Enhancing the nutritional value of cold-pressed oilseed cakes through extrusion cooking
Why this work is in the frame
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Bibliographic record
Abstract
The most abundant oilseed cakes, soybean, rapeseed/canola, and sunflower, and especially those from cold-pressing, contain meaningful amounts of antinutritional polyphenols that limit their potential as plant protein sources. The objective of this study was to remove polyphenols, and especially sinapic and chrologenic acid derivatives in canola and sunflower, respectively, using pilot-scale extrusion, and without compromising the nutritional and the technological quality of the protein fraction. Extrusion significantly increased the ratio of soluble to insoluble dietary fiber from 0.45 to 0.58 in canola and from 0.19 to 0.31 in sunflower, whereas the opposite was found in soybean (0.52 to 0.36). Canola (67.7 mg GAE/g) and sunflower (58.9 mg GAE/g) exhibited large quantities of polyphenols, which mostly consisted of sinapic and chlorogenic acid derivatives, respectively. Extrusion increased the proportion of free polyphenols and did not significantly reduce the amount of sinapic acid derivatives in canola. On the contrary, extrusion decreased the content of free polyphenols in sunflower by 68%. Generally, the extrusion conditions shown in this study resulted in limited protein denaturation and aggregation and a moderate decrease in β-sheet structures (up to 59%), which led to similar liquid holding capacity and enhanced protein solubility. Extrusion notably increased the gastric protein hydrolysis of soybean cake, but it negligibly affected that of canola and sunflower counterparts, possibly due to the counteracting effect of indigestible quinone-protein adducts. Extrusion is a promising technology to reduce polyphenols meaningfully in certain oilseed cakes while retaining or improving protein quality.
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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 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 it