processing methods on the nutrient, antinutrient, functional, and antioxidant properties of pigeon pea (Cajanus cajan (L.) Millsp.) flour
Bibliographic record
Abstract
Pigeon pea (Cajanus cajan) is an important grain legume in tropical regions, including Ethiopia. Yet its nutritional value is often limited due to the presence of antinutritional factors and limited studies on how traditional processing methods affect the nutritional, antinutritional, functional, and antioxidant properties of the flour. This study investigates how traditional processing methods—soaking, germination, cooking, and roasting—affect the nutritional, antinutritional, functional, and antioxidant properties of pigeon pea flour. Results indicated that processing methods significantly influenced the proximate composition; germination enhanced protein content from 23.50 % to 25.50 %, while cooking and roasting decreased it. Mineral content analysis revealed that calcium, iron, and zinc levels were generally reduced, with cooking leading to the greatest decreases in mineral concentrations. All processing methods effectively reduced antinutritional components, with germination achieving the most substantial reductions in phytic acid and tannins. Functional properties were also affected: bulk density decreased across all methods, while water and oil absorption capacities increased, particularly in germinated flour. Germination notably enhanced total phenolic content from 209.61 to 252.60 mg/100 g and antioxidant activity, as measured by DPPH and FRAP values. Conversely, soaking, cooking, and roasting decreased phenolic content and antioxidant capacity. Overall, while germination improved the nutritional and antioxidant profiles of pigeon pea flour, other processing methods significantly diminished these beneficial properties, highlighting the importance of processing in enhancing the nutritional value of pigeon peas.
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.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".