Effect of infrared heating on the functional properties of yellow pea and green lentil flours
Bibliographic record
Abstract
Abstract Background and Objectives Value‐added utilization of pulse flours faces challenges related to their functionality in many food applications. The present research assessed the use of infrared heating (120°C vs. 140°C) tempered (20% vs. 30% moisture) green lentil and yellow pea seeds as a means of tailoring their functional properties. Findings Some flour functionalities were mildly affected by processing and, in most cases, were correlated with protein surface hydrophobicity and damaged starch content. Solubility at pH 5 was relatively unchanged in response to processing, while the values were slightly lowered at pH 7. The water (WHC) and oil holding capacities (OHC) improved, although OHC tended to decline as heating temperatures increased. Both pulses had poor foaming capacities but high foaming stabilities that remained constant after processing. The highest emulsion activity (EA) for pea was with the 120°C and 30% moisture treatment whereas for lentil it was with 120°C and 20% moisture; the emulsion capacity declined after all treatments. Conclusions Select conditions of infrared heating coupled with tempering of pulse seeds before milling can modestly improve the flour's EA, WHC, or OHC. Significance and Novelty Yellow pea and green lentil flours from infrared pretreated seeds can now be more easily formulated into applications based on their functional properties.
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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 | 0.000 | 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 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".